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{
"content": "Solve the following coding problem using the programming language python:\n\nThere is a directed graph with N vertices numbered 1 to N and M edges.\nThe i-th edge is directed from Vertex A_i to Vertex B_i, and there are C_i coins placed along that edge.\nAdditionally, there is a button on Vertex N.\nWe will play a game on this graph.\nYou start the game on Vertex 1 with zero coins, and head for Vertex N by traversing the edges while collecting coins.\nIt takes one minute to traverse an edge, and you can collect the coins placed along the edge each time you traverse it.\nAs usual in games, even if you traverse an edge once and collect the coins, the same number of coins will reappear next time you traverse that edge, which you can collect again.\nWhen you reach Vertex N, you can end the game by pressing the button. (You can also choose to leave Vertex N without pressing the button and continue traveling.)\nHowever, when you end the game, you will be asked to pay T \\times P coins, where T is the number of minutes elapsed since the start of the game. If you have less than T \\times P coins, you will have to pay all of your coins instead.\nYour score will be the number of coins you have after this payment.\nDetermine if there exists a maximum value of the score that can be obtained. If the answer is yes, find that maximum value.\n\n-----Constraints-----\n - 2 \\leq N \\leq 2500\n - 1 \\leq M \\leq 5000\n - 1 \\leq A_i, B_i \\leq N\n - 1 \\leq C_i \\leq 10^5\n - 0 \\leq P \\leq 10^5\n - All values in input are integers.\n - Vertex N can be reached from Vertex 1.\n\n-----Input-----\nInput is given from Standard Input in the following format:\nN M P\nA_1 B_1 C_1\n:\nA_M B_M C_M\n\n-----Output-----\nIf there exists a maximum value of the score that can be obtained, print that maximum value; otherwise, print -1.\n\n-----Sample Input-----\n3 3 10\n1 2 20\n2 3 30\n1 3 45\n\n-----Sample Output-----\n35\n\n\nThere are two ways to travel from Vertex 1 to Vertex 3:\n - Vertex 1 \\rightarrow 2 \\rightarrow 3: You collect 20 + 30 = 50 coins on the way. After two minutes from the start of the game, you press the button, pay 2 \\times 10 = 20 coins, and you have 50 - 20 = 30 coins left.\n - Vertex 1 \\rightarrow 2: You collect 45 coins on the way. After one minute from the start of the game, you press the button, pay 1 \\times 10 = 10 coins, and you have 45 - 10 = 35 coins left.\nThus, the maximum score that can be obtained is 35.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
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] |
codegen__primeintellect
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codegen
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{
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",
"part_3": 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zhkO9dP3p2qQWS/XqBt8nQaEbHA+wXGOf4AztpkGAjpp5nWGfZoVWo3I3cWMOTm0CRYEBowH08IaX54ImrJwzwLZkw3Nd+uRJBUrWOAPoM+kKp7FeNlI/+/3NME8hlC7BhwYbXTMLdIOlFN4RpE0zf72MhLk3p3ZUSGPV5U0XWEVBDAoPaaORatoK4cSsbdp/o/Fl2Q7l+E3HjsQ0RRDxziTwUDVVjg0UReZ9i6MoKzsWBWJSvEVo8ZvkHFIEl9EHckS1T8g9NKgaKmdz4aPLifR+C7VbbHDOyYzcDAH8ulSvpPxoDpdSdvco2rRKP3HHQ1VOw/TNUNHQsU/KVqThnvXgMFydWlNxocojRJ9Em7H4Sp2l7RvRtingIZpgAQmnqvxsxSvyDySibhFlULRLWZk38M+acuzTxg5LVFe6URZLec1pMbleWlFfZtuEttoYtgyubDLhmF4lVZIhu0JlRqjxwGgnWS+qOKs3rpTML2qRWKwPCLpQWnOHapFGT6B9FB8y2MrRcomlodNwOFwwaBLip17clVR1mire2s3K1JpUnAJ+XdsDtEow7QsUUq2YcijA7RrjmB1q5V/YIdGkncLwdigjWEzDEdBm1BQqmfqo4DFV3LUc5FRHrw6TNdMIrxSGNB4uqsppDRy0QpVpQCdhk5jlDKqq0uC+Lu3k0uVFNeOou2vEaaCbVVidc86kW4cEUhWNAAwl6zigYlRuBxm1ts1BgZIgxh7FT4rl75wI6GlG/UkZ0kV6rwMCkhTN1RYmitar51FsZJ0rqRsJpGGt80DZG4NJk8aYtL0KkJteCGxvre+LP1EOQ6YCoJaIsCtRS3LIIdCp6mvWAG9hPkewrdcJeMDpp5klgYFvVhXlUmdZ+iRl9bHL7AWb7hYkVJL5AyJiF9MLwFDJwNc7OzFBcszPTMQHmbMR4/eTLzYyh+KhJnmY3adunUEOD5c9SIINDGwMQTtTbIFOZLPu8LWsP7OLXHOqBwzanTavXM1yvbJDp/dH+KhZl1+yx6kLpMA4Cs0pPgAj5KxtfHpbJBVinhTR1UgHNwtzfKH+qBv2QPNSJxs0MtcLJUDIJpk3Hea15sPZZkKhhbK0Jpyyn6Lp1ILGUKyphwrErZuQbxlvcz9lFSNGhEvDBtIFMg0m34W9ZNp4ZBmZECiCpaG52F4yHuakULbUWIn5lO4m7Ho7rhNh4JqEwu9KCznK+5sQ+N6R5iO5iE7Q1YaZz8o2dqcdvS5yijabYRAmYS4JixNNEwPAE7OPm5CA6EBtsQNqaJ5rGKOT57H+Bjs+1dS/4ZNhthg0RlQpqsFwpyM4dHhNgWT/vUYDGFrYiHEngRYbBkVG5WDKoPdKBj3INDZs3d4KpsRRiSYxUWBGE2v4gvUmzSkaM5kb+byWSb1zIyhcgTxCk8IDMkZbZIAwqw8cJWpMogUD11wtp81sARjrgOpcChNFLWcGs2wj27tiP9M28t7rinqmo4ce3ui1DM1s2a/QuSegbjqtgJSp1irUiVZnGhptWHKJEjSr3lfm6FC7qpQ41qSBhsnJLHAQurX4IITZumQAaZgIKNWk9UoWVXGlGwdIhI4wL32k7PWoOl0O0+lliuMkxFh3tlzqoQ35iGEyI526FlqR7FPP6Gk31dAFP1Y5rJB+N3zHzTaNVB09T+m4XM06hdNWKXwIwTRxJ2iemmUF+92m3nUTcjttyIMXbFhXJsaSsWK9JwVPZyqIJJOwRsNSU5MrmbJsInmumCwc2hEKvCRC3yDHgJAaN5DW0xp/Ac9QsyB2pE1flk4/2j3DyzN5JHrjynlP0Q3FRlFHR09vKJ10m/SCzKSvC51ws8SmvL/WNY1QPVW0wX1U4yjvutS1hK5utFX43EqvFVWrMwUuv2yctqaDAEfbrCAu0JN1zIREJ5s0ZqO6gCEXKbsmoI19TSbYPknI0TBKqUzz0+zc7yrxfdF29au04FZlQebKyXoHzCW0KUiYjfXq2MCVrYnbVxck2pMmHTYApqviWTPIFfqptAyxDHGBSyKyJ1CSVG9JNBvMfZjbRxBClJGyPiSaWfLACrn1CtggwU5fNtJHzV/Ah1WGEvAeip1n20QHjP1SRWoqeRZjTCBGmaUDqjhTBAPKQF3tsVKkp4TiStvSOKST7htWIslbtOizaM1zJbVngUbgNHUEVE2KZgWb1EiQhCNrwkbLe42a2M7Juh9koUgEoBKoEaYBU0qKCiYmPJlaEy221biLclPW5UVvqisbGBlntUKfGrjaosSvmHAp7Zwl+AKCkRTBSPJHN+d48nZNxJAY327Sn3tvSJ6NEjxpVkbAsqYgOPqmYR9oEmbatVcyh83Gvq1WJ1i3uvQzTwGtC9E+WIbAB6S2m+MQxsWqiMtNLJuFgyvpliNj6abdsC/awHVQqFbTG0LENC9CxjJNXjPOHsnZ0KjTEp+GLZrjcYd0I6ZR7EJfC8o3U21FsV1sWEj/BBPcpJC7SRWxRNKEmdI8NhJG2qYkD2QpBnEjLEcvn8oT2lCvhNvLg9+XqVDIkGnVnij5FTammJTQVRQwBQ5VC/9SoMeg3KHcLcop9dNNLF6TU6Mhs2OYMdgeaadycY4rfTzM+qWHdbOjYTMayrZqZ4ydZ7mwDvificNeSVVsEtl/yr3CdJVO0l9IvLK1MSlzrtaPCYCEbv5u+HtZ/mF6pdNimnRoe5fcHbUXRedTRcAzTUyttUsMqz1kCtWofDJ+Zar+Cd6+BSFEXquWIX+lqQMeiJ4JbDAkRcwzIdHJHzsGuk7ZEjKlGnY17f1Tn1SfIj5FfX7pfUMbDdlUaAQpuGOSBaeq9PtrDVZZ2RJXkjclhBUQAeExrfQb9XOrslrw/nRWTbzUMP2OdSmogtZ9yVwoAKnL5syBk8VsRxbTek384V2rkXSxTzG8bkmeGJAoXlVJjuQ5WfWdJmyatvMBqQUmMkYdZ042hI3FR7iOVveYs+kcoaDFah0Bfq/NWdkO1FPwvpZVWBxGmD0WoFrKUsR+dsvrfXSo+xI+QdfETUucaQYwVN+zTJUtcVXux6co9Q/jDYOnQhlQsg+KSiu9cpAeZ5hI9KqsBKM/gPYu7nAwVSwelQ2NnAatQJlE0B/OpB1xHGVj7XN+LQCeQT6QPpO9grVhTB35pHAsAhxNHAg9oqTCRQlknG40ATxCo9PT+susV/bdGIg+XDQU6E18tTlp7wfUja9HFXR9/EDZa2JKcVI9pFBJDE1U94GskR9EiqRUcOBCs/p3UxV8mmkctQFMW3U/wWVuqbg7vVL2TXTEDZsvmw0DwqJVY4YgnaUSFFfXC9shq5s2CWDcEp+IYrcTN/Mw1PEVZc4UeLEXkS1fDBazDcEoQGC0MtydIpKoVa/YMpyvUmUT9WYt+B0NmvFbCFeyAdFeQQZnrXAztM9gI1VfHJpGmqBPNu80y0ejxmyjEM9MnwhuC1oo4MakhwiGTFN0G5DammqSJ2Bq75e5ZpEMZL47+Elz+Dfjsh54O6G1UwYKFyYSR8ygTlzQVJfIzVanzREWRwA+08B4V/vltBS3zjzN+AQDuReLvSWm+ArWZBtSNVxJCjBUTSOaQ+WM2qXRnup+2SzuMvFbsgU56jKgFdgpaVkcZrtMlVCYwNvQg5i2ojIPF0FPXw+FBrba7KUqux6JwJ5l1XpfNDwyySBcvh2jFKQynShwubVFjjxJDng8enV6gSz6sLYMxmcCPdxPqylkBkeQToMT4cI2ISBwQqskQl417sHgWbYH1WnMfBrDqWW9XiK59ShA9Ey2eCtnsDadgkysHX5UdJS0A8Ma+WZ08W0YCvBrMquOStN4tV4jrF7yDryzbNZm+7TUxYz32EyzCA0zl0m8L/VC2E+rm3sClL31NS/mOlqsEqdvfQWc0Upx4sypm/QGZdZt+rWjvip+AXGuKuX0h9YZLeUG9LxB4yEZEBtbf5pYOg9P29yQpjEXDvQtzUgdD9nwLfSmFOAC3A7N+bbSuEpfLqVJDesPgIEGN+D0tWNIVxlrT8DLLBueAGFYswckHMOoRuT/ywTlJhDbFLivZIK+tPhWUUMUYnTR+6pPbO1iYWkfQ9aLorSUxTZq3spDm/SXVa1sihyauQm1QexMAC3dIOzEBwgEiDJPikTMhIDbHAZoMc2OeJ7paB/CXzakYH9RGkOkiLi41l7g1u3fsc4kxwsv1VqDFMW3rhYpMDqW4GxnqtMAMqZqiw1WEDrcQdye5tTRLhPtYot8aqcQ3QQdvEEZ2WCUNERRFmOlfF01kRq4l2gzCVml9XI5wzfIGdEPpqhCkxir2kG3MPINmh/aYsHJo3zmSkKGJqugiKt+DsCCJsvGhoo5fHeivgzNsgOUN6L3VTmzE6mokYBQAVgHGWmzuVZgvqNj4GM8aUJV+22YgiwVpkx0jFmcwWIQxzWsw79G9wVVIxz+h3RKdfRp8vA9+b/88W/XX/74+7/++Y9//fMvf/z7/vfEn/7fv13/+5c//vk///iv+Ol///M///q3/9j//Dt+D3/z17+9f8IJaMJhme/PgBL/mf6/fkXj3HH2nh6VAWBFdgbWewDsCwdYZYe7Fji5euw5zt+gcYrpRL1nS8dop2JjxXV3qhrj1e4t2d8RIjFjYxcpEdP3NyKf2KV0ekqAiVg0d6H0Cd0jfvUx2vEuYF2MI/NzRd+rve+t0V/xP8zfS9sV1nMz4RczR7ofA1ZMMvq98npyZcqIzF5rVA7g2/BP7vpwgUk4AeXsfqAggRveCWVmMXa81fffpEgC77DD28/sPo6NrNB7X89nLCozAUDSHtU1MuXKLvZLHMEcKqHRvE+Zg5am5SiaN4+Uc0AW9/eUI10YE5Pn6mlcGoJDI8/Da0NBOmctx62dRqD7D8pD6yI5oLWbn8nGAhXGWunzQT2Ax7P3EVdAoGqJ2dyf0h6tmVDP2W80vW4+FAne66I9lrohinw3Lj4OXKPhWUpJj1NGuOjtT87M41EfpffJBiYFk4IObEIMaxpxSaP3WZ/AGIiZ/UfzkQlDSrkPt9wfwAR1B3C9/REf5GOYg8uL4vyF75gbY7YQ3i3lHuVINNHLZ99eOeiD6MTuyv70zNlAe9ZiCLJAQn4nyelkNqwFR+MaIeKIziLPy+QQDdjj3BYXHoFcDPH7ztqRbpuANK7UHqUMhLh+D94W6Wd0+t1n96o6H92fkB+zSpwJe72s+giIE1m5891RD4OOvKSC2vWAD2lB3HbF1x6qT3gD7bvtD+8zKDP7HfRoPqDoiO5fe055gqHmXp0xIsphvoXGVHreLVPKZ1kR71/f10asbYcn1F5dZ8pPWYpdZqz7m8vslzUwio906miRnseMXJqdlL3zC28vQPR7NbX1dkFWRJX0GqMiPxkr8f4DmclfmI/NN0oq2BDMSKRm+P70XRC1I5cc7LGzlblps26YBDjZEWxK59IJgsEq2xV+ekVegYmf6KO/nFyC396F18K4er+2xXH3OhIQ+wf90URHqtd2NlFO45609L0a06OsdvjA93wx5+zl4vo/CSdgwdqM9R124A18jPjUHDMR3uFcr6sT82p0AF7GFOWs3wOmzzCqnYsPClkb6pKRYuMN8t8lGCHJCcmVvUjaq8RJdPR+JPkZpBEY/CxX4rLRu61z//uxy0Mi0SfDaKDj0PEYOy9Zj6AhsYdtH4/zwUcF0fZ8D8Si4j95ZYTrUHHqrjwIg/HGDIUrL/wRwdtq9b7rS01vEQFXfg4oVqr7U9frfknc2j7U8hHn5iyy7Id3nxKJLLr9GfOxLw115/0nr5EVqsiRB3cSGVMEzpYS0ZqGemfdRHAJ8StIhsVhGqbDg4uilfepYd2P/Yzy04JcnCN0xlHysnN/D2S2NshoK+s8FNC5qJV04gR/hU54zyOhdj5yxxOs6YBGu+i9OvsLuKK16r6kfhpEdK3FhcyHZ0ZXGPwjHbVViLPuJcA1QBdfQs73p65H3CgEgJ5dsEIecD9qdFCOvhH6E33uvRrpcw8DrX0Irg9YWpfsfMjTU9T0zakom4dtsb+nsrVYjprqieOMBHGOxzPAUTDyF+hhUsC7qbGPKEGFGnCXM+21p0PU2sVxip3FJfA9oha8ewBu1hDsVsRwxjUKczc+EJ5YRHT39eYbiAdUgtxfxmA00hlx7vc/HxENYMV3ucAFQrPr8DyaZ2kiRcELbWOsOFoourcf2n7bPFsSndq4Ytdqr4XPed9xzhHpNfiDyBvGE133doy1CbNLpmg5Fh6IxdytDPOcmkLDZXZuxE5FZ1xFiqyP2Q4HO+cd5DvI6OU746nJiSe4c8Y7Ni+Lp/s9TRphA12eGWUGwJtcN38AnUe0EdvYT49jjBwcr/0l90NxQ9tk7+02n4lZj3V7zjicmfsI6HcdJ5fGqQHrkM7IjAugIMYOVf1NaVk979Wxjp8eWtNl7t84skhgwe1gwWBIMSMyrXe+E6+WywcTg52d5nY+Y8VLivScHOEEmsIOcI/NIjto+8oDgYdlXd/1E5rY5AKdaEjbhbt/f5JBfcYR0voOta8QPMvvFWuDzZ8RH8J1TVp2lq+ZkVgxKeITA+KETJEd6MpBnbCBtlN6PmMUmStiUqwuzCTHOUIjeUlnwLxfdDo0TrYPZ4RxqmAR8bavPA4QDnrporXDTdQvTKIAeF89spGbOD5kBPfg5zTKpu8Dbu71OJ7XzybLfvvx/pEFhvPA/vL2tHJZKD8RZ1ClCxt8b8b5yG0T0vDELYwTOYc9kZpCl9SI2Z8aJyA5o1hWiV9MhiMz3/1WGXWOg9V68xXArSm/+8QYdHlCNKAlxja0UygKfpLzGIhQLPZJ0ehNfPYmU0s2DLm6dnGQDkYvncI2B6L0WB/u9c54gBknkJc7zM7+MGIpbXLOofAuvuPaa34MZmEnPk8FniCVC6WInSVHRVbZeIyk9zyjSTY38BYzgiTaiAiSpaU44NHe5Qz21EmAXRBFvZ8i1wWVWKMlysMMk8JJYsUuu1knYqYOmkSkN5wykRSMB5Qfp1Gyw87pHm1WKdaI/v+OCyqbkztZ2p3WcQfutGqu9X6mmHw5u+ar5aHDZ8oP7MdxPzwUiinur50PtjCAjzNOUHIuSGR9q7ESbgKxYctD6mHnB+nDg1UNibKbp26nyfAJvBGJURrjy/aJyNIYNR8ewE4B56k2smQ7gOpxj+4tmp9ZT+yQE7rjC3GC1sgxON6Z8OeKqEFiEZ0899nBIEB1EBQtvbbIOu5wsMnf1gS1AedG2ZEl/ib4uO3dI0QNhkzWKQsAPtxvL79JIZ0AAvA/I8kg056Mo70OIuVr3NEDOpJxxNVj+7Y/9XVtjOlNPWU/eiM49nYCwihHw9P+HT0AoVBsZe/DekaCkP2cUG0accvrNGL73rHzQxNGStu/RsaKkM3lh4wKU6K2P6U9ZPy2YrnG64u+wU7gKpvZ6Tpl4XpmlyiMd5bFCyWLO7h/70FCQ02UOPMUBY2yk5m9gHOQjnq6lNh/Me2vR3b3ScdvSgpit+ywG51oEDyjPqmPNSBQ9q1EwUIJITSW9xNSRCo/NPbW4oRqfF+T6OwA+NR+e/3Vx76juKhRoRB6D777/nE/GnzUrOwtxXPhQHJKUkPhj8XIn/MrHUYJ9ZNsM7emt0MZd0RGRBaMTWeNSwFaBVjHsdPTfsx4USegYzePZxH9Zd4kmTDFO86Sk10h3mF2WsZsj7Rmj1LpHI7o4uXIrONXcFQQCrSDSz6OQ8AU731/+iUDvYP5Hdszkn6yGE7Kyllp+UrsRY/FzIScDc7BMr33LyVDTcr2XSntjIpSrN9dVDA1BHasRMqx7md/YsZWSonSuFFtC6VSiaBOobegNfVIwjAjp9RZirIWldLq0kGk8Auvizn/ZAGa3qQOIY/UwHvGuQmkJyda51SgO1Ng0VuUkqyqCFLd9/ogU8q3rxLl6UZ7z2KKZN0REk5r93D0n/4q0JToQed9OfURDSdn780JEGmR4pa9TvOD8GMTYx+/gb5NgQo+XYEQL5fCI/jQmfZSUYpij3LiN3ZFXV/uElF0T+MAKUSiRuxeUaz5qXExsjRH0+Hr7Ssrj+hoWNOf3GNGjIjOSH/A8SeY9WN+TB9AzFZiltWpGL/DdT+huoXo3flWYNoT1ErGXl/zFc+M4ioyAM7ppdMCvjs1Ec+90SyJ948F196zCEnR3EVMZzQHKAZevpMBBOOwnOUkpqbAaeDORxQwPD7PMUuIwKTweGSn3H3963FmgsFO++KV+KJKYOnPeY9Xhbb3jB41lDH2mkmnzwTBjpTWu6LCBBWQupFjFHjAnvNpmFBDCIoAO5jFVTR22uq7yYkwXYSanu4snk4cy9z0YLFTWQJBJoIc+VaTFqazhHMENcknoIaf2Ms5uF/WQKrS3YnBB19U7VwNiBzne0+jbRw1tyfbJRy7x3qKnh8yKioePofDpEw9zvMWBwjz3YDFP9kL+u4QKdnnN49MVNlB+ZslKpgR+i77lOGloAdDDfETgClHi/plRnaAKhajzqdP05hSVli591OH0FYvI4e4Z3oIPbhyxMlHADJk1t4ZQZoxHM49ph7hFR6ZzUxHM49CUycYwBfilIwlzv5xXDBm1J3Q+2Vu00q8yxwue+09fdCWJ/jzFGIg45Boc1YDYVDEiM9IhMgyYbO67kT8BfbS2OKJhITz03hlH0M5esCjhvjz/qJ6ZsUlUAblXlFFYwA7Twu4PJI2hC488YU2SDXc3WMyRswsxclOoGb9s3hFM5rvOH4JX+oxtCRFhgbyPfGwJFLnBDbe46LUPbLO2nI9WTc9mMbJhtprc3IKEZIlqRN2WkbogKceTYF5kEj5UMbPdg4xdEIInqA7COgAO3ef6Ec8l4o7T9E47yOrjaWYj2JvYOuesRFGU02KRvT1wPPps/CxohBFjdUBVnxq7zCseoZeNYJbQSM8En7OW+IRRYIBRbzTq4x9h4FGUNpiukC7iH5iQrQ30VPEAo76cJG/Mvr7C+QCkxO5v7/dB5MLtPYOl/c3oYxzfEZ1B3V4dP9KY92BNgwtDJ+oiz3UouyOQSEbHP2bkOGARnt3L7Q4pNhUL6fFFucHRztfcEPnSsdwJM0VzkpHD87hHYyHc2f0fA/PvlMOIlVeCGaoTR7aIhnSpafyQHQLTXEjPYW2DCB7HWls5IA4fiO3jASEKQwHdPM+M89JV7T0tQsn2+6RQcRYmGy79a7TTA/0fGqdWKdkXVfJJkeP8r/ulRc15ogE/Nm7izH2G/Git4+9OjHVOi0ysIAaZjJHpiGX6NHORwuOioswMYpsqpyx61PZ3wy76Kjv07M+7uUzjly+ORx87F08qwFPDP3Cfp8jmadalOnxvWETG3OYiNwohSjBjvEkt3o68Ponm4IP0IqmE0MOO9wRRGOcRynyetK4l9+0ok2x0mc0HusoskWSXWDasLO7O1bEA+M5D5VtRSqx7gQmmsyFA390QHfJ118DgfnWSpTYIFmjnV9Ar5/qNi/eIlMyd2/XvQvroZWUOK0g+8CgQi8kYBNzjJoaPdvQyd+ft86gmJiap5zibJGj0x19mP/Q/uOpQMqjq9eIUYhIPInWK18nnjbPmZjnFA1Kviw2uOvKj85uOkP9dTxnCEh4eghExlAWeMQrpi0uWght38D9AAtprvikIjgSpkA/0GPM42tE0W8DDKadifFCyZdAP6ytKAXZ2MjvpiKMC4iSBbzWw51vUV+f2IYMshETd0dTBZ2NFo3Jkz9T4iv26or3QlR6+uIfaVPw1zvDu0xBCZ0iks8EzFLZic2KlfaQ28/BNPmmEPZmjLdgkECd9LNLFsUu0KZAbIirBwQL0Je++it+VOu3O1M6/CYMpGP2CkprxJlogiOnZNMMzbV+jNJJWE0n5R1kCEXAH+txrslgYO1EPD6l8AOYXJeYMjG1zukb0QdgHb3WfTHtBbkT77Y/pdwvXgTDg7bLx/4oAoX98zOjpVrafiF7I0aIWTzO3iQNHBGs+z4jPQkEcP+SAnhE4W9AwIr9e4c72rMDCilA/duuhSLQ88PxwBq9fEce1eqDvv7MIskrLW9iBWBp8FSe4TN7RPXUDVzx7WixHzgBxcsqqX6jllevPp+Y1l+2D6XW3m48xSfRrZ6FLW+CFyM8Rb0LIgbQmDPn12i3xaKJBhFqNxis7juJHgxyG1IsnyZFv6PYBwW+vlYdiCL7yUQzizZixLc/f8SAFvrKJY4X9lewaXfEi1eBXYHp0v6Y0+Cjv0L/et6IKpixwAZkPirodyRBAV3LHGiu94spyDw5Gy/90XTlk9/JY31K/vBf2U/gfpTgU/2mqPR/S/F+I45Sv/jr8ZKZBQ713lbtHfNA46bNciqrcpQonrkBbuU0WtsHjDhZfhxZzPgKpm/MPNFHpwDErpoiOuHt4i9qdNoZzSFV0g/qg/3BkxGvx6YrpfTlSTnzwtK33AGaoCDpt6hIV4QiQ3v5X4VyxO2U0hRAJbhq7xVePL0yMOZFD+p16YAXzy5p+c092PQCEQyzUNjbr5ikdGJXZ3mL/gzkHqaH+0IihlOzl/D6k7VA3ICg9B06+jM1p7TXDk4MV4U6sAuknFgSk8OFgBLw0khRj7/ZOVx+3DPzF4WOIOP81h3WWI+2fw1ASqfm336BMz1EPDZTnq1IlnZ4w+/afb1Su/epctorZnaX94/YaSefa7+d8pg1kxtUcJY9/fkSGLOIaJPAh8A3ntlYJh287L+JlUTa8cHClEddia3hp2ghQqWg+17ihEJ5USOR668DVuTxb4evhIZaOV1+jJ/HedBv8sQMZed7BzA0euSlD4ojQHkoJ+/EP+JmzCdbjoA0qLPRMDV7DRbu8eEN0IuiyNYqz3wxxTh0B4koBxph7uUdA3CM0NaUSSAB95FM1ccJKT9jvP74GKbTSH2S23WYkt+uJqE2f3lISgfheY6CsDu+0/sy4jGjxztyLBR2yyKXYaTMIVJTvxkjyZTQrtqVM0vMQUbRGdQFf6qwy7Iz5oBZoohnC/WBuKGAIgfrWfaQdAxL8rNnQ4KQjOASBTWjM6WRZozzmYWf0zOIKShlDkYyPY5M2IM7tzpnBQEAA1COU8tCH6FFecwjGHiRaBCddnyvx5Ty6XZRdK6/dQcbvzTTfPqak0r2/YNl0biWin07iOVomaGHQjk0nFbcBOVIxD2hgpYga729LAwzQ2b8Oflwq2i07M2Yj5FXrgqYQlOW1SYAYPdrVsDhbT4wSRoHd0GehqBmfgtPVjI3ZYZOPz00D/ezjN8HRJY+nk+5cJMswanpiBqZDwCZZzljj0RfqIEf5Ci0bx7alqiXo0HZojbPlXI/zDTzyaL7OIpxD8SPRsEcyjxlE+WET/BYL12AYkOYAj9DGSQjrT8IxR2jVox6YuPsp9oj6UjldbiBfuL+jHPTnFM1GegxO6ftRT/tfAzikRjvsCl2Uhi6lIOUoXxCaIi+MBekeygO9potx0O2tW/UmsiKQbMFfsTRWcd3tEXsTOBLegt1qnLA34m+F9JcCL+wJIuLUi8oP3q+P7OvfSDOXdZ2kl7n8Ul5nwpmVzQJLjGH43SZuispJquIl2ietWecQyLoHcvvfA/1YSjBGG0xugrf58ketR9iBd4zEnjNhCuuz/Ii+oyQ0hm9EvwBAES7wn6yVWRAu3oOVHcFBC6SpsC+0J4G3oL1GQhT321v96c5uWK4uWvu+nCCY/i+D8DTCZmMcvOJ0GiN9DOKSAeeEgnizlDYE4y++XzHGbS4vWnbdJKOfYhFmb0e9bMYdM67x0uhksYXjRA2oPQ0TlkTMo3orO6it585dIYo3T4y7/VaHZ/VEc28HbpG/Tr+sACZMoNCYRPs5neUMwikAn1iRRKK3U/gTY5+H/X0zvnFD0UvmDRp4PUfbbw2JCKim4ACGaICsXswf23a3oPtUCFsdD7ozzgzalzpWEdDfuysKT+WXzHGjr1DKcDMFl5gvJnEoS++40lgseDjmxbx1ik/sHhW5ju81xcySonhGp1qTnFRQYydnfOpR+IvUHNisaMIm6+/U6/jxTqgQwB7q/agLtjWmXCZDLArdZLwJneVG9VSC1Q85BzXOYpaCWm3vQx4JCxOjTDbwrQ62rv5qJc8qLjw0YpksY4nQIaDVY6tTqwmIutAj+fxcKfVzbhrLIoQM+4x8YwNQbE0+mXdcQyg6KQz34vSpyApo3M680zg2MNV9xk+zhbHy4twgPBymmerraPcnyPARfEBSEHI25+DHAAVIlbKLqyCebQC1Qsli/vRbgeCdP/CGZve68hxPqlboyVnAI55/aM/vsHn2WXMMyM9iBoPM0zQ5nZlc9r6+JpOZGM+LM55PEceLNwxWpxvBCeAMvDBEbLorTU4q+exEXj/EqPT+Yij99OWvR8dW/QXBlrRwdCsoSp0WlAxCjwF7AFpUd2ufuj+PsItBLhxQhH6RVzUiBEenaeoP/rUEKRJFpAbSkyGCCwJDG+A9JHTMnV7K8mjrDG+coZeGH0Z/4cwgi5gqIQhNmf2tT8dCfbC9g0w1WE+9RwzMc55ZvYluPWQDWn5MLWArtpRrn+YCW64NT6QJVWkI4qduyGzC2tmny0HYwooJ+YHB0hDFbJGzFN6pFMZ1/MMMkfeTwvF2YoIzg50j2Z5LIbK+hYuNNGOQ7YD7dx9IbHEKFiHkiNHWwHfmUoXDO9Ne/b0pZv4FuoHY2gVq/LQRZ465tjP3OxAvvSKjBkFzpZDfHis5s/ZkSlDVU4KfrCSK7AEeZ0CgsRmZDU7EyztMR2a0f6PM4qOgsRx9wezwRtArhTHBRLqEQXgGThDwWZ8GxHYUCi/l5riGRBPR63VGlgB1oxj3lpRIZnM402fO4JwaYLaB2aI4+79LgK3iLFDjZJ+xqAPR0z/2m1UABvtKwlLO0zoZ+ZMIyeUmTPCeECeWv7O4MEO/EJH7sT+OJSpdV8j+Sestb6vmLI/xLq9fdxG+sApTueBTNOHsMx+juFF65rynuRA2FE8//TggxADpjM6atHmqu3Yx9/BX6NqXPnCPvVEMY5Bw7Z88ifk0Jc4uRgVCyBpcS6gwTu6ELzYCKaFeksxzwGqItrjkT9NdmuQVxzC5uS8pH+je3KWEcT31k6Pbzkqmfvm5uvkq6JxdPgDYLhyZl5ikk/KwqE/tdcSJMWUqQU6BByI95qgvjBPbDuzLjREMB6/a7QNaT9dvkFxLdE33sub+djRVnkKskWCTi3vaYi+Bs67vSqj9R6gzywtF8RtGHbvl3fmU1AxRWpfDxkHqEKc8Tvqvi4RM5i8Z9IMiJAkDailB5uTvbyTlNU/uEawm8o38gUPDLDJvQjq6xFJ/fKn5ECX5FgIHMIhGUwoo3YezWQAqk0xSnzIV9iPwUY4VBxgPwcylYOBrTwWAFxaL6yaCLG9BO5HOj+GwpEIAOsZHnjn5iHlHqiCfj5ysLGHGBwVRLpJFQRlo54zDBlk4PGD3NKIhEUJxj2CPv8hu5xl0GIxj5z7gyKaASGPy8KZWAbBhf3Rg+c08vkN+gHeZyI+HwG8cdDgwRjhGReE8fuFh7NTWB/OHP3Ro/126ArMiNEYm0GwZjejnkU5n3YV7Vx29ZDHgxEgk3DvqVN1IQxGu41vYrKxkD/CdUe7HVKoq3CZoo+02N2unPysfJCRb7oB9CGdsTEcePobKfjHJ8khog5AxhRtowwoFxCoPYqwdSrwHRtj8kNgC50Gd4xcRw8qrVsIL+g+Mpnf0WYd6S9aHb1kPVQVs3yQKWbBIQl18O7EXADL3Grj24MeJc2TdyqUTm7JoeE3EkYcoKnRLA/SLB+j4Qd1jaZF4IzHDO4NIjWKlb6zwWDrIclDM3WcaAAHMJ7rPejyZF208Z0BbEfE3Rz00eQ4IH+nAom0WNI79/8OytG+Yoyz2ixNITjMI4MDGzb4qGTPE0lQg/VDz4GEGugpI7GLQBQAaiw6GyOw3HuRRMuhMukl2jVGOUAUI58eUc5hCtOUOQxB4jDsPC8LJgL90Bvux1OFYP59TjAIUwUATOkWcPhZjpXt4UFzLpSC4h0DxVXCV7jtAu5VHaMIxV4xrxdMj6BzSgssiBl4//W5hN7p6yikFsiJ70Tv92Ol/ZwXCF6sCV+qUOvHKfFJdAGR6+3TMQAwAbO50VIcpNTGGOfd1SeNDYLLgdnGlBGYrjxPC5um2Hjw84yESekopIEFYjwFuXzfYT0s7vC9Arx55egshE0I2ql8mwgaByTG0FzC0+2Zh0IXv2WgegLKi62d8xnDHvQatsu+t3XATRhuoyjbeUWMMlvgVYTLAAMFCqs9d9vJJygf5pNeYfWbWWRk1FQ9Kw+TjMYiuJwZOAKWfZH2nosvNBKBaVBIDcQErRwYzDNhQsWwt2qpnwFNij0To3gysgXRiGK+3J+wBZUTwu6nlvIEyRVQK+YDhVyUaOe0cX5Adtm+23YyhnCXf7JEDHqp8nsyZ3rv5r0YgrIe6AHyDlrl0gXZgenYXsKRSpFCmoeUisBawSKqxkMupGLjjM1rPp51iO1QEoi+LTEluPB8KlSqcZOgn+4jWoGWRH+TcRxLQHzhxliPrZBke6b2sCug+mXBuDoKxRYaPSepxFybaR0q/PaqwEA6fIfyfhYQJr0AJezT/52xttD95msae+XP9hESjuzJe9SRcnN+IUIfsrpT5IVqXQ+TjmfowlLs/moXgthvCnCu9ZjBAbgxd3StrzEdOPOA8eZXgg0FfYUeA98Bmpj5m/ZgfP905NsZP5MksQ/UeCelx5D7/Y3Q2nx7Y0ANRbZ6oDGo1DGGAOwxTuQRIr3ltAZhakrLrgfIRfmTmqpwtkOdk0E3sjxCuM8Yrh3VjiIgns5qkEfN/cgYU2zmTZ4qwcP562FSkmwS2rjug6y4AMJb6cDlIMCW8gfxoJ4T9dHa3taH1gt47dd2OP1v7JQWQRHnUT38D6YbHGNRdKCm0MHrRwX3SVCBJKETUsAWURgtNOZWizbW0XY6v94IHD9dmva42UB5dEeVfIyvOCt7Dx64ahSRWsD8vOUP/YI+f1g1xxw/EctO1fNn9lYoJMdXuUoM5TkSmkDdRFMUOwYJz65GDjwgBc/pO7vwGkNqbh4CET2dAU0pkfGjiNt55qLIzOsWmfPBgfYzhs/3kSCZZ/NkFKk74z6viT3H9M3jeOgDJgX9kHlUhlYk7Axo6F/Hq4+OFRLxRseKxnS2sQo7hVzM2xFJOnshccqyGD+fUR4NwFTuD9RYw80EU7R5aFn7U3En++Pn46sdgLbDY+pEn8eROPojTEltoPFQ9WoYeAsCnc5KAFyXPs4YDQLAHP9EJh3v8wzaYhVWFkWLJN/8UsSoTzZmVA4gxiVcTceY/9m6yI72AR0w15s+SdJmpIntKFJrcqyS1oe0AI4hBINOeGxkaEbg53amXmf6dhWV/lPg3FvAELjW1rdiw3/sUMzjMGGrLSBbbPYgIQM7fC/UqFDG8cW6Tw5H06e7flw77LXA7B3UF0ucIPrdKURl7iPuDsJUfvA4NFnqSCne9iWKtLbumh9l9hRpbPSI2WkvMv2f0YnC4HOdVnSqx9D0gVySpxrHyPkrBLkQZGo5VgLkiXJdVUCTeB/9pFBHneQ64Jl5BNhIGBXhisJWaYakx4qV2lgiZsFWJ4pWza93ls4cOQtuFpDHG3qS51yLWXPvU+IjWvTxRwcJvN9zDCpPPMNRWIdUwS0ayO/qxto+w7k4CKmvj05sPr3DFLoSb/OJTGwotAL9yzcfAeFjfFNnMQvkGx0/FEStHiQmjrV6KgC2FdiyjAX4dofR5e/3o6QDMar6sfQyGXIE348ceSfkT8CcqnmNfCRPmRQ+uUY/mjBv+o++I2uzR1vqntHL2clpG682BSBFe/WfrUDcWRy5UTa3FdgKRPQYxrHN/QFH1uphPD7rOhlxfwqPVg+trPfQfAEkM5rF7TGDeIiIpIXsa8Zs7TQT6fxSv35WOOIcpZB0GgPUC+3IUAnPRMBfHwY0J+palI82HAK0JRDJMROH/GhCCr+fbV1PDA+IWm3p9dI8/SZGgEJEjeBncL739MEvAX/LcHXdh2NsL2AE6eT6JK4EgobnxRyv8VA5Jds8bWhM4scscZRWhiakAXtfvtOLdPh0DxyTTizo0UTrEMR+QIE7+NbsOQVRuqQzK6bG0jhIwfWc0GS672XzmmbTNmU/6Zgu5sIj4MkJM1zEZsoK5hrhub6X0sFHASUwgyQyXydRimsdQTBq0ZXDGMuPfRbSxnFos5h5ol1QnlKQpqZBAej8EPREe/sEBZCboscLYmfs+jPeKXmdARgawmDHlEM+x0MuH3KNrxL7KR/VJmpDIS6Mg42aXPOfihO1UebHaWJaFTJXJ5clZQ+Qv4I9HuUGzuaEDsZBbGPsf8QMY6vdgS1vbeV6DCnrqMK1L+g+fRT4BH9bJD37sIu5OAg3UDT5lCQWVTYBI8yPtTDGSphQ71XXHuPgHBcf6W6IxYBQtB4pO7SZBQ/YG8dFY0TEJyJ0nSx7Pk6CK4LiQS7iNBD+QmpHrn4+ZEM87/zl9nSJBOQ7l3KM59DS7DHEpfcDMeKfnhW2GsVr46BHOZHo63qoRZxu4FSC4dCZJbDp0oP/yNE4JwmtBXSDzHmkAS1m7lRFRLuyPKkdG/1g0qxxRiI0FL4FGsreVTocoFeumcPjOlrM6CqlhsDoHTXUilPoSLyfQnl/kGk6hsQs4ka0o58TlBoqbD7sBOzgY7mQ56eWF6Jf9QTZ8ghfQx4IDKR5DKx7ZEfjnInIUTCYnlHshMJDPqjaUCRah7LaTncCAHcia1qMoYknCEfPs5qpXkDTRCizxkyEzXuQeA7gEFuZHdd+hAgoOFJkyA4btjDdfShZTHMIfAm0OjyE661qpWsGVmQXdw//MIcZ48jlqEdwPASAfgneKtZyKR81EgEYY3pIuHCbleN880x8oDhEHUIIKL0sFrZbQEZ+CjKOD8bOQO8j1Xh4zMHqDT29qPrqsVVGGGGfJgeaBDs3BekuUqs1WPFyhx6dL5KUxkdePV0FILxi+lzYdiCzN4Jsp+kH6vMQIk0hHYCxw76h/JzXi8/hUXsqVOR/czyMR8YRRGIOA32hQ8EK6sSC3gxcBV8hPEwY5lhBHccAGlDH/YwO9hCjiQ78duQzx3Fs/0E+OhuPa/aDnUVP9GnPR1Ohk+YH9FTwsziMgVN6qwGvJIE71UNJ/jooqBvaPiPLg6+M0nGVHoNJdMYmzsiQmUQLJi0V8JhMWLv07Im5Rhel3Yd/cgePYp9+7ESMFYTDUaI9O1Cm1VuY7lROOPPxKCmiHw+h3HJwNndYKD5tK4zDKR82jqobjswjrnYm9z3gDNJfoxRa9KJxU0y8Vwlly0KVkag+2mkYseVJNk2K/BVw3fJGazoNB2pnjJf3x3ZtD0E79LzyBzCqQbb/ThBqg0Yzsp8FmKlmjDkp9LYjBy6BCN0POAYnmRoQ8+v2ZPpgIEY8BABAuFBv7c1w4IqU+xwfKJk0uh3RPgo66YSc3e+IcciwxGZgVLKjPN8mZ03ljZqUMeBIN42HvzKDSTLj/QcJhuYGKXCjxJ7mwC2fgIfjPnJrpDhsJgFWBOjVEdTKdG0FtG3fQHnYRPR6SkfohpN6FPSQks4PEWgSEpHP8Un20C1CHwBvpdr0DIahTBeVtByWRAIpxuEHdn0F+ppBjw7iCWnyQdOgCUPtuBrCuFHjHwmJ/NhSJ+AmoZd4mngzeISvFGWY9H7qjqGLTQ3FydMcsE1qyvSA8WBaRJ3z3oPXAvBtmZ+k7+AU8yuYOeNuomwJKMK++3VIeYy7qKBHYO6RAKHA2tlbEFpCha59nSGgdRMZADVeA70e2unJz+MA2QYW54FPwkAyIS7s7D94QIDGQ3l5v4IHsEDpPsFVAdkTE4qoIRL9mEDs33FmHX+7EbvkHOhMjvqXfNLAhaTgdw90eiyMokQENq4/eRV68d0feADid6l+Q/jgqEXlceYYiVrM5xHk064+6n68YfSUiI3a6yRiL07WwRT3qWYwX0F9OaMd29mf+/CMlDXjzKblMz1Nlw2tKEqKo2WuUOAcQXFilyXie8N8NfDkodoGtDIZWCGFh1w8lwBkhBg7SfsZLyogN4QKr/LRIVDHHVRvtGgAa8WpsN9gdIcCFzpBwi35mb4Co7GfRctn/ByOLOccAhmcohQdXC8u83qmguUQOyCKOqlT2er9+tqjodzX07BkjSComMybn2/+jmZrEbngqKpq/aRvF62kqFS9jjfBCETVDofRbODuuQOYFjkE1TLQTCk5irVCPN+hlKyDtUc/eteZH7wnsC4nFyNK/qw6gkfoN0RX33bqfZT2B996eqIByv6ohQSVUZ6qPbxe5NanWcZbpkdu9HlbQIpvdklq1TY+VYpYBUcqiRBaFLFL2Zn1cSfJBo5C5SVB9YMOxq9ET5P0fRj91iOZiJ1KX4R6jvFF6JkQaBMVu1BjtJDNCZSBcMh3uKS8uLAHEASx1RoLXzBB2QveycXpCuCXbyH0sFM0DzwvPUQ4PuC9n1dcfT2242dyxib7XT5xzZSoCYlmyi5yyrEAonrNpzxUHxF7YJe4FWZovj6xhadgSyJ4Mq51JiTBgSrhg/wOt2G5RiPuU9UwjtQXUzLbdVgPYfaEFsnpVkeEpKQ6DqURMC9abJ1Bb5TwiboV4ACt/0fVl+NK1hxXb6VAW0bOg9ZCQI5k0JEIiDQEQXtXniFvRhv/wP6636u6N4eIE2fQOKXRKODR8gcRyFYCQkzvSzG/zLVVDM14ygYIKeF5UbfdEMnDTO9KZTGNhDnQQ/nhgSvgclxTmEdn/sG7yYsS6nRBSbqPP/jWNo3W1fQbigPKMsFKm/YsIC+x9DAzBQmjGdTdz7oDf5pEbCEnhcLtaeQdMEGlfw9vM0z4mVPT7OUz6NYO8oisTVCCkJffYUvOQaz+9ps0dpJDxpNbkxGNZg2HZPEMkErfbEoW061Hf/UdNwu949KoSh34lTuL1HfjSNme1OvaJWeY//Q7TpJbzgarw3+Aq48Ot8taqSRtUW0COkDm3W7xff8Db6avpci9TKxkiKPfPWn5DJC3jA3UqjA0RbgQaOZg1xjCwM7ADZrtsCV2RYWGIlsvxwrMJktCIjf9J0O3vmkFpy2oIoIeWnQ1LNMSOcp40FqJnMueP+cwBqaXSVkhMoJ+78gflvk3jbDNk9YZyoiS9pwvQWPsM+Ai0B5x2JGUK5AHTVjRgCU9BI5pOIIeWTqozGAAfN5uKJzwxBsLc25ewoGBvkiw4LxPBP8kPRoCQ11xEQcNG0OzO/mg16Tu9HuAjNKV/i8nAX1sGAyQXby2L4653HyZZIZUNrQq6gWYHSkHWTe9TFKY2lAU26zj15pmrd6+SmrK8ieo4+hTVEInB6EbHE+QcjHvyVKDj6FY/pMOoDI3YTBKfqPCzN87Bfd5IQ3R0HpX+zWE3q0gWd505jq/exGkHLZf/GoaHJp5RY0oJ8ZgeU+btYHpVJ41HQWHTe7dXlgtczfCSMalBeOUavj++DU40c7NYBNGxlyA0Sdh7SC0orNFHA3MDXR0nLOkXMIw5uPFhhAUEY/8UGrwKkckdA8Gf1fK3cx4Y2UxH6OVTJ18nT2Mn2FE9MBwyLZsveh4HOSckLH1DNqQmtgeBEFWMQYBtWx7B3EeuL/auJMPsIMIg6U2k6uGO9QE4UYJRqyrOM3IxgSkmoFOPkCVV/2M7hqy+6kcgULO7011oQJDGxQiX4oJ0EwHHjYD61Bv9lQ95+kkbxAV5n2DxZq0fEXyB35EMcAds2VNazvwXo0L9o9JOLb/J0MMnR1s5ctnfkH/0+YBqmhR8yusiANAhdSLZicFZ2Q24tBdf+JoGshsFAca/lY1PcyuklH9rjAOCFc4Nehv9eb+bP+XtFT7AqVojXqV/dmgSS2nPHaRJvlRfBgVhB7HcS227sYgO3ojmyBLL0tY5Cz7RMFjSA09eWYMqrXoY35cNXwyyJv7BUqq9yrrBEJO63nNU+5dUgl2l2fjIlulZd9p6KzoSnCLV+VlBfdYppQyouOWPUvFK6Tl8ipmwgz2e13Z3WUH0foNv4FvlPGCBqgFJOAErxAOvxmEBZJDf0FQzEmc4hqAK8VroO/1qX54bQ6TlzchFsiAYK11mxFq0D57Nhp2bZhWTKfDYSiLBAcnCzAB1crLe3YxXAZxAq0oR+X8zqCxBT82WjWjNWMVXjQJEtcTEEVZ2zOK88XKG5xmR8owNVFz65zk91WT6f/o5kd6EmQe9KDf16wSgPCPBQLG8JrjtbJBD/BJs6vkZkco/JQc3EE4kyhhNMxpZZ5RTJjoEfT4vkoMhECqZlPMmOQ00/PKK8hrJyz6HYnnGyz7k11JUkEDAe8AF3aN9sd9KuiHdnv2Q7GLkJP8rpcLfdQppE+lftiJQkHyMp9VbK5z0azyJbqi9B1NsXOVyTmYCQ6pt0kzxkyoa3qwOJbcPHu49ehaYi6aSo1GMDTHST6tib2P5P8CZCAYSZJXO58DDuBTOhqf49yZPjRG0J3HafBk6WR1FT8qjiPmu51/lC96ahc78zeEMPx6NkdnctqDm/VUS+06eCVjjaInzy2KVz/PQU+amcYBVYdTHJbTqa1Sv9kyjKAZgI1vnB8zuqE54j2KuiiEODSZyS4QM+XhyamDiovsG81h9DEyLAWXUnoNr/XqwAxgvvr6Ht9jZJrj2Wf+k0xd1reQEuW9I3DaJxWjvQee/6DI6WF7tA9FoT2uPyqYvWGaURKn1ZrFEKqpEjyvV4LCQRbbAtlvdg7rvzyD9UVNvuT1dWi2GkSlxMqzQwrMEFnqZTDdUZZH0TwWjeV+9If6LEkXdWhYWVURBYPR2IGwyBgL6HTmx0hXIXA+f9EbRzLuH7lcffgEwoxD3w4vZ74knFJYSFBVf63gts5T7/pN4z/COkrcYXtAaTsskbsNfwhOtfMHjm5hThlY2ftjBhGg7LnbSgnNnheSMLLUlCMI7IY7dtLU4YsxoHzCAAs/CaSek97X7Q4QlE7qDhkz8a5XJbsq7m0Qx5osKDmpC0f4rM69umbTQJEwJJu2sJVehbfx7h4z0mDluZFTMzGtcsoOT0atUc6qrzfQNmM2c24sS8MWdbqoCmWnwIOV3hNFKXKDUazuLtSkyn7lWScutk71G2FQoLRfuhaFn+RvOttxU1q0nhvLbIZHz0PVhoJ/8xhPsYXR/jCQNm7YFgYR/SsJaflgNzf7/Cxx0DsIJgaLanAMyCzOyfge+455qrXKFjkVMpp1fbV9p7X+vsWNELQU1pZowWDmimc0NbJh147ZdrHBf8aOwZs4jdMs17KmJB3z3v9AopHqq7Uu40BcCrOYipN5qOAmGVcaOTWDOeumqtvAOAzQX/EtPwkxgB69nDUAWkRfbwqa2cWl9BRF8MG0jGt9/BF7dFsRvZkD0b/Kj+8LgH9TZhDa4mr2/4eG0aqib/e9xNl1GZm8xhBFNGlm4i8m7VI5nwWhDdr5taf3T0BCA+ZMj5j0LSPiwN7bTmhJdhwyAp1RJea41LCRFXN9j27A1vx7nxvbHDb5ucUUSJBwnjgLq7oSBmvOmWOfEFYwY7rEu20jmEcTAYPxOybIHCelI23d1+TF0B9yWcWD/gF8+G4zUJr+FAXz6BrBusyJTqft8aigSuvTpxFO3qLsTdW6UFNmG4tvPzfGwr5dn3lIzEcoZeQCaonSb43GsgarYCjjkYY6xd2Pu1Ri3Z1Ji/sKxuAgBJHh5XhQ4to0v8BfoL3/qDbEJ4nrvIy1t6h00AqM1CJjmN7LYU6S6coyHtFLfgs7zITBoLKkqrfPRFaF7Er95kHUEmTytKijsdH5PhwvQXWQYqwg89w3ZIe2O2UaxtzP+oKj5lTezQj4foTRWKbTQ8o54DmkiVK8KaobSg9ymVZtn51tZfuf5a1MJ+31jONoyyI/ny9+DNftChzq8/XQZ4Je3SzeYNdzC5CCYyTLvdcVV2MYPYBha1FxZSsX7zJQgUYxxvXTOPNRsy69HrekvuLMvJE/DBIqgbYO4w4qPEeR98OUERr0J0X9GOht0zayhlOZTRPk64A3aLdb7uyEEu4czikmRvu56FBBPKXElK04rFl+N+87VhqHct2qZnQY5lukVknStUh4OKOZtUh1iGYKIuYzi0cbyA9XkGQocRx12g+6rVQW7eDugNt3ZRKufWgCfkhk/YgFOcVAD14VtG9EilXfV7QNvu7TmCcZz1zbH9LBdGRO+0vla1J/06kpeuwjgDTnet67hmQ3NNT1wXww6He6lWCcgWWUSRuVvw/QCu38YeMZzqEDN3UpBGUjV0B3G/7EHqaCaJCv8IZp+PnFSc+u/kCYVeesA6fyWCaabBcwuhwwizArHYImFJTZjeZxwFI+yJP+Qz9Pf6vPNQK3leawTrGBxXyMZu7E/Uya5jSLsVYYsZarc05bgcdfbeWqg1Gz+aWCwymleqJNTyrsn3OOfWmv6InON+aMGCMEpN3CaZM8A6p4+1t2JHOw0bUrHNY+LoNT8b6E40tWN4UTSxXDqylX6sKgKHAg+1dp4UYEdcF+LwNCupc5IUgaxf2NQgWnAuwZGC2pm9GPPCe0B/70tLCURQ+Vskwrodsz48A26+bnEcPd793BF3eFYwTnEN5k6vXj6GabldqYCDkn3mP6bvI97q+q4DwZjXWR7S9sWIlH9KEykracbT52NoaB2Yw1G9FQccuAZAnusGXQy+7rhYabPQzy2XkUTu+WqS30O32KFoWlrsfp7Yw9h0gl2UOqMDrpqWJAoVbQ9imAxbpktAnedXdgEQf9OcjCPle7bQnBeWKzl0AzASpYA8kMNQnPh7TkAQ7iPob9p08ztCyJb2ATAGrMweu/JuW6wKTS7Lz1M0ncWBqJXirULGGHboM11dYYujsz/Py/y8Ne2J9CHeCJchGqkoXfc+ZMakdzSI/UU4wPkvC/yGALuv1847wYIFQo4tPrZ0bxY2pxts3rLA9Hc0kYxREvlzIspdh1n4Z3f14Z0Jyfstd0kA4nwUYbt2lJdt65BJfSRZfsnu1RgEfemKmtwAlaEcNnbLpv4cZmosha3xVKkfrrKMiJpVuZkEbUrZSU+HBk7PeqQfzBkHX06mcdunLvNly4JQxuDLohfGcsniExouqSGk9jr2fBB+0iubUfNYmq7RY5njzbMfz3sDvTHATl1nYyFihFipFVx9uY+/ckdiCnWHmg85WOhOkhZHTfrcFzjWdSJhHdHSTQo/ZuPyqpGNR0usDxeYTl0p/bMeuSkkNoHCMNgRJ+xNImmdeKOU6VqVSfJQuRp+I0qHQHrNq9AtrY8wMmncvER3R3WbqPj91XTKq4moRqB4J7N4MKk1OoqzCxAwfKblDKip5vekLvSMy+m+86FO3lZglUgzmkpfTzjXQyI08Yzg/ZpELQtEYN0RjE9Hnjydxrc/AJuAqOVdfDgursr1XFEZHbo2l2gWgz2DqwdutBbEa/wlGfCkhqZNwl3aZaSn7T5PYK0jm6ehg1VVGZ1hXn8eYvvessqG0Il7mkhX2k6ZnylyvPR5oCy2JCg6ov+Hdjy1ZJqunakBiM7EiUTQOhr/ScWIn4wmkpqPfnIa7QPdxSiwCoM9lzlpHsZ0HKsdZ8D4j1Ly6sXm1YW+xdWLegKYAHqO+buFX8j+zzdlanjtkbKzoYFbG43VIr1XPZf2uqIDqwe/CHVzTnS9YrIGYzHfeWIYvynBqMZdk1RQFIoetaekamhWR9DG3Ov1EDXVmpv1q0MgrrySvpWYafUWZ3lZVAn36U2dHNuLv/BKc7aUpFmxtjlplqzArC3DyY3Q1KoMAo2D6raQqERyAyHbAfHjXn+pdhCSceQGqWDYqwGVYwDqEdDRBVWItwyIe7MH2mH+oWRhzxwmelR3f0pP33LL74fE9F/KpB0FHs1yMrLUyd+/csGCrA8DAF5RFJGJalzcvng6RkNOWZ0OSdCvhzruvxgI5tC28V+jwpeOQuLw7UV6Ybf7ZJJTFwxUmLEPDLTN3MOBS5Z2HDaUI8kc3WLz/WB8dyIUgNrGgCu9vyCToB4k/rrk6KIpRL3zuPVJxYeBZPs7XKr6wHMbMIdqKbFiTKGlay2wF1sNHxqMTuZHhx9iiVJIz6qNGDLI954nhGp7KQL8WUG2iWfT5m/5sGLMsJESjSUsgahKpi9RdkcI5D1A8l0A1xxC0mxgoNnjjuUE90jQpgCKFg7ekfMbrSXzHXUtUCi6hdQq3QaK52fm4p6XM9b+Mp/dF67/5yw4sscTjl1e+h82d2jraZpTj4Z6B1EY0rLZjvUoe2mUapxcrBHR5bH49gjGbynIR8pol6uGdcIvt96rXtKybbpW9KR8MzTFTr3nY8cmjU9fqk/nalmLW25UaDtLnuOOsegmzx8kUC9ZC56PyFDMRqaeCbI1I3EMJif8p1CUIMx20WwqEWIyUMlYn4+kUhADAaGI6Js5+wxUXnCpecY7lxbubhAqbh7UP+Mk4hKWGJkyo4fRt5XLJPPZ3kJQPRTOI9Ygww2aNVR48v8oNgOX4qYrMNyR95HAEoJRiuh8HgNz5pNEH0Vp7kLAorsmge933iTVBNkzsvb3KHOIODgx0Ep55S3iwBln7B8Gs6nzR3CfCwDavdYTS1qMpyhuRMKICCmR7fQyNJYI3T5tMDnc6rtzfDzd5clyZj5M5bf8QA9DQipIFJvk2yy+Wwo92q244iEAqVFgZKw958TRoH2pJT3noelEJ4Jj2MMaBYupGpwY1xnDynq/M6jX9Ke/8idOlmOimnuzqtH8MKqiitVRT481Pa9Z1iasC51myqvbdznS/HQvWoHVTKl6tI3lUtzi5eP3vlOvVOWwR4Y1OQNa1j9xOf0Aqp7md4hvRgzNiKE8OlPW2PZE47HI/TdaLQC28/jwXUHq8UmebiXqcz0hZ1V5hvxzih9o45+kjh8DsbyarvRMzxQZPct5j4gKrtaAQeaymgM2gbx/5D9/ijrdyrVOnhYqMEMeSVTDuKrylWX5dl+O2GZXI6G4fNEEBYhN1wXlaKuAGnYFCIjdsIEdIABXsK9ofU7GP4slUHgi22dg8hwwgr2Y9XDFkWyuBU5ODEdFyijUk0P9Ri0e4rM6oRRU6VNa2wqpkjPYxMvx08StAh7bf26U5OG5ZRl1Vo+K0ofKdiR4HXjPn606xCqj2eC8hOK78OkIEwReHousXBaGCV+z10COo41II9ufnZ5sem6qAR+p9NZm50ewaTLDgL15n0uMjxWjq0lKXewmyE5p/QXQzTQsgYBgGpKhlssBYvj/gJLJ/VVLnjEzoTG6xWhaahEz7V+podoitDLSETFl/7xFBr0Uy2ZJXMXyO4N+xWQEvO17dJENceNQOI4tQzl8ktbU9miI5bypqokOmI3cLp6f4+Bs35ZiDNMJQmlRqn5FgMTC5PN4wDtxbYsZ5vsO8qUUlLwQ0cpJzHl3G24v6YHr7gGYOwkLenn+cKWyPoNEA3bLVE5x/2GN+ZBrcZXU9yct+jWA04NHDkPD3fJ6gfiionRDcVYszdiffl5WUjPn4KiOgMwsAMz+cL69XpENbpQAk0POc1qWnCBJYg+ho2Uu96fMArXfiQ2AeMvdiREp0HSCCzGzRi+jyn5l3ZpbSBZHrrK8FqE/cRpu7ChaT9OffoR0DeK8LM001RSSbEpKJe/wNRMLq1Hce24RP+yioht50KTz+D9kQEq4QnuU2p7KfvI3csIQdghGKYNC9Av6t5e2c5lZ73JZE2geIcwhWI4bHluiZ1DFYFdNzz/HgdHOS0U1qQEApAswWW1yLZlQFs/ZKhSVg670dbhzIsXXe2xVpDUcP3+8EUAEPMIBHAULLgJVc5pmIyOBV/yJ8qm3ucNLb9z5hs8iV2h9qyw3x4NASsogadLWg/ZDoCA7bucjVj5BOJ3FcGk+TtBEJgvX545HM+xgYDcb9eGW0chTSq0gAbbMZm2X8Ddd1+YvzBwUNZwRCeZBu1rCpbGBUII8Wi9B1wi+mL87kSoygDonUK/W0DM3i8viDetAWafjHd2XYF99eClMX88lP3q8sF+oVMiIGr/eKsECL1brUEJ1dwDkmCgCAhHeMBCU0x1iP256QWberrnQEir/DPoIRBc6J+J4UpooqzaMrRN4mcsc/oEMMwJyP26xui2tDEb8xCGTx/to9vHVw4vnQ07mFO/SOXMgMFINE2VF9JBdbe9hVL7g8+WC/7JpZmeyQFEhT9jlK1GVWjsUgLKTtkjhl/8TD9d7O9x/XDBsh7aha/bgSHdmphhpPbSFeBysk+3lnB7Ujo7Hd+AyDgLENtF1StAAambLtpdNY97rQXQaFHFMhmhiia0oFXrU4z4MCsRComHuP55et883rjtoooF9rrVGaBM33+y7pkAhr0Te194P+5h3qX9UN9OBAuqvmcWKhGZcsG8YPjODQhdzwHLCF7jzNEptYbDrYpKKU2YS5Joc96ebSkZueINbHJ2w9Iww1K0cENbV9E2s5BXW4+FecsOWbb/WjZdGEx+CzLt3gWJ4ltCJiCABfYsg1N2p06FveWlkfysptvNK9ggBTCeRn33cYbZ5FlRgPdpiMGNT4+2SkO5zdT51ixntvrPuXskfksl0XHTXSWn6o9VNjLhEY1HXTU7pw7axRJynZwvq4kXsA+xLkUhJAz3KAg41Upi84OnMxp6ROdGTND4VVWFhm3V4AG5s/wKHcgp3w78fDR256y0pFRhHQR3eWZ5qKaq9XQeGAghaBArwIZj0NRtLatDjErQ9mQbGjA0DZcO3rU6zfHwyNh3Jgjzc5BX18VaZFKKFRsMB4kd43+JDtQK8lNbWYYfSG1QwfcLpc4mXsIipEZ9vPaBGbJJPaerbmmuizZh98lBK2FwxuGRYQVgnt/MtkQMEy6NsCe7rkRCb0IphCkXWkAgaOqyARl0iuWlI7ueAhUFABHTvcnPJ8JtPuPvMsfpH85W2Kyp5bZ2Yuy7gBF0K2/uclgPxj3FcETWihsAuOvKHiVp+6mFJwRlMqlDwtxaVgIZHfYfBhaZnZ6mkvR0/eBZ8g6yvda3peXeFOylR+BpAhwCpZvi/MHcJ2+bKBCo/iAHGFvMDexyDulgGDrUZF6DlyVXQ26hljYg6h6YPOqT81YIhTUomqRHtb+4BwxUpUB44WbB/TSPl7ILDXGTOT++loZfpHpInAeVjyW0vSbXMsxJcZ7+dZfxUNVzZ1ZSq7Y52IEEJSiWUnwjTxU504RTAwl22K2z8O4+YzA5T/HgZloePf7rWK4SK9ZA1DUmYPZQ+ysgpfeRuXGV4Hg6E+s7K3ZtNBVflbnA1lgSybz86FsXZKQtvPzDqZ0/Xxogd44tiE9UPABkNLlBHMT5mw6/jm4YqTKrOJtgkhiZiEyHPHa9GWGOtXn1U3QgQx1mdlkhk/iZj8NZ7LsPtdX/tF6gTawZ/2QAYN5Ij0IhoaILSvENoj9Gf8akhGwpkopwT4Cp+dsNTptd4rV4X7kYAf6guWQ4o4qk34k3eI4etYCDhvXI4305f0cb+gjtgmZtms5gULD2q/0JapQK1TuhJvM6g79TLP2E0dPS4zB+gLFQcY7Jeb6gvEozy7a9BCl3gw4yWlxeGFQM2xrxYExT9ahnYJxcl6hOpEdLJ5bklGMpj7zsfrJ51jM2L7RhRjEQiFMph1ZBFXWUlJL2tT3kajosVAw8RVjePDWRbdiviMvQ6Aea4lFD9D6VGk0MLjYjG3xVtXxsyhUpwGGvdUnBWg15rExOzVq5M/W2tTAJ3PzEMmZSWm5ZhX9erH4aG2cLecaKMRtiK33uBZrSaD0adAWfd/QI1pL0xleotBZ/5jCygjO99OCEsBgddTI86eo/21T4tfkQ3RLORZ/7vyo1RTO2sZJ9TeN62tTCLMx76XgJGQlzMu54RwNnKNxnfxQhZ+6xr+aYRNqrlm3seKqNQhjmRkIqzKIdvvNoi0qO7mBsAMx4a6Wm+6ly+FLmqfCDwPsuSVOhLMWL5LWBbninkMlWJvHioCs9+OWF0YcrWDml2SwHaw1wYxn+MGUSweWJAhVp3/mBUpP6IQbpcosLbNRTNzB9h4o9Ne9V860icmpWDWIwWbemNJ3UVTonkFr2/NzhgAo1OSTxuz8GRiB9fk8KNmR5ltMqOydki5+SqbF4T861/MKNTTtnUy2uZuFD3solveyODpJad8Sp+CiU1jZnrcdP28d128ciD54e0h51dchrxH39FBGNfU2oeEuVNWbPGtVA29uEBlkQpVIuBnjm0igs6kM7FnaJIkU+PZU0uSo8UYFo0gH+7JZzqVcMrUNW/vcn06moPVNfTt2ZxuofHbc+EX3Th2Xh6ndtYqjKjjeAwVepsP0+9XKu5mSKPM949v3GaD/RZLm+KhqIoR4gtDYlbRnTZ9J6MCxOafQXfotLIZsT1sGMS0LcRPrzv1NIYadlanX9EHPQCrLl6Cj7HL/Ih6i5HGcqtgJj0C02eSnWxhMsY6QK6E6gNFdUadA4thi0Hh+tru0ifcoG7t425zNwhOyooOjEX30y2ulaXLMgN5l8XNjjRqSl4DTFetLPQ8vKHPoMLslx8HQ/cGxgCqGvYZ8O6ENrjRk7NqVqBXr+3rklV3vJdkM0EJjvyhASRpnDhpGxlAgru8cD1ZkLvGN+lnI1UUbLRrPEWANDLW/9Z1TkpWU0oKOC1vG7nD6ytDjLErhq5wVQFEPbFl012xOh3t0kpZuJuf8HD44K69XMojKAwLY0zqva7Kay3j4E6jTbLG+e2Yonh0PSxM7+uvg0cCvYjuehJ4g0/YMxFYdVyiLbDrSyhyLa59saKfcaZ2MjEIB9M2WLNzNIqF9pIfrit/cYEHOfcvFm9PAPJfPQI+2dLg0bS5A7k9pNSSNdHilPrVEIQY5bBQh5xi84RUYHeBGZyuHLrmbWr+QizhI58FReU62z2dYfmueIbH5B9ekdc8UQCV8Og0W8lC3tXnTIdYvB3k0MDnbc9jrbtxQ0nPN5k9jnOqb1LR+xWN+NRAgAsLALF17jQGQbz6UxWVdb0iJui6XoGOhOWB/epAti63n18aZEoPPzsb3u+Ns8LnYVW5Q6py6vg2DZOqLUyRWoFT4Liwc7C0Ol23oknnJjHCGfT/klNWOtJS343qXBo2YC4R7a6zH4kQ2Wuu+EcTguTzdSbZfaoH/nIQ6j3L3iKw2Hk8Vpxxz/75BHEocMG+BMeTLOS03RomjEdSJRvN0NDKhM4X+h87a0J6uG7EO7344t53dT6yDDK40g3nQ7D81ol5nPZkHY2dS2oEiRaUJAWB6LuMh7xSfKlMPQm5CQP3teMYlWowRd5NuuhWFDHzCMqxKUKOcP4bAIyeJtmfZkWnHa18r+sDIHTTNj+UCfg5ScfLn+2SmjKoGzrnyo5VPBcqiUfbtCMqfPReTRX55B1cbTqSnpUrz6gyyWR0ye6y2PP7GENAtzRVsV4dcnTasXYrHyigSExBdl3QErnA0bil1FrmrcLvq3ZbPm6hREL3TCl44q7GrIod5IBoeZkLqaAXUrjeUDqdFTyJWD0JPxAr4gqkjgePOeRfLzFs6dm6RiKEXUbpZk/sf+32AC/MKWek0irvvvOHaLsSqEfDna0/XPGZat1ouAFhyXdF7tVAWhqzfj7ckrZF3UvXX/SLNie5OeiFpq6GT4mKEgFRs5K0vfE7g1j+FE+PYcQ6r/cM3MrlYeBv7tl1DJBFaFu+DfeM2iJJ2Jz0UzrAczednz0prBk9uEGpjBBGOJyCS59DQCBv2i2JMWcL3M9VeukHVxaevMBUSwMQKNmSYt2qLl+kEe1rTQV/iJENUzaycm5IzOFRnBtdXZKFLARG1rsS7kv5AdT2VHJ8wuHH5+iIU5cd8tv8sscK8YpCxDJ9p91fkb0RDpcRBo6oyU2RwqLR37YHTtV5lVMg23MEDhRxPUFLNP5Xlybu9quxfJ2JHblgirba/KzDRzWSEX1LIR0vfUu6sVhKMBvqzFdDEffv6wjXig3hdjxRGlZ59L8HXomvxm4eiopk9qGqY2ZPyy+JS7gBzKk3SS2RLPlIvSAoZkvlVli2KcAqjwR8+WDsJqGBe1G4XaWb+/QGbkojTg4xOKQFvGyJSMUuVfQGUxLN42KdKuc0jhSh2dHTQKw4BjZO+EcHoTijkDv6xjRrZV+MxdadYR6TRdM/yZDpfK7sCRwk73gScGW5c4feMh4woGM4xmJFZ3/2z6zQWe3meg4Ag7vBt+ziMZafxiHHDGhMN/Lf5x0QeU2g6CrORSggmhlkarL1YoJMS0xzPUi8ElebLVlnEm+iU0nwaQiD2AESGqu9nJMWIvzx7sPcGyMbE9zfacSE1nB7FMQFJhedxiQwBtEpyRmWU1iQy0z24aZgwYvjIAgQL8M+W8qRqtXd8gK7P037YQgP2LaM/EAwFP5hJBSUzu3ua0mdMb93dg2Ex1ouVU2feuMcVNbGYqOZATPOwOEfYb7CgQctLTsFH5ZTpFrjoHTErTGJDZCXevLYXAKDRK9eDhevnwVfyewHgn6o3WFIm1kCYjrpeKIkCY5f26Is58YomomRyW7mjywXv9Q/vBLYmMQqZJyxmRLftIL1rI3g1NSuEuDvKWw/4tGhYzruT3zJScoOKbtAOnurMdsXbwxbNtwKmlVWQNFTaguGNOlkGbOKRXiwkK0y2bM+RsBNVebAgFio//Jp2K2847+A2luy6MXlkwKBpitDGXEdUjefX5Hanffl6fe6r3S6OAbG+H7bo+41ScFDnbs+ycn9RqTkKPZYqDHqSOUG7M1fwmRpxgv+SHpnCLSmaw1cq2/gUkkNgq5sr00AExKBAJSzx1jTRbPzJlNUDTp1pcGNcuzhly36fn54guI6qZf809xu8pJxvJHLhueR0cfBSoI3ZvgMaAiSMczZeOLetsb4sQir6RnithPYq8/j80nBh5daD2xkTC+mjdxqKdlXIjFSpjho9dTlt1safXPtWgi/4piYNt9RZMMpOltnGufqyX+P+Od1WCjJmIN2KYX72P2ClnndomgqZ8Fni4uaoBpqPfSA/be9MU5bMB1LmXMMO7xwj1mDekOkF+VxzFqfwxLmX7Xw4mhkBj0V1CNgHhk3tWoTz14P/nczxpKHg9IBEvPO94oyzs3w5RT4r/s7CfDKtudne4PqkvbOWPe4KIlAa5yPj2fYU0hDM8W5ejnmd79FuNDXZsmfN2xkiEYIKdbfsbHATFocJ00sOnZMsZanpA904rbIu35Fit72djrqKAogtt8OeHC/zAcOx+Qi+tCJiPXtKfgpbwDkvb8xIcKNALaIBBzACusU3VYydc+cd/OGr1GrP+51W3rDyQPTTVWpytjCG/fTBZkKk2eOHqUt+rFNGXe/2TF0La0YvRBsxIJ8yB6EUoIzAF6FhBprtLHolxRly9bwG2YK/sBpUNPOAdQayKihibyDuj2tdgjMWrfm8GWBFgZzfaAFmFjsIRbYp9xOL/YY5EH7D9GXdNHAkg8PfW4N3AIsrBGQDG8GYR5mKTEYF3W0jOMz6NXIO+76maYMSLxydQxQ7VKW29MwfAcK+RyxjkcsRYBo2lrKYuZBhU+7UqJZB4YXUSKroNhI9G164DQrO5qejwLomL/hvoMBsy6220D4s/DIBH8FW8vTUDAlInCwMW3b8YQBuCb4ruGusz1OFAMhEXif6PpMZ23hAujmYF64+j/8d6RIkd2YxATltR+Ffs1NpYIg3X/bqEFIr34r2OZHS0WnYQICZgzEuB2cLPPh3NbSHCznegajpg5MW3I/cFS+pV4jnfwgNnw0K0oka2f48jc4v5Ybs4WOWkHm02GykUOYwIhsDs9kstJs8Gp6ROFkumM/AvVtUoS2eJAyfjRHIkeU7HIrar7CkaJXfwqwrEwuEAW+3jyP2YzZly4oURoWofRCSgL1RUwDACY2QIjuFCIM8OEoYXwPuBTDQjcjA2IUEi+ZrGLp5fTJfSaXKXgM0T+fHEcvGEXyDxSaJ/rTlFQEbhnvFMSDVAd8ZoPiA7Jx1HEctGBrW/rFBGNgF1H3egY0Mj7LmChiTYOYNY3jrj34GY6Q6B28CLeTaCgdi4fiMGkG/oVYI5Zn9VKrVel+1jMKkye7GvnWdISeVQWOyHJK1MmocK8foPBs89dhwoMo8/fNtwnCEApgodxHwZuzBiWPS/oMJ9xaRaLU9m4mdyqdq86dDu1NDznPi3kjfophMLkFGYvYgZRGiCrd4wmcb0b2UCDDK2VNHSggObcp6hB/uJGAPtU87IlbOBt8YDNRoFYHL67crePsrseHwCfzWaxM8XoWhWLuDJoqcmq6qEfxT0x0kRmcZ35V/ZJMhTEURK9I946NZdOphFo2/43KpN1Nb7CWeLy+L1hBfrSdiNDy1vM4QaNPbU8YVxmPU8NUw2ig1JqCzTEbEXR+lXyEEJi/nYJntarDoo3tafl00zMh7sjWGUNj03a73VNPCNnYpdqyIhg9YJiml7QcIeilhmK6+1EWHZ4yf0Fcwkmdw4/v2jFCmXVSWrgsoBS2ApvXbugF6iKmkboH0g+aERywvABfwDcgeIeDKO39e51enFM4DskNcQRuhnnQoLWNwRuZXt2++PTlv7XxslfcoVWZLwb0IbCJPHpxLxqAkiP5z+iy8aQNwGi55L3AKH1N45FUGa/NZ5ebFGVM4OKh9JJSbnIhDk0waT07DJkUEhq9VzbIcXF9PzCzhSqDWHgUkLivRTdCcsiVX6Brg77n3K3gn1Y1+p2Y7Z2lTTmvvC3MPp76cI+vzJwY+e0ob34+Tzrln6e+xbJQsisNHhsIRBvPNWiSbwe/BhHxa/F6kqQlOccz+qwEOn7JEC7T38+83YgbKNTJAvVF2mGoy9nUFJBU88upQs3zhO8zGZxInZdE5C6+oS7iNOGZbCSq6iu/fc/18jTiVc/tl/NAAhm3RMOWGqbxwtLTj/aRa0/OAfZuP7BhPdSuJuCCebTUtmvoCaemrGg7Bk7dggOk1S2o44w5z4Ms1TDBrAvLLZyGZ0SVw3jJ3vjR53v2bMcNiSFWBBBcXBhwFrsY5IqvcpX87Zu9wjGAtzbBmvEnl+FUyeMi8b75ij5mVm7HxO+llnJ8rbFCGc4mcsz0DXZ9mQSNezCBerOcNhM9KO4oPsqYqI5WYQAjY/mW8QDe7gqYVrr4MZj1HghAeIhcTamNt0EoHhfxt2E7VHJqYqTM6k+gNLceq2VFCqSgO/ANnFs1xQWYbZY9LFrJTHWsdJcyinOmGrCXcTBRKb1s3MzVgAh2b9oti7Nubnt0h7YdI4X8X2nqcI7FdQj0R1HITenhToSiqYtiXQn/M/DKRCcthXnt6f6425lwFjz0O+ujNc1fS4F22XixMIbkPFjh9a2MwJgC+tchWmZc1jolQWboiSVueQQuBbeTsgXxHKmx2V/F0n4zxYNKrXHXAGqULc2+Nzp4D4K36H7iw9ad7ICNuvAMK/5oJyPC6vw6DcM44v5M/AqVUDk66gGCFWZRexweXVz6wwv27mSyynoFBgZvDjt4k1G4+ITOBx/zMs3CtGOVO1zBFtrH20yZ7vs3nc0+YeD0WC9wiOPZC4pXpXawOgo03mQ+MpPINNgktvBuYN3a5R+9yVUc55wd5tupMq7rFUie7KyfGSmwFrBXylQNllLbJxR4515VPgcAWE23ClbXFEFsGe3+nCMZGJLR1iYugf81kNnf7iyXhGDkIf+lCvsnD4fVD9Jl945bDJh5ZyTrixxexrdwTONqwCqMJV3BlpZEOcb2aqyUTa76uW+ojR6Nlr1OeGSMpcg9lGPLhugKGoeGYMfFmMcoCPgFbp7UeeX2HFx6FGQmjOivgnAwhoCxneeo8O1VQonFDnGtHY3/yZ8go2v2mVJNziUazyOoVkDyzsfBt17VJztYwt89hl4St86ysp2Y0M2Rz58DjTtxLRMC3HKnMl7+3fcYYU0z2Q7fegdBmf0EaSFN0NI7BT2ozsPmKjeUhAVEQFh6JqlHCJniaTeYFUvg9LR5GA7qTr0sJFeX439taFBDMfREopbJAg/3CtfBQPCK2w1ydP9uvC7WndBM6g9NpNneskxEH57t4lJs2B20DQqyblMWC6KwUpXqxQwqqGV4iPUyeqChgWXJ96lJVKsJXtDCmB9Hh2SNA+KhJjGJ6eqGB46avIBEY0hG5g61+ADt3gmOghodPsOkPrNRvFPhEvl6qSja9oGljsKyt+JUUXwSL7KTFBtGaw2XMNMtCvG6OCjLqdnjq5N4HUzQS/ouG+XZCwl+YTysOQlEfOZq2U0oC+w/bL90A0ewQbvaP+QU0MT60vgecxcwbJWQoJJgCMbfOsyPSOft36Bf+x/MyMf1L5vIXpN7AMfsJiodZG/26LjP3D5xj7U1gXDM4v6vvfNTZxgSMEcb0JPxBrbBtqtdInMdlbGvOaX+VbNEpSZWDPEq71pBBjUHskIAQ+ACDJr8g4naPmu+MO/910zsgiVOBqb5tdz0gx3NF0V7PN89XDTQ877QRNS3DH30RLOFi0/oxryXsza5Jn4gW0PA58/QucCNkGdQZVwAmPkbAYpXXtiGI5Yej4sYUKjeI0NFV4j1uEKvz5YbYQ7RQ73kEF6MfPKnKUEgbhngs1TpgWv+BmOCGkQG8pZCIggq3E5rtyXZUv7lfPLI01mAywqMmfQZlTh1fSt9tP7dfPKUY5cHkM9CH9XQYUfz0fpsprGFegC0Niw5PIDaTt3oo5s/hj9i3LdCxMhmiPMUdlUNy1b2ZAECy7fLT5yezsU1xvQkb9PSZ7Wbn0pCaEbUSWOPXbqb2qOBHdYgzGzpskUP7zTC3XxGlP9FvGydacA7BhkNwLch1al+pj+FN4mEJJWyY8WUlX5MmtfdbgDzk0gjxGr3ag/JC4EPt6g6u/PRRq8+lFZjyZhqMrlx6pO6dgwpnO2Hl/BZbMGCOOIMXDqKfSAG+u3IyCTW984O5kk6usiRmwaVnRwdEajtyCJakgZemYy19+rsSvjM6EChgm4UROG+jdpra+PmWCLNtKPlaIkuhNYW0ZoGDoaJ7Mk/3LHQhCwa2zpKQzpFnFAqZS8peXIcCB/V66XCSRdJw4Mx5yr+tr06julqD9InOs6a56vXT5ZRlN+yyhBlgMP76Y2hGIM84u8FOhSRbzdfacmQFQkXbMnFX55PoFtH7/KhiNwUk3fM05/qH1TnNdOTbrLZT+RVvItA5qKd1habJjZsXVolpN62IKT7mqiZB0rgcbg7RYgHhpL0pLJsvUwWzabpsIzBVOrV7+zxCyZrJ09RQjpI7o69ZQKByLbm9WJ5JqtwDMOh9cMN0bZRD9S+8XLfLgUq35x4juKdCkirECDoSMRavr5Sjq673gBU4ShP4xq7wssI/GY6VgnMQuesPS2HoI2YGXafToA9zBWqXbKfWsgGK85lZUjbKGgMUhlpw8iRU2hdLc5ronnex8ycyEjPh3sUg+VcrB1yKAskMHI5EH4kwTSly3bGFDilNJEqlx5eFVabjZFf6AnPnCkRKCs7QTfc2bwwnOgO4ZVz/Mp7SQCb31HgFec+0Ba5raIMshbv07ggZsMCYeXZ2+iWK2mran4yZq0hsF8NZs3fUdXPJFQaGVSM9Ameh2qAElQc3HYraU4PzKIRkY1uPWTzhJ8nxlFr5JbuCKNu3Esxp8kUd33mSDtNCWVd3zMdFlwNW/40joSMJzqVl/0dwD7IH3XN/li475KrKq7QSbt32V+awKz0lP5wOqNQ8S4RIJN1zoN88hWhbHy8KT+5cyZ7CoXK9vohigeAxzGBFy3pxPLswIEVkoCtibEsd0J4nMxkHTDfY8mhgfmsnw0IkDnq2j2BgQSogLUpPqd6ukahJirbOkKsdm2ox/SliDjp+jmmgu5jgv1ySLu3NgwUwgYcPA2Hw5CR2Uqz7bsZzP7txGKi38WYQtLmzjRNx40wIGE9Jw08MsfIddvHVCCOl9ajVA2iF2HH2ok8vv6RKZ91szyVM5YyIybVny2DlCzvLLAkxckAFptqC6vj5JVvJGxNcoLnV48PasNCm8CxAPUo0DeW5H+KzgKBxXrhCT8kcazMwpJmRsb49iV4PbcJ5n7qeKTzeDDtUdQ/t5rR33bAAinfvzMUjVKUMYF9bIUKHdPHrrmkE1VsI57jD2UoP60BnYZMAK52zkjx6AieWgo9uCsM2emlmCQRjrJsRPDGuuLbnFAK4KzwmX6wVB0/UyTRdtoVlRIlmfftn15Q9RFcpMjup9tImXdJkdkcTAJEPanNKlmt5FDhuNvzvYkEpQ8pxxZ8D1tUYOoQw+iC/MDsoSt3NZG67RomqrjfN7lKhv7SmP0Dx+wou1YT0RYQR2krG5yp/iPqYSHDu/WJMipbluCQ85EdWUZBbwupm9RAsyrRc/u5ikgaucxKj0bW2+3dgvcHhsGZI4pXPmG88fzYzVUOem+Thj2peGFEerOE55mdg8+cMkn/ol7trykxbnMhGh6gL861T4RUbV+efMq3Ufwsu1XnSlECLGnI9tLDRlxc8lXN2mXJJr2YErKz9qWSWk1DGjSSh3gUJffXKzrP4VOtdV/BYW9kNNpXQ0FWWm9GAtgumc5hYKsoSgWPBSjXRx6W/XB/QHtGAL/MTibVQpfBI/ioCohkx2Ai4Ga+SD8cuNm5HVtVNDCXRYUlQRtZbMbY/PzUYY+LO26jtswMlK3leM3LGq7p9WXd2XRyyaH012DnTxvnaDttB57cN2KQEFqhK2jX/wLh7PAi/0a2hR2dKvK8gPEuMZwtqVfB6byafAZ4ia+TvtfJSTzvQ9zuz4x4BkI12f5Xnlq15iGLo9I+j+Yn0QoV6q/4Q7SVbma91olIH07ikeCwkkMwHqcGWRnODi0MM9KJothUgW5gu3l98VAYhYI3nuDj5uNqjeWp8HQlxRCjXCNEDhMnPj15N+kg+GDDLMD2dzg8j2rumiGOUR8LMYto3pOsePhe32kxcfSDiI/lKYOCPfmMfboef9odrdqI/17m2Ja5Ad0T6gVY/Swehax9xGEUXRrdZfARO5DJNeK5W/zy9/kbijNJBN792Gpe0V0xP2J/TNNIefLkS3Z07BE+CgA3e3+ncy0dH6eMhXGs5U/47hpgsNr8rEASesTlOW+aN1m9hqXaiTxCp5yXbFJsaSEzL+rBDA8POE+41mRcUtCe2/pc7MSBL1hKWzSmtBdsYidt6iKTOrscFz/Sk2uEPUO22MGJDj9E9+pORCaDl8ei3nEpxsl6d5EtuUPUI3Q5bTKcP4WmUFSA+K2+rGlC4ZeZ58hwgP3C+mxRThWIoWKA3TuD2bJAJ0c2vmuQkJfCmOAvU66tyVC2yhLw4D92d0WGsLJv2TneV/EIasnINUhCjAKUYwaW9MlbvCYsZ5bO0Xna77RHRrnuDbhKpMMCwynAwbqDFOHKlcaC0yG6kFzN0vvFNoxFlSFSgnp0kilVEDD4dDPoYq7y33e675Y62zXTC5ukjnMHRSJR+NblanTke56CL+vd+DElcprOMT9I1+gr+F4s9B1bJMkDIahPUtn6NvZS68vV7HCB7pjrsiug8PkvpaFEAJ/EpxT3zyjOSe05PdSeoXSX6qYp2uugBraRAxlZgVpKa5oNpd5Yq6yVQ0lsE07BT4cjzF7+6hBgnnjV7PQAMjNNCn1NJnQB75LV6DBznjCsFzww0UdlMW13nqGmofip77DutBSZRlz0xqPbHBXA+iaJ9kWVXZxBukJSK0/fUlPVO6fIbV/OImiFzqZBsM/cT6sM6vQavBvJGRigHCB9loxragcUW9Hfhk+GTnkkh+mzgRecIkKiZ2R2oxZZCYScP7FC7LIrweearNc+duCFT0p0FWhQh90wpcekCJGBdjGEJ0Mpz7AlFgBQu++ZqJgNTxLeqKFFswoFvrCSp/G52fvp+AxOD0Pr0xkKI7mPT3YbeGuxPHEqnxj3TET5I9ipHeK9DKYnt17fD2YOvJ/Ij8F1fcBhlgCR/nqJQdR375xGquMZeq4VNVDgrGgCN7CbB50EHS01TNsMGILjpVoFWjvodUst3T7Vg/8KNYL8hXlnTpH/ygdRnGKOQ8OeL3Mg1ZmKrTlYoGkwwaY584IZqL2laagMYaTbnAW1KibAiZjMnZ9KPLZzH+DrDHvWet1JF/vB/2F5g3Bh7xewIWXOFKXoNqXZJ+Ai9fbMSGlCV7Xeo0MA6tzBOw03BpJRRlSKlYU4PBD7UMymw6FAfNYgIfC0Ao16e6t8gXNzdc1QbP86f5Uyy32Dy3Ai9G8x+wEGp204DMpdo3ILbDBpApbspRZvXMvdEFY2LQWkcsLRpGTHgW52NXvwQta5gEg1n7pJKHBOyCfV0VeUO4c0wStwMxCbRyYFjyrkMc6jMe6ZQK54d8LJ+GsuoN6Xrn9TEV66Mef4Ozsio53p7UYEo6FhIVYQU3FOJ0Z5Fvti5SjwXCJ3wCirN1l7FUgyqL7v0IQW9YKmzBOtjDq9iBgPcqXLoxTHFH2Z1qD0giJ0ey051NWTfn088ZZKY+S3dXayMIMY5Na56MgCpBHs+4D4riuz9YD63pNgTx9+hPMcz4RmIeLQd3dMTjxQw1ZtdqzEgM7XUSQ/uMLeFDfINwSUrC3zOW3rAFZANIUOv80zXB+u3t9RoT8YArG83w54/q1C0P2DpUnjeS0XcpgAG4oIhF6mmXO1sNIWxncXg0omfZZICZCJlKg637c72zKIA/Zk3wPt95st9Js+lIGdBvThqlWLGmlM2MPEbhE597o3G+L9ZbbFfWOVaZy7xYJEA7gVx7KaVcza6F0FzTOjNDd0UvtId+iamcLjMLN3rT7hlNfGkNLTk668uIPcXgNauVkUX4uux9ebZbm6FaAMM1Ns5kmyH3IZx/M9Pd6n3mBwUTUyPaa9Zjxfe0x6oejpDTTp4HsX7g+GS2LvLXl/IjYwUxMyMIFjPOHKwcPQ3gvCYpi/6+FeQyFilp3JVwbtyjG8a7FAIXSfR4a7C2c1+IzBvks6Xli6HAZDH2JdTSg1bA21UkM/FKv0UqxgXImK4ZIfT0Stn12DsT+YOeLaX7Iok5x3jcHdXrVEMZOCWwZo7v3g45gOVRBoxMYaBhkDJqvlT7KfAVDFaheptkLnCimXS+Rfvq6gJzHJmhr9+1+0yGXiYn0Nf8XS+hjm6nJfJExL6QzsJvJO+nRir6/hVvIMoH9atrSQxKaJZB+LkhD/QAwwzOdsKJ6arQUzmgPTCsRUEHPWGl9MVugqUFKcR2q1ixIYrYXbRV4JBEBD+Eop+IvqgPSIfRBf9kjjj3H9KrsLyq6+ZBXlb18l5j9U8QQrFwbYzxoragZRKBdcBbwAz6eloyU8fKxA74IKGDHN4uHHMI4A/Sj56EsHvLJ3VLsQ3qcrL10IxaS6H4v4bOFOWl3TUdwLRfKnyMJvscBCUbY90hnAKuFDzsIk1DkrssrxXWFQAGmyeM1K0SfK3gsVI0OYpOD2xnuS+V1j5iWmErY3bfO/lM5w6vxChRhYr6/RafQmvn6FS1TsLXMv1GiF6ASBtq2anAtCyGtKwklzcMiwxvXRpGZit5+ZLeiM9n6cSAFCmYzM1Z04ysH4wcT2bDfGDx8spuyUEYP5JrV5SaLwgETonEAsuJoivlxAiJC1M55YMbB9RZhAUHA/5Yty1K5pxBaklO33z80CdwTVd8mjTQ7OBxKlnzhkgTeUp7y710v2Up+D7EUsJ2RlvbEqvIHRxZzEJS4PFQi+RMl8luv5eEV1M+3rudpswgVUE5WbT3hZOaaToqudr8kT4Dka5jGMkz/RchdYH4soKTDNSDMgwn1Uhp4x/duary8Ifc5qqaam0nnR2In8v4l8t9tq+5E6BB28sx8WRQo15Q50Oc28kq23CceMrk1gCZOEMxB6BuKYqqRfcK/sbttD/0KEFTp3n6BmCHp25SSo8hDrZSDTLa+NzoeDNRD/DaeofTXjGfgNFwpOLSc452QqN583TcouMhQzGcc4DeSHVXw6sebqv2aOIewmzAHjvTOi9iKpDiFtCF0D9cnIOWXM+ymSsilySxTBewt0VobaRR4qhVU8Pmae1avNYj+G+aeTgZUhjW0A6PuhoUk4f4O+zDF7V+Y3gMA+llyqQX+JtLCK/0RIZlHUFUcBYJvR3E5UpjCqBaoTbEuz5s4RMxdXYEjwxj+wwDqWJxk0OxV7lFH2ItUKCO2OxlwC5ykUSDcEYAMDUIcPRyiB8vousfyGuniZIs5+f/SmJKM2R+d8UbwqQh+b9N492SGjdquthjFIzbpSkUx2iRVpcfrGUFLTUkHjNGSdv1LNTZf8lQniwhd1cN/Y/MRHyZ6xcC4ulyQjD7C5ZYkj55Yk2zYso13vzfH7iSXqhEKNLsXpDU7pSiz9hMe5bprlse1hPfHvkqVbDnvTCgd+VD8FF97b+5nnAcdFvIV92fnFv5DadL31vZSEjxYalPPNxy5y9XO2PgnOGpH8LFYOjpR4+6nYwK/Ck2fPwY9XQfmKyBAOOegqtfNUluQWeBB15aO06insRghktnOHMH4IP3qlGdP10ooGNPCNxhwkX2llNZzaN9dOj4ZA+ovWloIBcmNwbUh0qh/45nPx4qdblOTgGrS9k6qmbhnp6+4BuE7amx24Bd0JlAzQewcVPnQDImtNjW3zU/qYPZMMsuhknZRNvGJhgsu6JOI81vGWtCp6UxT4NGihP7PIQjk4nPZsHteXWnkjbyLbEIS9Z3jN3m1ODhaVUnMd1FoGIgJ7Vy7wJz8RpKY0h1Ow/65Y41d5TH8rIKAXU1l1ZmoNZ1hilNK81mhCsGuSNjXG16BFNsIdB9Cw1sJ0weQJolq0PZwuYPW3xri6yZfiubdjpbrNIReFoxGKn4knx8xZtLeVXhEJOd4WWQ+eg2N4eqpHPjWYhTTMsKZ5qHR4+5+4w357VutKXazFEWgb6xCnBDDrF+7wpaHxAz8iCQ25MFVU1cmg0n1Ea3SJA6xn7Wq9COUTIpS8TX8d+tHf6GWvmcm275TJEY9vLyyMVBX36NaBmgED/atXGqoe2PfI35fHHbKXhSGWFnrApam558IjWCK7pqOfJ6Kin0tmPErixI+ytSjqiWyfbtiXi5vSo714jpGlVeuorcXA4kPaUafZ5rXo/CLWUbSc9BMIEm1niYzzqOXZnp/FCljEJ66v5Kmqm1dvs4AbdQT4S1Z4k7oMJet3J0KXWYKKC3D97AUqNzhwC+Ll0mwwwSxBN67Xkp3UBA9flwVzo4cbe6rb7BcdCjqSMfFlb/rqFKLF8RbhdIWU7z2MnFXdkmyJl7ovwlQAYp8nI8yKtTPk9/5tNeU46EzC9kXqPfhufgA7U99JDNAWicFuJgQrYNKhbp/5kMeC9hTg9mK08lyJiGiO9cQCRKEun9vpA167OxiEcbKQrVF+6r+mLUYNnNWgfuzyrd/q4Q/2Y5BzZ3ET3dUUZdTJo7CO94J3ii8wpui+Fky76VDiCqTL+GEXTvwTHXVHxQWfRYMNbEs9LgBHnj/KdEGTMb05nw1tm6lb6OPZ87yDgTa0VYk3oCrvaTBz9QTXGhDAiqjM7gwBrwMbpH3O+PUR+dnvynY8+x0dYwjlUyzY5RBk6YfrIZNLnOEAnQ7zWaq692/bXxzMAzaHAmjgwvalxNCgXLHyrx7QpcqkdnC6Jr7o5GErfUbI9bL415HL+7MSYUp9qjwc8T5mjI7qsfJ4iI78w6M4sHAjXr/0/AIv5rqHEsCUp6Na+9ypGmpiHfrC0keB8jSTYzPRiySJmA4kBnW5SAf55tGtLoVxpH/q5cDWKZnDhtanrCseOaeHXhghuVfUr2Hh+C4dr8ikDYMgUiw92XMQuNx018z0PoYZFcE+xwTBR93kecLYkEz3FeTASWaCXsMGVVhujUUxEardPxQXUzgOwK+lWAO28sTIwkQRQNhuLRPptYkdPZfrlREfLkDdKCnVVP3VNvnEchJQZ2hivoBpfPP0hbds+ILfVzvcypgjAlEHfS+YbbzPK4HnME7Mm0162qImPrsGsI0wvu9MxKeyH/8ZZYzV/iuI8Uhg0UdAOe7xz3E+r25hGccoCl/m4jqlnL2b6kmoBswZ4xNytz/Dtj9FIPiCNmU4f5K4SLeJ8vp6Lcecacil/iiq4/JiTGdxZSlGLkc1Oe7oWHNRhLkbKESzIRVeYirI/t6BI/awV2iOY0piqCFm2mE7UHdhnOGuQuYvtKRHPVyH69Mh2DI+p9cXkZZDTwe4ZJQVmW28hGIQdYHr5POBjwn7u3NIe4hnUBz/H+UpTfKdZP9dPJmDG0T49MfNzwYIguGvq6ja4Ek98pyj+I4KSTQylwr+0/UbSHDXRn/j8iPxBpuSTyGywSGtHfT3/96D1y+uWmAQGL/LTTQlRpSXoIBOPixi9EucyDS2GELxf9g/W5BuDgrUCUYZU5qbTO1mjAYAnhXqM+hdcXcNuy2Bu041DqTxU4+7yPCBxDcLiqSsdFYhAFlfEoyCsuVwparLxHSOGcn+GA1k8ZcAa5+p3Is3WoqnnjJaob0sJWJZHh/yTTvf0/bLB8vVJFVhGgk3hyd0/+4PlJHINXCAxE3fWUCAJ0IUZzXqfGDpfp756ab3YPeeW91JrEtV9rq/FtjRnPdlWF9yitsIsiM+FgRi5FFPcGY7huTy1WIz8OSua5weee38EUma35xasZRsvcLxgXaai42f2Jt2mVoxmglp1WaBAD7eUXiAaHw/nEWK8UTsiBdqlDsMZn7tGA7RN8yrDx+mLK9TEwmMDziJwiNlxE5vCsFC6IYn7uZBUOumnmBwpqnAZzYJKmaTBB6x+8MAV+hpsVm1wTnE3NgSjdjBvGmKQfidrdctSEHHMlzJ4orzzGSw8W16n6zGr9KstnhvL50Sh3+ZyoSxQ1ifGWCBWYWRNtT6bRRU9+m6VgjiHaTMGd1P7V9PjQgg3o59VNQsVxVkJ5qoIUt3l/Uwa/lK18139MMAymXpf9ub5kadJ4wM7NyvU2fPUIYRE2ZSiQJnZmeGwyCnPSYmINgDP3qxiRm6QCW2c4LJO2sH+n4S+Duyj2lZhM0Y1vZaFRwOqFJyoVBDK5aW/SgkTtc3GW+4rGMAtvWlj7b2qCQfvSVsBheF4S5BHG9N17dmEOZiKjQ/yrtK0QRErtQEzUnuYbEkZhsnA9kJlmmUpb+MiQj6nJ3ckbxLIxnlhuV/qJ2ec0OvnbxxhkZojjEimaATeksZTyLl6vGU4OmJ2OVLOxd5m5SZc5BsmBcbr+V4WAyJtqT3yE0JJ9l4hEplsklyCawY4KvP1k0r4O68zdbuX/GZ7lpGdloPQJjkmkB0eABqnpCX6Bf5JYbVJu5izJFEmGiZfAitP8B5qfiAIUGXBXprfPGmY+LR5QwPJU/VZ+YPRhMMizMdFxbffqI75bcAjWlIMPb2MuWJ2kl2TNHKgzo1rBg9ajA0OnEnHSEtOOh3QRvPYofvQfmRwFkjRMYYU+8dEYQwazVLPVxx3Lo050Ui7P//yNUpII+ukcYZ2rdL7ya7nMgHtYpSBxCCHARJQY5h0IuEQmlqVvXRbrsCvy212ae42coCqRW4x+kVNHOcVdWhyRjOl+RQCHPmBT9bl1sNwYrPHpNPl7TlD88CPXvUGFS6Viqiyn7kSpZIJk3rNOBbp7eJLO9KNEccYDfoIwHgTJy/4PdukiGWRp4oqptuAylU9Whyy9cpRCEqs7NkSk64BHhcMHw1iIXr1+aLlrUH8/H4TPeAzoUwek3BvHjWY8yQSf8vbmliHzjSTYnqIeYFapZn0QYzF6T2il5zHuPIO5hjQyhfHy5FgTBJBY1qGBmODKEoqgSVBN5GQQLdMMS8CkNlPtpa/i3hS7pEfTL+Zk9OetxxJzIFBz8iHZhp+ukNAqCtBQjahDl1EasEaG2NzjCWLWw/lzc3AKITQbeUcMnA44rH8Siz7n+ev/DVoHEkrdo48fys6oLPJdEnOdivM6+3AyGj09tsTbQbw7Zfostq2xcRVZ4I9yHSOylOj0scBhMmtk5pOcc92qpANYvWWunq0HLTyQhyJ8zmYTPMaAEHF6UFTnSTsglxaDbnBWrXd2pQYt1DOe3aMKwBh1rCmcdEFDjuNEIattxbtRAKXqjLuWtYOzcfxVnJ6XfKn53JC8Q75YLta/lKcCsWKiLp7qnfkNcy4XBpBl+ZwTIzTS32WhYsmbeAWJKvUJ52vd+CmYM3QbAd1/832zNh/syv1KKPvzxzUSxRTfpbaeXCF+KpcwwFPXB553KvLM/Vc0xh9Od5aHRGQEMhICGVith6GUIUOYOWd5fTF7kR5PsimlPyiVniMF5MvtIXAngfF6LQg4zK+KidwSWcKk2zj5FmWaed4X+tLe4IPwZrme5Gi6tAElT84IVcJVsIoqaadlpd7btzwp+eal+ONof8pzD1dxLmFoX8/j75cMnnhKuu9+lrlKn5UAy4pqAOyuRdIRHxCQ0bkUPAx5NZNo6L9UjRJjosemU3Uj43iV6XPzNqSSJ2/fDicQdVR4nhSzBVQH1C1pgPru27xj54WHkh7AGDhIJNlFqXLlDUL13wS6YshVoXJrbpKFVu4ngM37QAAZUlsB3yUqbNJv8P2mhM+DVbakdubw/wPKa5Mb/2ITnM5P+HOo4vIdQgTGWVZo05E75w1y7Rx9PSU5hYNrAi/YzueTWc26r78s2+iO+igHkQcgGAoeVnVnR8FKuQ4ghTJWg1jkpUDZLZIWAvlcyUPHm9MfOVM39uS34HCNp65I89MFgglwteuiR402Qx9MBmOB3dSw0hidGXCToPyQwY1jN+GtPTsom5hqE7iZZo09JJlB/8vNKXK+/TAkY4qZvpZtM32GppK3SiySaTrZlvuxCbfenT5bzirR8DvYUXmiYlKBhpuokm0y5eMqkt+wwkmTxbarlSHeCqyCiXgFW/KFy14URf6/GZaFWfzXoAKBpHJlp3cdxBverEk8vm4fgbHlMgSs68nvUBxCHi+5lCwFioTcJpqflTlQXFM6EdxOcyoWgM+ZNdsc4PBwgZAXHxJwq88r5AhTQJ7zkFJuTjXmE9XiMMY8HY/h4lWH2Z49fmBATim7V2ttk0ANnFDXpyEVsUM6udKNdmftEAsg+lZHY459prVpps7OWqqCUjTskigTiYbj4H2UnowjeXBz7LJbjwg8eD/pPuuhHc0lhPjiuqpRT5L49bSWJF0Y9nNeDi2aSytKoHf/F4YLkl633xnJDDAGfySUM++0RjTV1Ft1LubEJE9Y5AvPaNhErYQdqTSuZN5clcnZzdtP0EvdWNthdxD3GgZt3IZV2vGUZcydnmJ45DkQLM7P4dz9al2a8zr1LjoEFLsdQKhVZDeYJNj7Hyq2GqcQwbQC7/vgsucV9d8WRA0agTPf2zFk/D59cCegkgG94DN6hpldPMbGoPs5+y7Ze5tl47s6xMybamQnbjd0jC4rr+wI/qfs4y55jY0e6yPGM2WhWG/SSNdKETVYn9zDLqiFwY+8MwCSWv+EcSRHUpx6u4tL9Rlo7UmI2YK50kAGMNDC87YcEBhTmnmKm+jc3LwAsFNxpV17tPkkAoGv/abZHcjec/bEYAJNLaFFpX3SSHwnXk1M3y+rRyCyKHyGCssZmrxztbrSaMBelQWE5j4izHw5NEy3dYC9c0apxgqZKECGHhpqA0UWHCAC3DSChj9VhTnwvDu2YITH3HP8qibTLHMyl6z7z17KXgVDwtmcDaLVHhLZ4rpMH88r8y2Cvu3JXGyrAWX6WPE0kAbTct2MQJGf8mBV4SAxNlzmAyxlXy2CsMyrNPYuwEhpRT3erG1Cn1ESnnp5hzt4fQd4IfxKRPXm0EeRNswYHTNXwVyCATJ7DV84xJQHEGzgw43CbvZN3aajI2qNItMw4teniqsIP4OI9tzCd301yS/43u7TBkUhKjnTH3WfnZ1tC4OdlXYvsr59XlNj+nJVFVee4OCEo77ittHhhiSqFj3QzoEBLR5k99mgCRps09zNIAowrU3Vavt8z0AdkgPtS6AfTFUdwb7Mclm4L6ZTcDiV12POkd2axnBqLhbCfu8cmDXn6Ksk8Ov/YC4xQRtbKxTnCQzaRT2CtvPCzqRNQFJmCoopd3OU/LrF9PHCSY3V1oEkcdj3wyadb6tiRpaTpufiggmrvRu1bgMJyb9kE73s5IFqvQzs9UzORiUCDXdzoOdzBOm8wXQwfCcQ8325VVA5Yv+YwtLq7B5A8+whti93QuNwfWdnnryG1C+ewAm0+9a2egehYocYtoh+RYzRjHE27b75Z8gB+MUW5qvACcr4YHAS2PMFniSeC2xZafdNiZwzXuVbz4vG8kJ10L3jSntcPIU6MRch4jT1EcnnlZe3kZno7HJGVfZU5XF8yKDmQBN0/9zcXoS1uQj9vwPEeqdamAknF51Sm5q6twk4zkHLxAOVWf0pxG98nymcg99+BidVuNOe0k5rcG1D7Ke6CkIsIxCpaZ0UAhcWYh/8D8eJDDvgcpZh22TQe9pq139sloMMCTzIUdoGWTZg19eZVPBDg4AV7exZKI5mZNNVJaTqoyTYDsvgHk27t/FFWRc5SCMJlEu9aSZXk1dVlWUQtCbRSw9+fhN0UX2J9LLUUiGAxs6jrFsno0PN2z0kG7Suvo3V+o4Fp1FL69Wqqwdm2Ow8ic96jVSmgRa9+MCKqaBQws70v1cCNrdkacRv1tzTYYIpvFp+3FIoJJ6o0tSiq0r5W07aDvW3zOUwQsQnvOFbAhZ7CV1Dhce9IvO8Z3x7Bo7Qx8M98eziIUk0gdukQEl7CQxZWaEEIa0JaA+LYUAGozvMmwus3UOmabkYOjt5iA30vzbEzoVyI6zSVTq1lBUrTKj3JOn1JO28GZUZiZOcy3rbVvZbpNEhqmCH9KXMpWZAANlVxYnAT+xBiNiYvNBrAoQGeYlXQwGIOa0O7hnEuNuZwuSpKr4WAxCq4+tzFSJN20o/Ffdyno7ypMgHc5yRvxkmJVJMgpAlvXrLcwAYfQ/2lMUQNOZP6oggLnkuYK8uCM76cHvS/4NsK+2HpFCifnSCSHYiz5RjFBpHlBXq1IwfV/narRPnp5xLckJTlSU4PDbnoVl1bL0gWOttsm9ng9W2gybGtC2ze8pAro5RZ2+/s+WhTzDaS5O5SjGMVbMXx7R/CzyoKB3bAeE/UBv6+nQtf0rw3jXx4pK55uHFA/GcFHy7fx21s7gi5xTyLNaSoPX06JQOIw7fGUtN27dihIsJ5l/kPXYa3LzPJuix75IY664QLHV+KCOGr0XMadawf2jF7ntDyNwEKrgMB/9OkDRgbQw81vjn+UIn89whwfkJI++29aAOhnw7qsEAyDy7fkMRFSfhaEhqDo01DN+jmIb3K3zqr2fnGp5oQ1wr7PnbDZHQB+ULKYW5ECqOUzpe7tZctSR3v1Fn8kkx0HDI8gVIHF32uj9LI+RxZGRb8U5b+azjKIukpX+2WJ73NTtUp9jVJGQAaK264B1SkYAqmfbqfGVr1PPktiiB7iJ9xpb0E0Rh7ScpQvFtTnGok5qRaL/NnMlx/MLoQVCfn0xHV00FT+1iv8ErOPato1ygWQ/hT5thiBew8g1XRfVwtVRlniwlUHhkDJNA/FDrtMoWQVfoLFKK0QkQGgJ/4BqHB5KPFiGnkNAT2cRN8CpkIxlEicvIxiQcHKLtngqFjRjDOWkJI9uO0WuQPwtLuQHdUKvuGm8BdbTlW2Oe8sLVmYhiaZnn7ecL65KHfD5dOvrA3n6tVH0FclMoqzh4i3UXN9+en+HNBiAlz6LAXBTjNLnessM49XqeshrenNXHZ3gKSA9SCuJ3mSBWNK6Kv8+HOBN5kxmJeibmfjBCpFwjfLRN0kfLE+DzDmrxt0Igp6WJQDW72EaBXjEOVXmTTJ2zawy1RWIldoUUOh0Ak4H//rsf4GTnYSmpZQSSXMoj5CIALuzC41Pn4y5eEZjczYKDzDjt13r5rARAmEUEzdkAN4iuFN2vUxJmmm3O8ihERlEYTuZWsiKrr+KzjEWdONykzXk34iJ0/oi1FQTqHOrTJF6I3tKlHNuL0SMEH4p8ylZwROiG0c9b3BaOg/9y8qy+ME9Mxgpki4Ui6P6ib+hSU3PW4/ZMbSuPhecVYG07k/P4ItEWWSsZXXTTJ8163dfzzUm7X1dTpb1ZA50GRTWmIjlq3LECA4MhkvZhfse+XTZbQ69uVuIK8P4DJYT53WZIo7PngN7k11CYLmS35Bv6Gq/l0+0PRwyaHhnFAJ4FgPHJQwFgLbrA1wY1JinqYXDlD761ybTz4AVkgp4pyJYp3iMODq/Cj8rZcTyzEL0W8IRLRAKNu/305Kh5NGlqaZHYo58re7gI6rfAAPDjHLhQN2uTBx1kA1rHkaAWeTi0dDPl76c7JQuiiCJvB1wDb8NjycM7aGOQF2TbSxFCyuGcZiPS9N0cEe7qWGw5aZA2EZq4kHMF+cG0pamjVW2Qos39oOcOH1CPvO6Xt8ktcz5WG0gNY3+kg5EPKk1CB6ZzFef1lAuBjCO8rICZLjNcphfs8IebygQW9V+xTOY3kXdDrGziAkFRvsO6iPKN53wKY6nnFPb98kwvKD/QapKvurLfdUVIJM6BTJVGfvaUSt8c+Q+PguWbCrNuoV47ytSsgedaSEjNYY+SFKrMAFSuYneLD/6KUtHpts+qynjn/3qp7G4Sxn7tajEnWwTp1kTeJ67BClZY8GwmRFevhFWMyKaXLfkVEJQYKHcZQUroR8TYa6Lt7D5U0Wd40eprtCz6IwU7Er+ERxDz526vnieoVgQxS5T3sEM8OpeNEl7+T5HTHOen3USDVWnBMrgoKLJ3E/DQGcxxaZKUb8INRu7xqW43snTOIpPUcJGphQFecXb7hem/fjxpYWAEdJqlLTzhXhwDa2Xf0hjMwrdrn8hRtqEh+5B22m9uB7HkgN1+lHtKokkzgNBnc1xjqrZ7uOCHLTUFaEj+EusYPs62I3Qpchun1y7mTKpPm8puEOy9VTrgCmLbyLEwZf+bEaxUYvGmc414YQAi2a7URp6BcDots87vOz5pJv7RqjO3sz8xViDPtyX0E+NrLMadTmhzQmJl7h42X4s9Z7MvmhvYbMaUA0vFB8ftL7IbZIXaS4ATK07XqHRNF75sDyEkNwIsZMVZTv4XJOpSOrSx4ve2UhNz8ve+3IQTV/3SQNyQszbgDvztEH4P1/Fan7858IASIP28A0KRWQlBeD8yWmTlGwHNHa8ag6kFFPxbIYCv08pR5YlPQul7XgHDDyhiv3CbVZPsr3c7bTcl3w8XvASYlWy3b5EKYaQFKanyfKG86mW+dk6k+gACqOr8/0FruIae7kHtPGO6caZqBQOGPhk2/CXyts03ZyjVHw6GnpIE8OtjnnXkZfgLeWA9TJkgIQxq7mZjdmKp7+Rl0GlodcIE1bI4777hSxajJzbsqUJGGOVrWdNN0kXtFhQluRpg4mOTnAHfQ1j0yN5mpq4wQDkVRNAdKrTPd2uZWDv5TkjZsq8cgmAjdtVhkkCZtOvIjQ7gis40T9IU8656IoJPRTnVnJzaIxuHVHsfc6TDW/AU+CsKzbL13fSSUJgMuiFW1tEI1ngYeL5TA5Mwc8rNxt+eo6pJ8uMBMzkgIlpaTJhxErVcv1anQXAQ4b2nf1RUWgZCuh/TKEPtGBBRz6dxNum2+AqIhDXZXYAoTkzlXkxp4sUGEG3UhwZMFsvJoqKsOwYl0JnVsM1yuWhBBHD7tVYMnepsV4dRuuB+rwqSP+6IjjbJ6GF8lyvXIVsBg1vZrlXEK4naLysbcUNNB9PgSmzdT+L9ErWN97/ltyQpXs2UuuoRw4Xn+X9KiamnS/hudbqrHbPSr6pVlt1adO9LO8xgOQ2K6YzWynpyTzIPae94qfmpdX4eEoH8CEIySUL1miaVt+/kFVjm8HOuLvjPQ/IQXOFRDZgC5L3dy5+5h3ua8RJy4tz6debp8PAtlM9zX55F5RSzYvfVxIRg+C3kiERfHTphoR9NcR/YJWuYt4ZVrQQzbIBcF0tvalLTyeIEVqYp5DaF28UyH09o2BwP4oQKrZYdhgzkoozN4dgMNKRc+BRZWEguJi7rEpBHgRjZi7TMJgBll7yGdqpYh2E00+JkkSvcggJuNGMww+mn6sbbVefRc/BgXG0fghYe/VN8pM8I6BFzuIQ4KHuBzdBcJ/lknPnfhyX045nmWbCiWwKlXhnPE0p4YhbHLI/VS60iJ4RGHvBc0OpdT78+pLBEPZ77iS/GsoW0BTMcYFx2nOeXSLtNRhPpg+vdB1IOZzJddoYJVNe6qVK7g5DDSz5QyIdZ+b39bGrSDUwomii5r/RP50kLZbto0sTxCIJnj4Hpxmoo7L8FeQbXRmE6OVbWTSVuF2ZiDeD71ThmbAC+QpdfwrTGD6CyeVz09XPb87Af504N+nBxDQAbkaAbanVKHW+zg1dbTOunh6MnVglU6ZmKyUIw+gudC5B/tK//uVffn/9y3/98x9//+c//vqXfz3//3aqsMb/8n//8vvfv/7lH//z9//Qf/nvf/z73/7z387//V/4u/h3f/vP758RKINxFWoM1X7i0HMiY3NkztfwLM/f8SwCB3mv/JPSQswkf45UkgC4oeo5a0EsWFpqtvcXWlJq3igWSbLOoG5f9OFEeQQsklN1lg6eO+iD57qwkBiGjZxu2tRNKZz4JctHAe0Hzx84cZSRCpV/oqY1c57U+WV4yVZitzjEzo7qX8YQ6lD8GBl8d5EUh1Vrw6XO94yY9wD2fM/W/1KdQyJWWkMdBS47zHymTzLwsVAfvJdBx+/JL6TZ9CZDh591Xu/27I9W8gU7YCR9PtJVfVcd06N0SUuAlUCwhWGP9gb9ZvEz5FFHSjkyrfxDpa3K+jVdnDPdU/gbksR0jVrO3aRaBlcMdLP3XWxSlOCqW6RxBAiBwvs+1EFrgda/Z4hNMZnAdNOmOf5PAHd0seH+JFsOz2PfAU+BlmA405wsN+aF47J3BgBKc/Qu3Wgnej3QNuactin8MUV0dimz9WoArp+jOY1rmkS5TfU2nlrA5VvQOE32fotzJzqe9vNi8lc1J+2ZfIHcxrdgAQdY1BAa4YGkezZSanfWgdkMnVFd+Dd8DTII00odNwCAepW+BRdTrgcY5pwvbqoAEMP1Yapx33SwI85xhyC4ccC7vetQyWVL24ilbM4GevYq5WsiMb3FElmf1zEbh14d19PpbKi9Z7EwNsj+vrKUQVk/5qZeQvQ0+ZxNWsEthJDozj6SMgs+Rx/JmOcgW+I8Iyt8MilG+Alm7tJJAKtX0fBoXIEYgn5jD4uqYM0uOS6jCqCEwYYYd9zGjVi2OWmbPpf4Oqp0aDuDBeFQG5lsPcEm/KPpoXcemHomSBymvum2lxsB0PvVKVWC88/dZEpJxT3cm9zs8HKpLcWbciRUZxzaXTMKFyxEM5Yn94VOirD3Vn/E9Jo+v2c6mZkElWjyIAba7I0ys5m2Slk4RuRqsGlyOd5p0CQahkTuherg8Z1a3nhcUp4MBK77GsOiaD1Xys5f0mzzx5ovyRqmwQBEHLbI5OpqmRxn4hCGYD1lB6zgn+FFqhmghJeelq7BgenSUX6eZn5ejhdTYfGbh5POWcjuZeGIVeF9W55U6WMGM5KtECkVbZ3v2zEriorEBvFIm46UWBdjqDMZAoAARAyzgKCnBwp7o6npm8dt9i3vxaRHfmcDwDhIdg5rjbDJ0h+UCz1lYpeaLFJd23S31o8PTCZOtjMtM6xRBbcsPAszEHaXba35xHVLN1odF2gD+eu70ujsPbm1yv4k1KUSxHe8MSQLoAbd5+1bHCjgSPPzJme21TiXqYgcZCioGOAFPJJEmBi/aIURwQczFmEAn46j6Wsns2voIIhXUh38hj55fre2hjiwjZk+CujiBP+vezUA+uCU4j59Gqj1FXbpVhAcf+q8nu4YcZ9fm2QdR698nP1Ll3SiVTD4Ms2TQEDeW4eUJuLEbBdOhyyH4rNNMQfBB3mEsURbY/9eD8D5B/3tBvDFusdYQ36SvRpUGgwQwV2X1KRy5AxF9OlGbtZC0vwQhCz103QS69+Nkqkh2vxscp+HkYTOLatUQGbQklXULPxuUnhkla4RDI5QK8iHSCVl0ucQTW3pt1Qn8G7hJfBqH9+I4h4Z6SLMBCdHFX0eowHMZG95dNY5tkLer7oB2Qzvpvb+QPilJy1yxaSCF7WpMVV0G/QmavI9Jgw7Ejelmn/WR9BFzuKcNNzuVUWUDD5yd17iPaoy6SmlvaKJqAoG3HdvAyFbLkVs8pTpL/zdGUz8hqqmF9srbDo/qsQa8ElUaaexxsR/Jz9F65CBqbTBuu02/Tz2exjYuVVw8jApZMptGnve/QCDedr7NVTgALfBUy9Oc6va8qz0TPUhBdTzRDrpAaUBTCKOy7LXyG5JqWQYweq00afFxQM/HEjixtNxZF54PDiQj4T1OYzDK9UM8U/pulZumXXAUK1dS1WOD3rePmEJOqk88tiq0IMVTt87fflOScenaZaJGNMoN48kw6oIdaclcXD5wqELCk+/IkzUnqccVohgFQ36FEDmqN+u99yqwqmYXbhUmrZ8kfnzd8A2vlsAAfXt1W0UiCZOg4s52UTqwHJeydNuHBRgYtxzUMZQg6Yt7gIoK2rzVfibesqqVtKkHfTQOj01rKIbGoYHxUlZKGnpfvUZV4+hQN7Tp18XVOADpJmLP80JqHaFQUFs8lLfnzBdEkT6mXVa8u1l9FqC3qoyPjEXynbKBIrGeyonC7mBnG4B/7qLeemTh7Xb+qLnYCU4pykLmSTd/Uo0ZFwNgoB6tI1qPXd5wRo5v1Ioo1oiGrBvYGInc1sP0tx7Ijj1+zEkHIOIhZ+yrhfU1O63cghDiby+TmAQFOXSyJ+BPevvs/T5a3Csw2z2lBHlS6SXq5D2LecaRZ9dhkDAJNDGn6Nw6zZIioq/dxtYpFkvS4PRoYCuDwpgqvFkRuBe19WrCD0Y/bNOHjpfWEjRYqQX0swEae8lfBJf3mzRJgI9Krh+yTTZV2q/ox/80CngLWPAMctrtsGBoE3SXWeyv8FPmM2c7SaX67Op6/rkeeAXo5bkJztve6nbtPKIExldffoblckm5VX5q+iZfjUfymKg9h9oc55OVf+Z31wQjd6p+EXaZznd2/u2i24YGsg00el/rDLm0MsvsiEFu8KerGR3g2R/+oFp5Ics/VhCTRmojM+GI8uEAW1//dQcRWXw7dm2UorqvQ4Wp/6jvu5xTI5x9vevaB2Ut1a8Oui55Jp0NxL8neDVdr6li1HC63A0GHY3wbRMDbWVgOIkcXhzc7DOBQEXhLO0TTEaTpfGdPH68IJLe6+7TD/+pro+jxtbDdRonELXU5hORP3rBUqWET0QI7nVMrZsxJIIBOEZrqFM97fTExBAwo9bzBq4oV4MznKJof6QJjIwyOyiIhec8tRP9mXiB7NYSSrZ8mTC0ao93U2hh6SFKgl843nTE3I4K2G2PwVMOW2I8wG1niZnYhegIj/ntxFXbtH1FXhNqVkcv+qOrCw+Q0XU6NTcv3+CHmuqpB/ODKbpi3bTki/z0KFXZZS4mUP43R3gYFUBZsXnM+ePr1PF7IxeoXfhIS+1G8joFlMS0/dpratIZ34bVwpJHfaFEDpFOOM7a8j7LxSkSVIOEgil5++WwN9gBWSHLnyu3N1Z5W9j7f4aNBxn0vTdj7a7siTOhlhfxwODfDhydXPk6UcGXuPnz0BT1ltlg3GG+g9Oi5ppJKU1vW2Fzz6/WwKs25XyqyFxiDKV8GuWKSeeuq0kSehTKV5wYVwfVVcXS/rcH7HCWjaET2dKBsrcpEb6IVI/IbtO/GJO0G6JwhOvk9dZc/oYlbgb0CPVm0nOHvw82valeBQ1HqLIotyDuVhvlsdk1s2Cle5CO0/9AeC4mXHsdWfG0QOCpKR7qoPVNHUCimq+r42U/wIxqKo3c0klqrPP0rKrAgq5peNZWwyuguVrK4me0412WFoJ1hMxlG8rQ4C74V2liQLddXV/W324GJf4HQ4ENetbLuTwjR3eNfMxDCCZYNM12lhJRV+uZH3M7/qCd3fJrmZcYWeVx/eEYScANss5Hq8alZNfPfUPtmGY50UjoCAA2DnyLXRXVVQHxhDEfojtqRi7ya2k4/fv0st1Gpg7nZW4rwOMJdxE4i1gqwt+KU6M9dSvLCtVcK69Pow6cLAY7pYhxXwIjLDRNS4Q4vKp3DqSLcQ7iBDfnVVISDCCYfLm2aaoc9joTHWgV/U5aRM5erUOPJuzM5sHadPs2XuB0FK2uELv/Z7jPT/0ho7MWyeV+eIwOPQpLQwILaTbi+3im+6ckCHuC8HlETB2MmJwUs0iES9NZAqzwwwsYZnhR1iMjEOGjvrehHRNvoMMsdZpfnYnfsCi6dt52kd5mNPxZwVUd6v9Op9xJVe7HIT0vhwGQyaBEJZrY1XFLT5NQlfShe/kC8Z1MtYwEW1XgqnA+Xv2UWMhy925S7/G4DO/rwJDnOH/nW4rLMbezql/MUJoXhpsdL6Y+RnqI0gWu1a6eghS9vHRhTDT+iUtlaaq/3l68h9sG31trQ2j62Nr/pbl0owVp0Gg4UCWfsymB2Ivp7dh+klXHceBNhV8r1iS0u773yIKxSdWuSPv5+zp0jV832S4QReFS19Gb5ZS+ZUGmEdV1WiO/MLkp6lwvdKuJBHWHCI+iTeAaqBJc1IYLOEphuq0XcQfu9Uhk4uTzlSdkGw98B2mdRCV6SGcYxaHQpEtiIGLkvsgMd68xzRSHhzCArra9uDhrEg1miVUFDx1JGXKnYsxuJk4VMuOcjmVbcdJbVtp4C2cDsEje9wsYG7dCxODX9cCxqhCFQ0NLvHL/JnhgZChC4kQnEIEAGOX6bO2ZpcXVthz2cJKHf2gy+K8WPSkwUQ19o+USfrWiJaJlVxHmMmg4KKj23ex08moabSn4u+sQ3hfzGbb6k2uAd7MUjgQ7axAWuvyeGDu7NojjItw2smRR/uMzgzuCdcNt+Qq+sBPJrw1rcbarht04WS734OFLxjlX1czQ0xcxa2tmcEMM2azza81nJ0uxkHeQf+m0Dg0UXudM7E9ZwBNXJfz+IiAcybqr1PpTPUN5cDzp2nkOVclDsFr0Z0qOv3GgUZ7hWEVEq/I7CpaItOGuAhI4PRPSNDgSECsXBRLVIecR5subkeC5Hmv9pR0kvB9IPQQ4A/pxbaw1Cij5hmW3BYGD0FSfG7ldmukjKd2Whh9fCpLmZezk6Ppp3xhv/ZnMCEh4+hs9WVT1Q9D5Dy8uL6rH5lvp3crQs0Pwys82GKeCzWxe/jikDZi2NuLQMnSgSXYiC6LMyyIRX17hX2G9nOmwTWjHFppX7oIepq7XFke4z6ao/qsROuC35xyEEpiWv99GcyYCefua5RPR2EmiVV1hI2cl8wJxtyf4jvlN47I2BmqP6bHpsq7RtFZrPrn9B4VmHBvjAxoQ3xKMKFyeAiDQbxKs8dznv3tAvmCm4phpd2PpjH3DCOiSA5ZckDrYgYCjjSiBBxYdTXj/L6QTm6V4qU7Qzwvw0tCOHgsgHZXLkcgswrCVKTp2OdjxQluW6rzntwzqFKg5Fx1M18VgW3cGh7D7iWBwczFnugYOuTvUwLLIbDy8SEKxRJ7f+hTHrwYB1F19ekovDic+1AgdkjzDbRI7DNirio6kzYEuVb1y8Zr4MDHTuG80bY4B15V1A1Dle/hIi1w6/iudeaSmGc0vzCjPF7jDadt4QGS6SG2ht9NxQc5F7B2WsmkarnowELCyid6Q3rW81mBYfIwpscq2elf96gGV4R+EN9EEEd79+dmmdRoZIBatej4gwCxqPKSSwMwtclCy7GJUM+zVB9mtEFeJAZGnteOW4SvodAamdABCB1pZ9sK0oEMGrx0tSEkM7tZ490H/lQ/BS5R8R+Hz9PqCwYoYwz53QZcomSCIhWQDdSP8pnv4sINY8zcBBvIziHTmbMbvp1OsJ15GjJINLB884dM9SBczouxIdwHBAQ+igrW8UoPqMHzgtlYdq1GJ3vNv5qo4PTY/6pXNB3oTc/a9nFJm57XPmOrMbZvuMvH32azl207jkORAbBZw7ImQlY85euQFuuCaSQObKIJzmBetN+ob/fARI1Bb3efA5+YWpQsOro0PejEu0mg5EWsDyxgYPvWFWXNOMChEoFnBleX0GMPaoX3gz77pqlffWj9kN1a+t4Ur468Sw749dA1DI6WrhgcngAVhgKyOSHIHNZvDy+Bs1cxRngLgxpsLpwD1YpSVU4hZtEequjlPdTMjN2qOmzWXHjhhB/CWb+Gmx7mc4iOYuYc+e36Bgj9LV9Kavecsl1XdaAwK4vIw3HW+XoTaLX1QtRrknDcLYZguBxy1a/bUjIzRFHRuBxQlp0mRtZpHJQl0TNs0lJs4wcC3XcRUrY5uiLTWIEUJkZteWIUjmLVShki5PweV1lSACZ8LInrX/CKQAwnVh79barwUaBP0/QRzJ4fa0CDMtg+rKxMdMZZ0Exid81BMO4EyH9VNZSp5i6wrnwDcRRSp0bUhIoYkG4VLSQhMb4BXJpN3fajyKoX8n36fV3iJQIBfuvNHugjgmnEqff2N83NhpFtdJtlvY43KifDIahl3rBWrAJXgJ5FQ4LGSVg3gMsh+GZjWg0+JZrd3XuCLJ361po82vBDZ5YyA9ukuM/VZVQ1AylC72iJlBSaV4eljaLNeIQFtpsmOsk5hoV2eybn6OqDef9Osmubcmc7a4tTFioJNZM2/4PiphxuejuBjn7niuT6mnOqsgZD7kd2WSywBX9dd3+fIbPcQFnkPgIUmN2cxeSAOaQtS+ecqMp86ETlSh7hs9F5LY1XYBK5xVvaAh+GSDQoCPaaN/y19BlAEtY2Lrqcjwuyz/jOeNnL6QDXmJvdC8/43ff+nE1zeaP7QXKvTjxrmzAo1stTbSYbfRgHn02zv3zQZMTXak8E5wQWF22oPKzSYyKQhiZwi89CPVthadpkTEq/GnMixSNnnbjFXszXGIcN53cwUkMxy0NpmPDHduKjUqJEqf5HGjEu2zXd8oqOVjOHQ4DEWRq7CFKCLQyihc9PV2cF67vMbJN2Hxuok/h6Dqyq5uENRRbwF9Bd5JaajIMjcl6WuTdzSGY9TvU5XLMtrZyb84AeFph+MqwxO6MvmNnAk3NIz/tY/RiDMikwm0uPaxGeRCvJK4fW0ACIzsKXv2sjhwsPqDqQkxlX7fWa5PBjSNG7WC7wc0PO8iMUwBMDD/FtMHKtQUm/7hMMy7UvozzQs3qHbz3SW0zkareBmK4NJrdVASzGhm5FMRmFMXscCwLJhLyqLjFWgGF5xqxJkAh2nFkp6Bdoi0YrSfYx1ciP3wQ7CV7/559sqzpR5wMu2j6NYRKAfkMG+llhf+MVYTTJWmoKc/qsYbw0hzNcJ90mvgaF3il4zktGMJxxJv2T4oxHHOlhmoDEy/0kDKcQpNnrerQDrJcZ8XXmreELGRYA6W/poZaPtUhx8cVOICLYHi7bFoMWoh8ktck3hLHwLKzaCLGSxJWUxgmLq6xS1pc+5/rzVX6UWahE17tFCCC8Sqc0z4vUntYeYwg8fFMDLKzQGBAty87mPOFpBghEPDq8WpV5m9FI+9Wbm3LWyrg9eyhUWh91TzQZHF4YNSzSCgMrtqu+dv0/mFB2nzkqYbz6jmmIU+PYwt5BIs/vQXynJwfDZxm+fBgesNZQaTHNtM+HAOUhqwoA8txhSwkg73NR2za/2RyoVKMEvJ7zCNGE/p+qM9e1bcmK6K9slY2RfcO3lIQDRjlQElUGQvw7GU2umddB8Hjv3nP2XitzNhEjWvqmooUkazsXcaENFgTXhknQYnhZsky1eLS3AvAYrdMpozT9WlBafWKO/EOzDsHQt+bDxcOhtvMYNXyoPXaii5O1Qu2dHSDzJhQtlzMUSHtTlK7bsVO/L/9OX6TbfB8ys0q7Fi636wUeL+waCvWq3slwQkSDe4xFqfQpvK6NXmqcR8dnxFoDhFg3cZP3LrAk6/q18Sf0eD5YdGfqG23mH4Mv/lLqJ3JEiy5udx7OLO2+7Fn86pRzy0CNqeYMPBg3Sxd2nEUKUQAWmmYCPEs53/bmsn95AK7/ur9aBGv1KPbRH7eYW3Emm7MHDapucD7potAdjlvOBpMqqVUXKfY7KEkdsLplaA+UPYObS5wCRq1AptjmNdXXn0oFvRyk+83wtiHMZ4/9XHLYsWO5vZvWCv1GKhXV9XST8s9wrK8AA2uGPAupjEVjaCm6MtZdFmEKr1PJah3vaAKiwXgt2Zh1Moz5+rTrNx7N9Qcum2LRm8zC5DgxRTFJHzrJ6bKzx4oB1DTx1+Qm70fM3Skab8+DziR7imB768u4eJpdUrNVDyEEWb+Nw9VwfDJr1Got8jN8/1oKupjW9UkzJkgXLUSAuXOOS3eK1lU0vuPSOf+qUQVYlNLovBxcLPz29xwmigT0hjSfMLgHJVTSTmjLs3reKZs4GZH1OCS75nt47SwAKVrHQuNY10UeMvrgWw3CIL//sFlWJoejfHDtx1l+i9U7hUrJrZx9dFj3fzfyns4SOZWfTQALHn1gMYVLp8/by3lh54hPisoB9mmAIs774QEq9oGUvXrpKWgenois6LVzR58vU59q+YijPT8HOVVqakPcQBM61rFqXDy2Bxfe6xvwMfLc482y7hkM6f0oakvOPaJV5K4aRjFaiGbA0g0Xx5lRH10kVedTw7n6sE8l3hB2FK3YmlFQ0DhNgOI9aFgukAdxnomsFX1xmtLOnnBTgUolkc4JknYx5xkX/sa310IBTy/45WOoUIzBxB+bQxrJCQDner3YxMJIq6V+fnjP9+N2dExlSXKzzfK/mngBBU/tofGh4nuP/sixuE7ej4GVQOOyHtcvQ4FAdMB+Tz/ur1lMxZetVJnMvzEuh9hVLYOYNvKBju8tJ/NIaQ5q5vgM4Ev9/Fjst8uz+tTxo4xVDdwLh82x+iWamCz1b45diUma3K24Y+037/EWjpiZMuhmuMwpQhjtaJbZJmB9PbP/Hchmedav4rEVk+DxHs6dvgSOrT9FeoZFmveKCehQPmWY0kCcm/qCNEWFhY/a8XGVtQQYDi+Aq6mM8vF6PMB3as3xzNzG/OmT5GsJ4R8GwP189nIcWlR7bgVWuQRwZJWfBoLj2Ed31rKp3HjnLGrWMYaCgRyeAU4of99mOMq9ZBhmin1+US7EVUc1wcBpBqmKbXPaHXkEsHd1w4JW+9xdZnxByKZRpiPDMf0Eb+1OblgaFByzHUvHq92t+1GEsR3NkvdWYwG6DYNZmhclj0MEi+2mgk2wvk80VcowPLmseT55KqOxGDtfjkUsiJvRDF/S3CqSy1eHi3CKO6WsKxLgxLafLlpmJs6VwDKaYrFzBg6VS++j2OyKD6G2OBJZlrIV3iM0PPB494sWJtmhxK/DQKhcVGlZBc2MyxrLaa5rmP39+e0o28eNA9Pz+uRWnMYuxzJsyjhAcNyiLFBc3Gr9pgq4JXIj/l9pSsyOY/6rAY44c2bNr+edpuf6ffMSDi+m265xwxGZy5XVyzMCPBoEpArh/JhlCSnH0eyKAf2kLeWRXzCssFR9RnqKCe3X7kamd4JYS+iptL4vHGhrITevyOF8HFNBwFOu4FH0pRd3/oaqJOZmtfqUWu3X9M47sXUyBQI9YJOZ2RiWXaaHB4NjjE9cRkoUCEGncdHBQopsTGDIGOSQ4f6TQoLkkDxvfPc336/eixnxROypkiz7Zj0Q2TmrQaNQjZa7P2oXEs//FBlB2jeysZ4vkaIYvvfdGkymXs84o9Eyyvdr6JpMMsK/HiCy5FR0l3ExZlIQu4fHzp45ma0o1Chzysd5zanC2reYaSlcTVzyU/9/vknH8ontdL6FuX1p62SeBoYx2gHaXS8zwc1M8VYouY2H6thG1oHS28PzwjClsaNVxmfLLMbviMTPxVPxtLfDWYB0TGIY6FUOCn0+6PeX4VlMJb/pK8PmTafbErla2g57JwtmG78M/KaGgDGcugKwQKvedNT7aFDZP1Gz6eASqA3KlOTBII6CrEhnOPK2dmpsw1D6Yspbpq2t2LRYYqxCH684JFYyixI/lhm3lA28rD8r0jVLB75QvXP59IFQZ0BOp8OWUQxhUslMyM7f5w0PLH/1kZWZRMdy9gDYiF/o6TAVzn5MaZ5JTFbJyUKAzGHD7poH4yocrKGa1QXUffK1d+QIQ3bwVqVutcUWX/60tfJNyKdTv/GFdF+JsxcpJlkA2kmhMWPlJJqSnaJLGP0MxkXN35GmqEPLpeGvnuck9AN3MWAc89f6Ee6dSljaORW3k2d8sZGEw54CJH2ZMIh+aNceWrPdebd7Qn1LscwWzB6nIsnX9/shXRCzrd5vzjzD8mr7zn0u7dLuj6M4JUHQP5lohfS2SNCpOTA8qUSR3676fFBUSUYJ3rWKjScBE+samSEK5ZsEynoikMi5Pd+xdCx8dVeLAT3mvbQkfhcjH7SYcZPplPOzfoCMHwuW7+LEctCDMM3JFV0AOVDZblomR3TzVJKyGICVXj+xIz8+ys6/R2tR3IKpQWkW5QwPXOM6ZbdfGPxRDH4lURdidaXVwCIoePt1mCbGSvb4fbgJyvQ3awA0+J1rSKI8BzTZCPqal5oExR8jfpr9TugU7FbwkIixyIsyd83ZGodV5O/zb9FifhjfT9k0rst1az2Ga/RY4Sy2a+N7vjGWa4ZhGI7eXMye7rcYD9q0L1S+73nEgDjb88oYBUrsluRVieFbdGeodIfWCqrg4LJDenvvopzgB9wt3kJKGMKUofCqRw+tqEGSZrfmTRuOX5zhW8My1sSqVqp53cye5e1R6ucEkm91ZccmDqKi7mdDogtsmX2YfMnU2yRt+zCJeP88etdEgk0jSBj9A4KxI6xB7ZFyubdHy5t4G6L2TLqHcQVjh4lqdV/XZOHUZUgg7BDl5+VPjLMJX6mCOjjs3Lt2B4LbzWu+ktnaX9+JM7WWh2WBUCImLM7mGLzEMWeYgyo50DyPHbyATpY01VPme6/LqPLn7YZ+asUUgJtUas1P8WzxR7rersuPSpfJGvArQjwxR6xWq1PpyLWOtDm9e9148bA0olGedt8QFEjAmIylOBgscZaEWBavgCa7w//R6WNvTP/J8g0sKy6yWigUXBk64o78Vx664sufJ95mx6KcvG9Go3K9xomCdpAgpG3AEnGjOCEhL+eru36Ybp5TymAHHg7zcZ1RvNaI4cxWN8i+7LXH4qG7nxulkRKYwphNij9m3z078YwRlbWFLY0k/a1vU40r9f4sWO7ukVhsSBendhaATatxHYbIEoLMKnO2L3t5qApInpLQ0Js/5etkxY7fJ3urt4jcwhOetOUlPgq/NthWxQQt/r1723cFoTfWwtncAgbeqb+/eLAf+WffXBohKTlxHKilfxZrcGj7zvxhhOXgqZOCHGm7kGVcr98kP6hiT64xDHa3zOxO2hdYDQ7PTPXs80aLf2cPLPF4Pb+CeVZvOU8L5lAYNLlltEcLQamP1ezWQBavMX3uUctBm2UrdpWi3ikxgWPhV1eMa2i92jWGDNT6oATo+0IMGhgAsPv164CjWO2VArBMoEGnt49rOGcIfGm+sYJPwwvaG0eIU5lexrX8wFhSSyIZkgB3lbNsa318RxX0gATeCZ/HeB4zwpRgzR7LNnEix9fTAjBg4gGqiJ+LNUTzJ8jUvPFwqDDGYcI8ItNU4JCZGE5DytLtsk7Wk0MWyU2fDh4F0cWjinqIE/EQpUG7cwqmohiX89at+NerrEnP1pfmFnxV53xUfowW6+fdv6o20Cwf0A0RSnj42yXJdq5Gzh/wfBhvSU1m1IjlISv7jGL2PPC+7TjaI/CgbdclmJeZ19FvynEr9f1thkLNvmuVGQjPppz5UBbot+uWzUkbRQlzMzf0JdxZJF5w8oMyWpdZo5i5VSUadQ669ALJD+g4xG1CFCe13q8mzyM41eLbUL48dxWDdW6PSBsjakwUwFj9OQwht6QN7BM/M1DIXbckL3QlQ7RozyWqHdqW3RyACIHmfSIGlz3HkjFi5q57bdi1+TWNeJc2HYPb6gTp2oYU+lVmoWh+mas87LCtH7CS7sn85dfRhQYVmnR82DqUZzKXNRXjsasstAyOV9OkyLBFANzchCkAdwkm/lWdHBtiCgMi0yeUZDzdOfw1qsedZZ5UumnM6O/OT+pkL/yxrpgs/xNEJGzL2dcfdfbJLw3Gmj1AhziFocc557RfK4gnR/kSw4hgzNYB5CvAZNz9vWW516PcZvcxHU46o+eqw06TUyxJfpmVDgnBrXXL0Lgw87C4tisEDj4ELeI9AELIInST/VqDE5dRyswRTx0RKSZD6eckdsXuGq+cp6A+31PC6AhqoOb0AoSd7CDpygURzM6W31nLyCJC+0Dl9aK7g7bvvLNW1VMUjpciKzhtk+MOaFSSzJ4wBPQF57OaN6Obfrfz/1LdCQIFfqGdnQqMQZydTe0as0rdD3CIYeNkWegMqMrmy7GIb4QK1oczMMrPBkfdEOf3WD5VNMKGNz23xxCP1NSCcclE3KnTyoRt7hJqMNSFptfevfjCpTEZCHClvZRi4ybKckhtknhVequKptgeY8+xTW4CeQS/zjBDiiDw+ZjVof7Au3S6W2lVKcnyAZ7NzGJaxQAxU/8F7ez45A1sEVIfD5eriM3SDRWsXi2kJjJV63MjwhHJTnpM5UvLqOW/uFzaJ7/iaQI+O/6lyVD9wBp0rZxSyRmPvI2NJy7XKDis2Hd0ILE1sQ64pr6Cd058Bi6o8TXjjN03x5fjv76d6pq62KP5iydgoGmPaQncMquUPwGdFHvMNOy4BONx6Zr1zJ+YHf7VLfVvXNzSy3gkiKl/VwTThQqnglr0l8ann8+c+Jmc9BZ5NXkC4PygfvMbwyQG99ZntAtIEGjcRSU194MBfOSnViIimwfBJG9T72Sjt8MCpGoyMIwqIEFrm8sr49kFMhgBxcnKdtyjvNb1BlMfHwNYbGNwMbmWZdaMC79O/7B0PIbQERcAuOaaPkOrMB73agI8Y3/bAEyaC1/irkzFTppKC903YwO6NTtsjch2QrWdHCO1m4NAvlN44eYqK0RhuE+ruid+wlTrNXULwz64rSXlOQysfcdMOJXQL9Kkg/PVXkS2+hd9VD57+OSMVeiHTT367TagPOA5MP13rmXp0Cnw9wVykGKzv/8El79K/MtFXT/b1o2hB+XAZcm8hAbFkpzn1auBrDCGz18FdZampw5Jw4dBwx6cjzxvC6MmYgdPaBwu1Yv6bKK5BSycJ1QfD4wYygNYRIHZsh+Dl9J8DJvQpDAHpxaBCqgCNUE0X0MNfsvPDEbaQZOt1d0C3kOohTCX/SJTKTwaUPhxp5ccPgVVouq361v5NuTcuMY/KOhkbQA3qxR5p+0r+JmdQXfp7HJL0oOrkqBqVEF3gK6yomgUWM6/lwaOXArd0aIpgbdL7fC12FjlLwaTdusUWrENf7ghZkxR5fObp9b/cNn3F2z9ox91arCjxDK6IQxrOE8u+lY+bCN96QpsMMcW6p1S81K+YhS2bBak38qdXInqnZlDidAkdZqSvjQNHhtgvX+YOPJaEQSqVgRNAlOXqq2ak1GQb9uQ189+jayToDFPAbFBnkVgzYNOfQzFRVFB8TUJnESCMWBoWp+KYr0DIFw7U6IYDYiA7QIua1bf++wZzg8/UQ3dpMS8QthHiHvTIjl5njYcTuCRA14PzEnPjcJTBKgK269buik4mRSrqVp9MjMzFih05TD17vzEF/2M90Gth2cqdekTHUVdg66u9t5MjCycD6YI+CcqOe/bSqA6IltOD6Cmuna5lvIVU9Pt86wUWJc2yj+y1lWQz64QiJAmXdIKMRgo9zvPR4eDsaRARKrsNtUhoY6l75823H6DiCuXG7k+7y4BHwx6MbqUdjGESFvZiDyLSufpHnccipH/PPeSntRrD0qSlyEp2xpnrRb1mNJgbaMifjC4fc7bZfJM4ejv2etPrDxxpVuNT7zaEIlZDw1+f0Q7ZB8AeAdpvoWffN31F1f4oLrzP1I5HKcIajH+Iac7b5fDRHsfii2L8Ii2ezCltAq4+OX1yynqYwOhWrrJF6OhMs4lygHPp7q/1HbiUKdhorB8ONzCJxyDTZknt4x3wIEGL+yNz+HHxAF+PNOk93liYwsY8QFF+DtGijNp9F6f1MOnCFkgdGKFOhw/Ktwzp45f7TZElHTdRw+amGyn8eV6ExQaIDpcGqU9m7fMlEqm+tT2iSCAeDvNtrX9eJhbOBmzNlEfvYeAPc1hjTbLJL9Bq8AvBgNF9UfaQkJilSLogSoYvosX/8LsWdkvusOoR0FKMfk3gopitG8Uxr6afrwkcyrzEUvGklVYGY2s77qxr9axOrfGu9etzGUgyzpEvPLEwzAfobPJcHiVkfM5A5HNo27HPEuC3u1vrpeYBe7+eVW9VYVDbefw7hM5UPJj6eHRmiNBIzOBhfFJfkeg0mp889r8Llrqu74PBeqISc7wsuuncwIaGJ1OJoXd6u2KqfJ4+PJQtULIMBQ6jU19sUS+j6/TQPN9DnLNp7ATvgsAnT31slr8FClcsYU4BUGzukWhQ/oSAkls+cpU3Fkkw3wzHGxGGjkhRco77iD5NwucQ1qbVie2UUIshIp77qFnycldn9eUBGg/Ov7Yqvn+UHDyGT4PPfucnfOlNZJpOFvm97cJRcef2qtnACjjxwPdZ3bdfuIcFEaEV2vsmzq9lWX5tcTKOnuyKho1nT5olJklLXbRw9dZF6H6dA5B6hclVBRDSn4tS2HMcK0j/A1rcDWgZJxJjeoZduc74xr3SaPq/ZSKjiPkdt6uRB7HVYL+tpy13ojorzRViTcAVymv8GrMf4bcBwF4kqeylMbsIil3HLsOBh99O8DEqdCIZAC61fN4bOXowLPaXr6wkyw2SBDtQ6pMqpn8CKfLIGzskSRQ7naOVrmmHShXM3gk+pw2ESAcHcXoaX+8WMtaTs3m5jtRARbShMKhBN+IGweHCmiQYn3Vkkp/DasuthUIWfjMb8XGzlsFKwdhjIcjisd/5oeAVPU+BL0Sqt+VH/ExTHiVEOcb4yuqan6lcmhHoEUxz2WS7zO+N571GfbJp39QVhEUEdBP9eHquxErroWPjSPkb9mGykdRo9HPaQ5Blb5t7Z7xXKcHAilYATFp+xohMWzBENESheTdZMsS9FUsVUYQMrlqXa94D/w6yVfW59HV8NK/K2tKhsFeOUijUhkbHwcR0AGUo4XX27BDG4ZJK9Q8Q4sFBicDJo1S0uUPUbw9mcvFoHcI2D7K8KZfBFuRbjPxHgpUPRU5C89NMOVzEUEjXcrLmOLnU/LzimXHnp1X3d2Zbrwc9gH8rta860qfENvNgA5wJJrJzbh4B2Re5LbDi0bcL1vJ88fNT1suVd3W+pJCQtwBW7JdRSjio58i3tPHrLddWoROBRckG6fIHLe1LgKa1nSJLGyolLJJOa0VHE3UJYLTv1cITT/RPJiGUzC7mZnQa7OQhqaiHS5nOFpFcN+aj262BJgd9SJ6AXXa5SFTMzKCVtiPPNPJiuBvMq+7ej0TPbir+fakbjDv/PUndaNkPaZVP3cGkyH3Z0mQEeqrpbfhnRANUr5xd6qFRMz0yGaqCDHfSwlVigKYPPnFWIEnzhYzh5FDDE75fjU+dnfK4wqQftowO2UARmp/rumWbld9NceT/nPcbCPJ9s28xf0ke+GG8k9fP51JedbsBDWU9NADuGimzjeqwPOjtPi/WTcyedggQTrSwaz4fkPaqVkSnUsk37w+RvqGhB4ffOHrejlIWGijX1WhvJh5UuYzT4QNGT/rng7FI01zRsgW0QZEkp/XyumWqDMottFNo8w8zZtv0hTIZoG85lRyPozsRJVkMJ5Ab1nSSavZxkcEAMx5OfmAc/GHmf9pNljvDdZhMIFY4cHN+xhhzswKGeNwqchyBE0HxRZeG2V4aejXgLPQLQ7WtzloEJRN9Ch5NyEx8/ELwAXE7sLpdEus1MaNq57h86bt9BhrBzdwGHa2ZUUtM+YiKsE2w/JNBqAI5aT1u63Qoa8H1YLxBT+jT/KAabkkTZqlkehz+X7jRiNQKNOd1Yvl8/bRq/Mu0SYbf++SU6jEl5U4ksH3e+qF7YaLRK45e721amHUhbYhdHTm+cKp8QHkzri+IsEKJjJ2sxlziVzIb09G/y6lUq1cQilEjQ+KDb//7k/zwSBm/KC9G9aO+BP8ulO/HIK6eaadd839Zq5OLEM5wL9GCRzfkaagHU67lFsFrEG2LVaBwJAflDUfP+fAhGZA8K1jMNG8niNYkfakfJV/fEYwZu8L43BNZAuTw+UzYcE/eHs/YWSJB8t+tBPk6KOFbyaQLVLdMQ08f0i6w9LC8MlzkVrnUlRPfO0IVHtFoOK8PRxptILeRRqNN2U9AB2cLdhCdetBsuZlj3KtQJfWx+Op2FXJ8J+qhA0let++bMLiwt9Yw5o8EJTqMGm4N6n03dC8m3PJfFeGCUtCU0hJQSj7bvpsUbIQW7m/Lpzt2buto+E2Xlm1tkjXWHApXfpKG6GBxYlVVsxccMTBXjkwkNMsY/7KftZ7wJpfLY8ohjDXtrBpkCypo9PIwtN9vWRzmizzM3FZ6mCQ6eNcIK4yQmUhNQcjqppWdQyKYp5Ak4uN9GysKepw6iMGI89XyUhg0qC7OH3Kn2iUdUq2CnDkfsjf0Hx2pg+O+sGyMYA7v55+dwINwLqbhi+S7mKknL+3YTd5r5btDwvsZ9880ZuM8L15M9JpYnnUaKATULr/Lb1x0hZtOm1NXfQ/xLwUC9hCBP2ycAfqwAyi2DlZknq4Jt/iR0ItxJZjpDq70ieL0WFQ3vTrrmJs7fkUd7thuGTwz1MFqikZtxfcHkt2xtGn9UAWoAAeb8QkvIGzPvkBgIO2kPRoxNJ76GaoiblYHPfxJKE+6Cq2h+8galEV4qWmJbAsUVCWqB7mLySRj2e1i+0LlGPKLtmkkTvcdd7QDejTm7pyviY2C2qwxok/1xHDcRao0febmMFtK5Tj3XjuYXGH+wcMZGFMw6KJ5wofPy2N9OaQ980M3WKfJu71qVOwf5tQnpbt3Dn5uy2x9phDQvlCZsl+QOn4SAtXWkMDIhDguej6Dg6IXaDO7vLz8hloHCNa31J49idSQ52ejbO/sSUo2zHXTPBrjOdrtyfgv5KdprgIZO9MSJ02GfKH+wNsPqTAa3P4eqPgcMbHzfjm+aQCV51AEOhoRYf16XjSWvAS5y3OktOByDd52nm6g/C6nEfJdGUhG4AkLY5yOl9gdcxHuj1g60HTzuqNDc8ol9FMcPFE4UMtcBWS9dOoc7cJKd45aosylLiye6KxRVGyAlWN4uB8IjhBGDWe5wERHFUnLxyDGRr6Waue051EXe/1elJkbg7PMV6OpYajlU8Sgmrp3HM8e+kwAKS5fpsZ0u0Aor2xAw6UvYYA/nJoWmAXKh8OhJyWU/caHYAxFZYdp+wbd0jjtIcavpMUJVkWc9gF5rwUVROmh/MKhvz427gTct0wwJ5fPtWWdOaGqmT4CgwD8psIoQwCH7sSUzC3y4ULu3UVoHwzH30KMByPgxrjofXEOuPKK7FVXRRJSGN2KaOk4eQng4g2JPQyq/vmYKoOFNS2cnLthG7q9H6csWOmcnM31yWmo2I5B6c1obswMAhvpB5hslhzeIy4AVcFeu1dGDIFIKZU0UGAFNd3x8xJfHcItqNiTg3Wt+0nNbYwJc2FRvWy9lK66RDFpNMDhM0UdhxuzQGh6EAnjZd1SUVIZMDzNtIRo2hbzyRhXinlzcuk2qrk8OtiPEqhF7AMNzdstPnsJbJj2osppKzi3+Z/MGQm8r+Yh8L4RMlECDKhx2mrbiIbtDn3W5KJ5gfidCR+EfFdomsdyyowUhhH4NA7CYUG1XCsPZTF1tNmucYJDTK2TnU5b/BGufCbcTG6nGsvn+uLOjfMfpthDjgfWgkLLYx+N95v3Qemrdie0EhagkZYqrJ/dpQ80BWrHy2fFLDrFnCX6+vmTlwSpBvo/OFH5g/RvDppohKtfO8jl9SQbWYRS11PYPyIudRSyrXmQOzxDZznKi/1YDtTl1pfvgdLPpRjq2W1GQBhM7ypdQ1QiWgxdcM69MXOMMXAka8xVXVj5tuQOupK5Rxa56Q4AP0nKDFyCBIpKSDA7tywWRpzCJ7OXathEp5bHOTni7Wviak9TCA1o6ppAftNhtHuGc7iHxyXjJuQ2j66bGvPUVcZHgyihI72wekwXML9JiZxZYNs+FLcElAW+ZZtQBSRBbQN+MPUY3+PUCXj7o/dLyAWan9EgqL3l4QmwRwwQ2FN5+e60AQZ2G7iexpmDaK5FS56UYU7kEsq2P2QwtBQYDYF4Js6FyXQPmS1XS7E6Rw41VP+DRZBk7y4UvkUZ6NkKsCytuIxYOHELP6NzKQbCB6N1eGuAQXq6VQ4NgLGos0Y55ChWlJ/tMRMtEO3s77URTibSyRqIt6OzOwIyC6cPVTs6xxShvOi9v4YADDBgDwkaZzMWSqvs1XnFSmBdRtsPVpu7ahIDs35OcDVoiJ8imxd15YmATOP0d9FUZH2+7xtAvyg/BZhXpiMxsnp0yNCKTzVNErIlUmtz0/BzXO6jjcbsQm4NZvnq9zCjyfamwt10Eqb4sqLqNUwC3uNwyTdsKUYKQNZWXYL0ou3C99zREwdNEAQg9S7Demvi5bLEJzl5/1uV3hfWYN77MBp+neGEv2N+29CiGIzA9PgvnqKIYh64v0OLAqeg8nGDQVqcffANFEUhhgbbkCNRWO0jUYbDEzDCT+R6H79HTh4zsFVldLNgdFjBmcBUaMFKGz6qGpJ9oEV7GaiXATN10h5cbI5d9pPwyVFQjzeeKZQ2jUwffkSUde1/jDl03V6nxgmptq4y9+ewn801OelEm+PfR/K2qoIXXp483w4o5R+UAuSVcZREs5ca28eaci3mU5yuD10fzQPSRd9cWaW8aYnToMya+0fOZYoJs7zI+usFivnMOPqzIuRzeNLiKI417tkQOqlUsFi754IKsGdJk7kZWGuhSYVmc/UE8qEdq5H3jZlXOkJeuCvUl/8KyxEeFx285OPJQjUP2N5zYUPlVvOLfeoghyIFZ7eRuyPw9s8JCYAmCZzPamoYquRK+nOf+QVRiXAH60LzBFB2ZXYmIW2xU5BgdRuDdp51VsI5aDQcxQCM3RqwfLtRi8uRa0Onpr1JG5iWPKwyqz3B5VlaVZFpkyu7UmLwLFL6E3ddhSfi2eFlXdANM5NsbsciPRhi4TVR083zU092ofFvUEJhh+a9fzQtJj9Vrilnu4EcI/ht18sOhDvk60kEPOVf2FAgwpvqjJDBwecH8fD53hylhIDk8llXzYloLajdqwJvYrJlus0/hvIm8rm1ysTnCLPKJ+YCkRHATS011FA3NQpTmWPwqNdKZ5W7aNZXg9DDk0zFgE0v6clj2cQRvhbyY/dtki2mUPmRn9xe5xABSuT3N8LkfsZaoxLNxyHNtD+qi47Z2P372Y4xnpGzHRLY4BsmtGg1heP2VwG+EInkahxqjdxcT3iduEocCtrK8jsD06gZjUsAhEAUeeSK0jM0mlDlAzBzGKA3U6FK9hNI4z3YWozcu5hVbEfT/1RBi4Cz1cUkA2ghu/LHUTWhedQMBUuecswKOD8rZzHnW/X1jGtHbPi1zAhpD47d++nz+tTlSYtysugbfHxW6qGx811Cpxqj39+Q/rQ0dC/2/LyBhuJR0Ad9CkzPX2geYSdEI1EfWmICt9gmSY+C0sQnsFpWn1K4cRYD80YAMwSyedcEI0W9ycSzHaAJ8Weo+X7FCrjXsHZ3s9hDAJhj+ej0inF5S6ZWkXWerZFDqW/6WvcD+EzuaMhpcUPHEzty0Gzc27dgCIazs+VZqHMYLQs5D3V0bIs286h7IVubQ5XsxgJsC3e7fhh843EktV1OHuANN2cQrTP5W4TlcQEgh+dODpgEStAK/U0IpnqNrFWmnYODHBAGSOWSiMU+NFVYZ/o1GDab4kBqY/wYhGoCfeXeksshXpNT1/Ulff2DcmgS6NeCoRxNT4/amC+zol4w92fqo+FTwt6PBRU7r67c1f4g0d1ha+AYaqAWl5tI6wVCxfX1dFygHOuBkdUJlh/QrukCwpLDu/PUy+mwJTuFrYJqB0ycbokvAUTHm+ZFXXLnL2sQgDg/ALM2KH0edHVX5Ds9d/g3eZwwYpJlEYjFvmJNVsO/S6Gc6ZmGjUErE6lJ82qKVJENqwV6nlJAOgRQ8MBurFLri7ZfcBIsa14R2hofhD+oL/BSYQZzoUMFYcveaFTslRIH6OVb7qlOrq0WaLl9ISknX/CQXcfPfnLzFAWLuc6UHyfu95kg+/2sA7TF1Cl3LHuJ1kRsBw+uxL9oE7gkuSGYuIH2SkSCWCzYQTFed70kSjBl5GP2scOOYUzPWr54vV0vGkQxO9pP9XTZmrgjocXUYWQn53n0k8m3iI880V4fBymJPsFLhDQn8flxxipvFRgdJ0GnX1+vDNbm3Ak1/BGAe6j1m/rDdkHY0u+YDqq2CKlBJfrJjLHKEwACqmPbcUOd/gFgvfD/4MHVnXlhJfDMbr2D3BOjUW5Zb6csuNnPX2DDldQGgXu6NPX72QntTDH00CQsT0QFBU5QPblbPVtXANlSf1xKqGcyQ6vuQFvzO5bV4WTyc6sT0wLtlQYxQLVkr+Wlzi/ue0WpCJw0Z6ipS0ng4TetKytUyeLuj/TRuJcIZNf+lPQkRuJls3YXyowzsdSrL738uQU2knBqMnS+nPxtxvQKox2Hg4QqebWnU533Y+uPAhlJYXNHZ5hWv+YLzelM6EFuj6GwkqzXH50NpX8NZ+Kegew2bL7s1wfP7Ea56Hv2jpjZxv2QRTEti7bw5vt870Ds8IQLJTMQ1HA5+IAwSWW3RDIEmnS/Ojg8pND+/tgaQMYMVHQ+QQPcq0eqDZqakJ4gp0U933nzaEHDeIB3LzZ8wSGDyDw+PtDodxBpQ6KpVVT5+/Fde8mG3viWmPCIHTgk/GNy43iq3BLc+KawwjGQEc+0+v8iNLA/7J1dTbQLsiGoQ0p2Zkh2ATF3TsoKQgxbsbYejuCut2o5PnQUijdEa/31K79uiex4V1pdfNTUEKvUCwqOn5mrajTjRd/iMyEQfRcnxga+qBC8s3AhmaLmoh8UGK3MPqx9237qdNBB8meQZmmgvspLr3cKcVu/XkgMEAWXsEB4ok9A1rt4f+KCwNLMvmpYO5FbLtBAZvdLp6A8795DKWlzL2vGHnRnzwg/Fio6c6jUD/ANokMpwVQfZZpPcGu2eBTXDM4w+6SiowkVKbTWxyO5MbX/jI7sIfhgStyZ7gbKUwFYH4Q3VzSwtfU3eyeAw0+IfbDtTkApGk6diF0Q9FhfSmclh6nSfKwkxwxP3UkrKZOrEf6jmKdcQ0ctI4kQCH9z3wb9x0AUGa/Ymu5aEiFxeM2qtz9AJknmOpaOnuRsaRIUycnl5mUcogqaIRSYlLz/Ow0C5G2fTyDGxGsg3NG/955JR4b56nXcIh2FQn0u+B2nVkjhclXOeStlTyDKAFB/Cw+65oZ01i3l0fY1vnGsDmxAoKOjxYcg01+DtNoh6oXWkVBaRjNbTynpetJFRr3zjuHiOi6Q/CpT7fU+ffG4JKcLSZBfAsnZSngs29SBOJyniMitAodHZRipeH6nNuwyFJArDDNruebXeaeLa0CmzKsCVks+3keSFbhyMBvCBVSWIidd8Q0SE6A8NVo6ioVyentZqTEcWCSFZlMKBJEh8s5wx2h7jALZqlvEFhAs0a/ylxMV8hXbEtxjdTtowK09VB8PvB3zudoCC2/8PQ2AZ1M3YlEDZ3dp9Vq1KJoUIlHfdv0qLJ5eE9zx+eNitAnlotBKqWyc7oYbVRKIN2fgswoW/wT2oSKLbkE8Ldnnwj8h8NF9g1R4734PUYEjT4XDcfOdtaUYXkg83P6qZ6baXp5prgkF4dm/CqsJMfbnjkyLuNL5kIsZlUFJPLjyOFyYRhsfp7vyROg7cfhg2bDUM0L3MMjEjE/OZF+gP1eWslQBUzI+uM/yoRIhHyHDA5WYF/IBS49i3zTugHC8K/387+xSB9VUQ0Tr6Ca1F/2Ey7koAbe8yG+g6gEF1d2BjNMUECTILOq3IUYFm2ztvaR/veMREmS8G5ioePWMUYHWutGVP/43q92o3ozPE7f2KjTJ9hjc03VRrY8vdt+yIRSwpGKnYJMbQkvMQc6T+AkxmJAKp6mS/8CCmX8C8tsN75p61FvUR+cjezTwwrdCqKeYS7QO8D8jjhIOZXe9HhNq8R/TDCoTX8LuoTa+0uURTnjSVP5orc4RuwqtboE/FCaZ2dFod30PNviVb6wNRyahcPoRrWCO+FvqFMlfmmseiBdmUr9ovsdI71TX7ZP/UQ5cxqKwGOwgMfVU5+z5DDI1mAx3qSOuoePsPc5VkKUHRS7SflPBgVhKfzSnIRA7DHHNgy6J18/eTr+A9vpEkxpsa8eTSzPtLKD9pHRPVO3fgqdpXzwJFLBaRD7h//B+mVXtm2LZTEBjMO9cdmOD7oNNrbR/kSc7J5FDGmn6LBFBYfeeLy+mDcSCDa7F6s4IjgWN6qb51V9zCPYknDl232Lqx5NMYIjHJXevvL9Mgy670jcwUf0y1errhEddNoltCx0pHVf+rZ5Dq2IvxSc8/hgBxpVYBIbM4g/+GwGkz8s3UPz9UBXyDoqwjJ/Yj6sjHOAWmgV2Xam1+u5w83Qa5npWtXRVJ+WTksiwlAD50PaPq4osMI0SsfE18SMb3gCMzRo2Z/HhzPKMTwXppKNGx2lrEzCEydOktm+fU5ajzmKywnqLU59oTBzLIH6M3Lj7hulU1ai6fmLi9BD97aFJdVhPMp2wwe96Sey0hp/RH5klkQdYIQyQbHglbcUielvlzIKJLmdG151JaZ2qugsNMc5XBjnqvAoHDJPEBY3kznlwLSKR0rVomIv5FCf7RkvspHWyoedJr5sksEt9SLlbLLBNbLNI5rQaHdtxHpS8ab8E11+OqcI3CxUzdZ8B1CkIRpjwDnPdRB8ufZE+41mdSVONrxDTRzuLDJ+IV73m/otsvIknhZzBsPzDtTrJ39Fszpv2zi2Xoc7O82U2VN1Iv/u+YAxjTvthxHNlTongI51NkD8VaCwan153sTlJcdYAv11sj93yDR52DMipk1NGmCaz8uOCJksGsdA0fNj8VTtJLLyaNz9hVk/jXnE+3tRKYdkkEUaV79zfsGwWvGpwzRqqaDdstZzxuVFI7PynA7viITfDcBKN9k+UyGBlHb9N2i0rXx1T4PN83pgrpWJGjlAhvjVOO3uqSprGAsHdqctF+erka53/hZLMwq1vt8xtAkdf4dCXHm86SwkZbdHDZe8Rk2y8NHyhZuondMr3VFbJtppf9sGxRysOW4UyErqovcVUUGEBrXk9u56lEj7apy8dVJYZd8joNcne7p4jU0YpmWsQrj0YNLyhbibt2WdmpWeSsHh8INyj9mXYXjnsdte7s9rc8ANsLpN73CI2NBngxsVyQ9WVb45A4Q+TBHZtafVFIFDHQAZecYiEGXCNEGLqqhzZt+sz4j8GZXm6quxdpZe1B0NxpMusp2ngsCBKOaRxrkY/TWV/zF8QLgNWZSlPLMrPFAo9u4Uhn09xnM9mdPPxOjG9+Pmn8Cx0fghJ0+OaV57rMLZGy2voQlswYM+b/JX4onRnuQl1ssQc51Kfl1uP0YT50hVYU8FcnmOB+6nqCLw1b7WZQzO7J6DTvga6FoS15gaM84D/OUAZmUSbt3cg3NTXLPnrEoGm+/92Gd4q+RHFMgB2EuDpzXkLpeTvf80OKxtADcrUxQJSSunRmQDBOTJ6IzC9dqrPax03ETjjA22wShfEDz10+eIT7dikJd+iLvLUBa2dB/MmOpEWkdse8XOh2uY8+nOZaZcYRRuVqbcsLL9HHFrf4FOOMLPIVHF0EKdXZ9xJEuGtIKbyJxg/SlGaGEm2j0GLRfC1h4EIoRWeHjOR6Sqgnne+BNktcxYtoN00U/xYHf1b9aH/LolXgyZDLMPjE9wCjDByisyV8hnyT2aFxlFWRJPxzOiFduvWwXmYgDUl1FP+MkYxHkOJwWIULsXtxkqYedfZYP9t3QDu1tDym1zH8Np9TgNH071ZB46KsqlNoWE2vSU/lxTKDfNt9DiwVufPBByykFXPZUs/9iBL9uL4WLsK+Ab+xuJ4P67xGVVTJsWoDcWE88/0D9ta3cMCgDnjVFG0fuAetgAUFYE2KD3JQOTElghezufoL4IRgZOzwjGtzkgyaQNvs+dYtQnMXFzgsmcpLEcxEiv3vcI4AjjqOsOOFiMYW7kZCsTeEqE0ZdKyEYPUuZmuEEJ5AC9U6i1Tml1wT8MUVxPV8yrM4hKmW/8oCpQQ55Fzz9gViarwpuKFnh2FwWQOdCIcqoxF4r1ZxeB0+gZGRx6fjg6T2G+FKeTMZeoWnqo9CRUEADFpS8cz4jnWzpEIbEje7DX5txKKgtbeX41nBm2FeyLxMas9NRg/ZY7eZbnBoS5S2W0TUkck1qc9MUWUzmL9ahEGfhM67OUxzJUjMsmDiqcgNrHnBtDAImuyfpXNuHjK6XENhESFoeGiu7PWbrnZulTILkWY4GCWjZfULXHzftnsXE3OJiBZlBqnE5eXTPdF1KoOqAH8jwM6otWYxhYizN4u+AuxMIpyJ0YAeAQTUTqaCrNS+3R/cB15qQiruxg9soPxwhEJ5sJ7dZg6TAD1iYwrIhKNkFIsY8drUklkwdNLDFJhyakoYk8Lpk0WTYWm1Gh9HzshRSMOASZ0btDzU1Shtfw5Xv9+wonHpqGBblR0eaAJoqUAyG5OEN49c5pyYR7Kh41kZT3QRnR5OtsXDUGr4vhB0h9Pn+ChYfA2cQ+szR6ZfW1+l/B4bzdVoQvBf0t5OVenGAWhbxK4z898T2vQNnfXoRztq0UD5Bt8ZL1ZOsvqwpuJ5GBfO8uAiXu1zJp9U2hH8CCb85n2dgSxYqnj9KmgZhak3ivHIv693sgYG/AZv/7AICKg1kha/c6iWQfgbnBie0fynEkeCzKgxjFYVlt9TdLHQsCjMxNTyJehn9rKd7NwP1CWGRWEcLwJxovt/+jSnUv9WtaJOPrZ4vgDEGCwGbsQ+ltvTdX+xIvUy1P6tQQouqUIRKXgaSF3XqXwI0wKoJVEUK1P/E6F6X57qsG2Unp4ViyW1kPmRgyF2ysertuaNa3b5LPYghNjOYJVSYDIZSzCKphAKajyahIHE7UrncWj2fiHNbqk1jmc796Ki2Pq6guBSVo8Uun2X6LIJ/lk2hy9Z8G0CsoMli4kJH8nqNkCsy7jrtF26xGB+myJ+15ahzhcICHGfypJ9fw3oOh4CMr5CIP8bdLdI+YaHF7tm8GEqzpWyWcRuG641GV9as8I3sr5C59GEfhBm0StUpQrqZNDDCsXFX6o2YU/Xy61sGx/m7PfJ2JRY9o3Qmy9SmWaGIuMV7Hnnr09UJGHKSQlqOHcKU9UUuER3DjNLo5PJyEPxUMtfGZhgCRMwrlXKDWDic8qaaP15ibj+3I2HztZdR49ekhHUUIZNhrcYmfO7cRWwqMChiJsOXP5FAXjIoxt7DYJFE+IKZ+K5Sva6d0b1Sy+vgsEir4xK8hngSWxTKm5J5DyBlfLLCQsoKdeg7RmNEq+eEAKofC6eF9oo4oBGkvbxO5KqwMBeKn0VWaTgdeszTFnnOdF6lcpQRJrOemuYy4dMnKn2kfDd5jgmRsMwqUmr03yQCkPnHBJJ66BF5fKr3wLMvLBwgbbMl39vO2xGpUXYyo2ad2WPqQaWlf7RlzQSBpSFoXQ/OXb2qsn6Al73nPsnlw5susyak8QVg8VNIZs8AwW9LH7+M/mEnIcbkiB9nEOy5av84i46w+9WfmeAH/wAnzYCCb3ZmNwqHtK35aogQMWbKiCl9PDpwVyw0AnBBkrf6afQDe1b1NLjknwvOjYeT4R2pPz4IWjGEQKaTS/OT7+UQc4wTtOrNea7+RsrSCXcEQ0zeZ960JM/XN2XHz7lmYn5zgBVV2dWUm+H5siYtmH26h9awxUNL9YrkcXLIRmmIK3NkhY6IuVptLi/gdhCS07drjneJ5feHTDJm9I6FFGBDEKl27Dgw++HufJoLPLFZOMzLcMbcqeEP7+el9r03GxzYcJmxbstZpMIyOz1A8OFXsnrIvAgkwy2wG15+DBnLrU31perWZ/YPtGKLsL7CWEUnngrMDDtPKGZv3xZxdv3Dts16NoEsX9PfuDvpFVQzmK16WdPs5U8NG3l+2u3U8lDR8WUUhwqTbMsQdTLhygVC6G1wOLKXhkUnZ/Mcw76k+g9VC3xAE0RKKsJ9nojxEf/n6DInVvi0zY8Dx+53aS381VH4t1AkZ2nDyjE5LsT4RNtv7mvNdIQpCt6s/NeINJLH3Gkl5l7jYpEFlAiCz5b2/wXrbLEPzhVl3PmZsRC7syRzCoam5xhlFtzaX+7wL9jC4nFQ/SBWktGJ90QPg1bnNhwjmzsgBx87bDlhtJgiG248TjekVav55o1SvIk7Dw9+10yX9ZDNzvVVjEA2n28xRH8LuxFS575hP3qh3mDPY6J2ncI6HeKaIFGxzRCmqJO2VJ5KNquXxgQbJWHLQm2FIP34Hwchj0EPRAa5/hSfPE2NJHCMmmRPcY30nLL/6w/rmkbBiSMxE39Ee/R5uX7iLEHh98QCcU6ZlblyV2APlsaZw0JC9M3aY7vHYnvNOlQQdxISYqEdfX+jMbE6dx0ZMtYbON84L0UFYREFW26yxleYcj15vyT25yluEqnkAhZqWLuwrWWe0H67CPjzJJJkxAyMmwjPDILBTm0MqaSh9iolhZV0TIc8VD35WYjwgepuleXgu1kjNJPcOZOE9ji1K5K6Y+SNcQmqMvj/Gx14padPNHeNbnpFSwbp/bVOPz89qCZhH6v16r+6wp+9bBq9vMI8CdUVcDfp6xhSA93zjEJSyVpO3lZAnJoY/J0Gr4FUdg0sSJ0FjCcILvFy1btIFt6zN7cR4qT0kGbU92icinRLjByyIxsKIEQXIqFV8xI8zi09xgDoDZ/35qcb3T/TUpBLUmoT0X4Oj8d2V8iZU0lQqOYyuRJgkMWFu5ppAHdNpxNt2I1GZWsKEDusnEJbncVj5Snk7KdHVdgPOjnDINIdzSYu/GV4v+Hq6u40hZQcFBSSzNQN7KdfD7nooDo/8MRnAFG/Pmxwl/flotzgusGSE/YaKOZQWWDDUC08hon+2+Slm+fOeslqbey7ZXgwsTV0Eep5WYN3Mrd7Gg+G4qzyPg2CSIvMu+GpKSy6EDKxAXuE4G4Lk+dvi4KBImNTFUOytOQuAZE3yxZv6r4QmJnHdfvXom1Pne4Xy395PFgZ8utIL5fwlSBueq9n9dqbi/QA6pWrlGS/+uGQ5lbx8yRxKQfDtoQtDGuoT+7cZ4f4wjYlOWk/m6GDAYPDtO+egT9T6EJGIhEyFUHbjlr6Xn2QDSp/uKki20Zjr4kkl2KQXzx8ZeodGojiBGfdjtkb+Jn9mTfI++g3ddZ3GSr3eleHy4RzkUcXAupld7S1C0uOYbQLDBwSVPd0lk+1PmYK75Zz9wzcR3hGeK44+7IpV+3aIoG0xY+HThCRxg2PamXlYUQTpDaC2VDFmhGJkjfBaFHzbW9+f/N2FOaS9ZRuTUSLnQO0zww6lqUMOJ0nKsKLO6gi6RRRS9KdMuivBbqTqdDJ/QsQNKHu4CQlsZ+d+HC5FNX2cp5ECh6CXfvOQyquqoRSdhNtTK6hPunxtKKbatUsRTTFuBnnavq6Kppl4G+TXWMX+DTgO4S/r1R0NgyAewXLlpLGGzox2dLGDp240UsxN7Xd5my+i3LafNjwPOBebainiklt/ICjKFbegMX/oCL1OPd8LmKPTXPwpzKXj6DbqhaHpnggkx2i3B+lRMl39I4qtTa4c5CTDx6vU4vN7jYkxri9WDlslG310u5A7uR76bJa09psGJI4vA0+Cq2Q/Fm1XjhArjiF6MC4917hJi2b85PU1EIJQrfPn4r0AwiiP2ZVF7c0ZV82fqfKJpW/mmnCwRr3baMglVuw5iT5uNG04zp5x5S0CQqhYwOLMiPhBOS7KkeoFJq+a/YcJfdPL+ZXomZFAj1L4nEg/Se+8epRT7yGhFLwUSCc6LYRUTeengPys6C9hMDlNXXoctouNry6gJhp1FKhh7cZ2uIni07wp10LBKlhXYezujsfBBlOUgTBZcSy19NCtZjl+pdCCIVhFKdw/KvL7GDJ2UpwOzOXons3PX95PzAVK91M4YLXMooFCrKfpJEFMGqg7KQQzhKur5W1/9TlzD0QUqy+AEI91cttlUWH5WXTqLwB6JlwiuxjfTOFdi4RWeuAFAFOuZIHvkxvxICzibi6lP60V52sAZyw1ARhpKB8iy2zEjHZYdLe+aPac2ahwfpekwZbxZC0WWkrJcLHcE4KuXB9jDDEZg0IwfW6NCuFHmzuSZgThndTY7sldI3kOL/NWCUeeUYsOGMVK9q3vcVtrWu+dB8Q3x4/wDUSMWkPNVXe1IJYtJIrxU0FUG3hIWJxITLzxulhXwaEuFBGKrPpcs5sLIEIeRHfCbFVfeO9axBXcB/Nxi6Ppgi1uef2HHri2gK9ynE2q9oXmyFwNReSOORMx36dYv7myWzjE0+mtCzdkSN73x9Yqlc1qGnEJrPPmQTLFCOv4ViWzxYoGP1rDPsvBGJweZ8V3IrPE2m/FWuBo5DJ8yQaORWdhdPdetzPbHiJ1rQ4wq2yWS6giIi7vUZVQ3baow1VsO9swprpYzQpDt9X/dhWws9mB58fGlMS7OQ2URF8moOZpD3SQ0VmJ6fK+yQH1B6XtucWMKMBMxGdIu+ve7fs0cPxtf8u7xQckP5d9Eh4SSgyHOJAjBbbaxaptasSct2TAETgGDzqF5HiUjbBbuXzH2Q8gdzUxk5GDiF/3qL/TwFOom80mQLKliQqPGuvFVtIzThKfwFhthiLRgOzZor2yVJnHDJByVZLk03LyIkG/I5jnW4fTeiqT7IWsezb8Ois9/kLi2faTZERqFMYh5+T0Dw+dBjZ3kpF1rl1A0K/F5KzF8KMF9bCPVl6QXjZz7JNw+z1ZH9xs9Ogl6dAkVlcq0MEpPuZ3BqkzfWGWJ0V5Qg+DUib56OG5Slzj6SeltUPp3PPDRePS1O+FVYwSQp7uNt++v7RwOBHDzXol/gkud5R4UCz6y0JPhqpiOjeykCaIJVvTHaZQxNEjYFkpO43v/RSCrXpJ2kR9ZWR6tqpBhfxw/CpixXMkj/dYTAzSIzFzSNOJUFAfqX92/hPdM0HMgQDVh5pSkXA0bOsReGLx1n+6wVOl4K9dzwdJ3RrertNQdJmUs73dLqNUICGfRq50PJv6S+oHzoVUetoY1JnBAHHOUNgAuW9URWjeBm2KxIenj9/f+oRuQv3umTCXvvsT3TWov3x4xZnozPWIcRYzo4DGdqVgTXfPRiigccBBsNWjo1pjddqzMl0pfDYOKXvVM6TBnadF3Z+1ncJXKDu/ED3yPs5Jr18YB1997DUUoFK1XIcW+NgwdFLk1D/TK4Wn6HwEYsDz4rN4Ut3y9B8SHwojBUL4Tk68U3Oq+3+UlrwAijVsbDsXlP52XEktMdqqTjGmqOMJLjhPv/N9unMGFYVxLoJ836P1pJbnxvMLZ57OYz7tjEM//69+4RUEfn4PIn5yrAxPn+1lFyJcQ6a8iBcjkDJrRm3++4X2URNG2JFWUnIfWdbcP0QQorl6dp2EIKsMOnfdV9a6siUo2ca+zlMxNCldq5RFqu0yfZlOzlNuaNaXmcjxGN8K55LWTdRx6wt4Es5BqbtQogNmZeQvRAdCib4ErnOY7JPGxv0gFr7NAW9jK1ngKwTRWdQamhsyqPLL6iBOyvNBVQcY0ekSUC9QFEF+xeGQaHEm24xaYT4pvXQ3YQU6mjTeqCKKsR6YEbY6vbanv8OoAMdsFvmYEF+uqs8N4hkePtT0PO0chND9chHuWdTCmSWEnIp4q59ppcgin0NJp9cuLKhgnlKq8bG1+cJ3x8JNOw5U5/Y7K5psQVJszTvDivAIJ6+DKhX0sfBGxWpPwo0jxfyPTawDzHpREkGb0/A7KhZRDi5TFOBBpOKiyofdOUzI6Y9fUNvr80/31RKZmNf9Fxets+/RyhEx18yn/7Hbg0iU/kQ8NRBDYiBYCInhfav5AmBIP9NhtZsB/TSHkB8KB5l9fRxDYAWT7GlzvPtDzUIkU7/MGArBYyonbyhvLxUsWJkDxYFVqIYP+Nyb7f6yfzE0qL4A2R+xVRCo2GJLMmN4rjFNNCLGeg2sfx59A4n2OwIMFexAPr2tHNivtQe+j8GBAe3qLsGjeJmci6kA67mLMtGNus77J/ylROL8XV38E8g4OTPNbXy5U3mmRwsMd7ukJi3diQ3Dz+Fe0RdRfSd8qqjKezXUC5Rm4AawKBHFtFEnZt+SeYaJgveS7fLTn+k14a4vQ5SmBowZ9djB0zC5/pD1EyAMpo9+OjFe3vE84M/XnH77tyWxqTzQZUVRDd7O+5Zn6PRwfnk63HCY7Riic7W/KvODe76cdno3v2F9Mu137uqAGW4IdCjYY0HvUos8SazdTFrQohqbSI+u7X5Ac7tRshin1pm3bcxXvdooLyJ8/GaovpCrtOe+cQEZ08B+XrUSsZXn3zu1Rp7fIBZ2pL6uMgEQSL/yqllh+EuUCkk2isdkRZUjnJwqFh8b2SbRNpvBmbjUmCFd+/2LMaldoQLF55xvHylMMp7ysR/qy2bLHPcJ1nkMaV0SYVHGph++2Dg6mbOYn3ASosRhtNXAnlhgwjJ9A4OvgPXE6ZHbuAJ4DuWDQEV0xCPR8QP4fOlYe938ZN7iAtzGbKoxHBZ34by5xjB8c5lYrTTGaI3Qrls8gEv2wDUWWbsIvpJwbXMQpQGxmU2LLQiuYS+kafpFCnuViQJewm4TXL5Bt5TbdKesS7X4JOOAxUCyzfcGE1jUw5kE2gpF4wB/fhycxvAjGath7c8AlQFhuVwsbrXHzvpEO4UtQnP+A4D3jHv9HjSOEdJjvCY5uLZnHEw0XXvG/UI6oJ4GqE0SQSz9sHkYzjNAuWAsm8ht9EnR9HV/mMrF0asxZX04H6sobiy0TB0H232w9mMB4N9DQqQPKYJPigSydkYieQK1X1d7kJUPyMemS/nFR5z26fNR6mSHeW6YH90vKyTrosr5irKKO2tqvSjbsIq/fXobVqqnUGhOWMstYpUpbfAiJXu6xpUNA9Fyvr8h7siFrIgLA9/9oVLjvoHK/NqFafNiet4pJLZHUnlFI86tMBEdlt1igLP7c7HJeV9CCZMItwVb9HxW2jbhK2/1SRLLbrtOH5KM4uSebj3kukbIMuQMDr1ic5JqCJgLgQLccSAm7mb4MDzrXNjS0GBOiUaqTf2GJCNk09xdv6NPSusRnC4FXz2hZJDQ0819voh1Z6bMpflQDZPOY3IUxE3CeqnUFmwtYnYcUGAvj/i78dFMhs722EJprD5KfPNA3ue11iOExL7XDqd6e1btrLOmgkRVyMEbWQvJMrlzeaRr4SUuaSsXgIuXMh6bP14HTLMmpjWcYEN8Ab+tPxW9dO3VbECtU0KA0ij/bbEQJCkMe5RZ6oV9DnlLv9uWRFnWF6b2kqKqBebWJ8lJewk5+Lm/ca6gx1rN4zvOWyvbP8e9Q8SiCV8dNzKcM+Zz50nE1gh2u1tcGPHyolrd7yVqhQKoxSrV0kFidPENZucxrKLYuOZxF74G8KFvOBW+FzU791PqzKdBUHk3Xwk1eY3jDj03PWxfiQJLVGkPhdFxajHWbl+EqC3XTKW/uj9B2Ry2lLUIwOYZspHYM3KMVHfwhHD+ezGkbTPNpRCkY7/0xWY5my5ruoevVy2XLgmsEfAbb2deLiKUO2uae2ugoNbBo5EK4329j8nWekzWVtlWeO7maOYWbSZLydGejdwELqs9JEceDpgSwIqgLoQkC8iBs8lPSyu4ljU8Z+YXw+qTBJcKasFY8ZxKhmwtTsKf/TpUdlt4vPwF4AHlOpyfA/U2V2N5WIOLFw1n8Xmwyt1ZESE/kXYgbUdVBumHPsHclIEJDitOiO1Yjxccl/obgc6ZAHRaEyiS22MWewWz67xzGK6YN+MNwZl+uhev1xjAw+J/eBFKQ0vfpr/hPbpSH65CaMDUxFNfDe13rw2QfZhzXFnVIqWJ0/fWHKJLjt8z7tIkYj1yBAalp6gL6Rlxj+nguGnsal/WS9airMWvUUXDhLVFtf3oV9ejK1gGUFxESSGug3pseYaaREzfz8DFPP6WiV/6emKzX2U1qvha6SkpchoymXKmqAFJn8qeKY8LiV7tKfES50EthBaVU4pZ42nJF809rdrET+am4FOKD9TAY+d+mT4tt+eBg2VtryfQfTvs/svboNEb7+byOqp0v0DnmTdMgtigh+O4l1OufLhVPh6PiB3vQX3adlhzW30KikJKey9Krme0dH1IsfTmZlUXVxAyxSE+zZid4jRwOpe9hEKiPbcqRcwrikrErSwugKrzietFONzMFvZ7eOFu55Wp5v7ud2hZ6sNbZcD0IDtToH/8aXmN+HRIWYa07pzDInpgIMO5TtEHymsgxfQB9hKC0L71l/QiGAafl3ZdxXsj1E4RVrB/F/2tPKHoW8OoNG199fBi4FM8J5a/xsZCnmtwVUTEETG8yCSqRFFUKi+xKMu2BQW83T8KSzi/QP7iEzD1ftTX3UuGLsUHXkFEwJ6vZpsJhgl8Ybs+L4AxVyad12nxGA9HTtcMaCJycgS6HrqU6RGdjaAoZF/zEkWqHMtnL3uqYPa92kUNeyB1H0iNdRmLbaUFTvzKYRNo5QFIwq+fYtTNuFSgDXq9u0h0N+fCXOdU1mt2npJd3w4fp0h9Qq4GGH7r+0sot68rHnceTEt43CFrAT/mSAjQjhDe0fPk6OFuzF/+XlPIWchnRJCojq5UVDjfP2SIYNFpkuCcGuNJGjoUaUyDMn+yCxag/JrBWVk8LkbtLY8ANLVEmbmixlKWbX1De5RSU55nD0NIp3Gm+UX+1jfGFYqbGSZnTD1vgJ/OskJX0PcPFhdXOaqQDO/1Yr90rY1czQKFaiNeM0hvSsKLGVF/VO4c72xqIIrlT4ziOidfv4ZnDYG3tjaQkeIZhR7qKu6g9z13joPj4ZnmQrw7yhHe5BS+PpGn9MUW9/Hdb6UneosekvVu6LgHg8PdUYT4lipXYX6RqfB/shBk14t2tHLYtVVaiE1af2ZSOPBbiyK0ljPfJhF95KdlpZKh6E+1epCs4qiuK/deJQLRmf1ISMHwhZyZd1W/2Q99sCKmnE/W9/rPlKXxhTQgcQ26cqtq8GM9TNQhM8dpH2czQFLqSvWg+D+QRjBX1R6Coiy8SmM5p13L9hUsV9IhgV47hYP6YR70g1tt/5zzOqGrOJw8ex5V7ibJEh1zb0vvUlIe4GeiIFTOYrB1cW9kWW3PCZgHR7Zh6vYYMcd0PiajTMsQavpsQhq/K12nzm8kvSDXh4MO2gsK/9MBq1KkV4kzfHsyYZpozGwsvttIMsTV1kw8oAocWq52n1X095PGekMl2KZCC7mcAMqA1GDgoA8g56ufrn59w1vUVECJiyMzPLD4FuxbmMD7Je9hrwEGLtk76+wQXSvvMFd2C+ajjYjTHESQQqwMEyoF+MRJju7ZwDfoWLE5Nq2esiy+hs4e4KSTWmzvZ4lLgKhsKNqZibRM2MBEUaU0Z7AtPyxPPK87YgVx0Cu9bAzvVphumAJ7Diniy43msnUX9orFumptfac/UtZjGcaDfm4Pvs6cu+8HmsvLEr9A8xgDzwIyMtZO1UQRWhw6kg85YYZGdby5s4u44sfOBY4cb7qVXfoxzvK56ogKmAFiquIUgyfggL+V7cf1KUIbLCafcykgWeNV/C5XrFmUjgGYkrO2CEStXG0Nsw2gFNnrO6zRApU6Ql0wOdztT2QI7wxDkKRFZKlGNcXW1Z44Xqx8vvO+y4rlWYAjKWRyqbqn6JszTF1Nb7K+zY/IYqDhJvTaxV5S5t/5A/PNAio3/EbrnK7IvwhS8/6j+/Ii22ZRTOPDmwJirBmqO/hCPkSN5oCwoxSkRfpd8D9aL/cGKKJTnktZ0VndFXSql23kSFwEmegg4uuOq/QcCGYjwKga6iGap6mg6usuOScBOm07EJwi0V6fhSS7QczpzveaLsCFdQb4g+V2M1lRRmJ4k2pAPvU8T7QpLzBgtWdW35JlGb0ZOE6yBqSlRrpKE4zH0xBvPIzm966blZXbs7QmwIvAi+8e4+S60UQ/lgnMUBvucKBwgAmt7Kn0xLn1V4R8UO86MSRljND2fgLod02IbB+SPO38Pd3jLZLhEgHqqg2gXmnM+WYTgOkBOANYEulIZ05e1N0tmc6VFOYjwdwOmwTPYQxLTtOmOT2qE5O2+mfLL2DvLoXzoDyGVOn8QgILU6P/fBisa3vAmYmLKCW1N9b3xynaLW55sHqNnb+8JKpgiw8f3MVELy9NHWAesA/Gpa7kfg9tfZNfNh4VOI/F5JA+y5KqhdRugOTWQOkHugWHPbSOUXto3jgvBbKYvNkm9bkT22hZO1kyjzEIi4oksqNI9wxURIPZiyJpO40UqoOn8erNEQJe/W5i6rIqAyecQS6GckEBgZPca866FE9EsSmquHOS640legJ5z+cg0zvL2QQqgynqJJ6AR1ChwofL46mJMMJ3NQP3BSRBzOIj7shVbmhR/TSsdTmsxXnzEFAwAyo3yXncJFsxRpPTDStXHdB/qPLh/9sjDaFEKJpcIU2DykYMSiU3kmTEBIzzgFNaS7k9xn02pZJxzVb6/HfO4YHih6KnOT1WE8sPWjPNGVksAo4r8wn/ExxPE5M4df1LU7HTaS1pMYdc2L1dSjUtFTv6NbaScJr3pMljox8Ud9RurmRQgcaak3hZDq0iAgiq7PIIxjlIdi6x3r8u2VjksFaJ3jK/PxXAy7refTcWcPrPxxqFTUTOT1QrKYMjhxMdZwk9KN9/QygZQly6H1hMQbw+v8GKTG8Iygn1xONZMA2+ItH0Vm49M/9MXieb8tMe8rwsf9IMNzeKNsJImr8tMj52Cf4rvvAe1ZFQpi0yBgY/d/jhl7N7BiUVDw59lwvi+HIaLss3e046iQh6pi9I5cF/saotB3zujK70NAnZvQ/sjJAkZjxqWEaaZvHUfN0JpoOqxRQmYK9TWOqhLuVeOTpXcs/b25kt/q29OYmUAZjXuTOtuyJ24hs1oKGiL8EJAxi4ka9TTTxKHC1xsKVoV0wOOUm0TxF3BA/5rqJuUv5Wn5xApSRmBjvLS4VXiqsY2ZwELuP2+pwV40bvFUPGqrgMZAaUGJRVurmJvcoihlD0i1lSFf7jHGRwOlmZqk2uvHRaI2fl9owYtfNdJr9nu+GCVXRZKSLGBOWsp5Z0j4IDsjOj3fsQalhWgJaIHFk2g5jcbGX10oyCVv9SHtOSphJTcj/+uoNaRc+Fy+2X6JaaXWknqC1rmAuJ8eDBdF5FS4IRKIYDI7ls3Sq+vsUBpcoJfKtsvXMlPnY1+aFXu32Q4sAqg3yEdbHDGB+y7eJJNpZ6UTdyfjPWPqXnyufknTSf0XxuYWxG8eb9WPHbLlHp1IFhegvljMPicZdlUyENasbTr3CU4ukrgSLYtZSphzcTLAZDUTZUllcgyJdzyKgmeENiVpejt3i3Ni6fil3UCBydz2qA6uxYphAW7N2qW5/qPWgr3qcDAcTAoVCt4E9lgP1Qb4Ofdpg7+KW3U8J9LrDsZGbIbJCA1QLNjoHOaf/2bcSL+Q1qMolASU/oH+Ht46HXkvjBWZWaAa4jOeAJZ1YmhnV8ejDKfjuTSSQpoOWujue4JnsEo/tk4hzzy3rIr3H4oO4Eh5k6SSbnYemQHa1btE7un7uiqXTAxSCyEu3rut+U4AzcGHom/APBb7BK6969F5wZoYnHl7j4PpjkQbNdjV8C/qq2A6d8fsHl6DebwZmIiy1JvxE+68nMzZWjWUasNeP0kb+GpciuXGBgEpH98GhFxt+JsJisdQ0u29VjZ0hFvfPWDcvI2aXOWvo+aIPskVvOxHWGdtTs3Opi0OBQV4hrjR7Fb8XFQNX9BMrNLUrFFw9NphFcPWBFfaprwQ6WpmuKzysP14EWkBlLEeZnEYl/bhcpSOnM0BfVnFQ5NLT5LmpcyXk81EBGLJLcsbPNr3iRN6fU02CuqpwX9R5YbGt8eG60q91PKyLlmbKIefAsuoQKdVcG6d0sdAJYtkZHNMpPPyJWFWwF1X0CCLxdVi45OwoKQJKC+Rh2JhDpIMh29VFJOB+derektqdpNB1PZlyIKqioQ9j6UxyO0KDTDcAAiSKoiJB14eO989IByr5/I+jBaGCVJbgwdYWiF+EPeyoGHzi+IX+ctq5usw6TvdC66bQZNNnM/aTwJeyqErOq65U2IB46fBkcr8joKtsFuzfuc3uxVAHeSX5sSKq8DMgCVBW41mqb8G+sh7pK4StKqK2ZHP9YF3vGXHPUub7TEp9zs5lYZz+17FDnrGl1N9HYEJtnBRjj3aM86TSK3HvStssAkeHJJ5tgrJt7ttKm8HqPXA5KUmd63gCoDnp9/LO7qts+p52mg1Sr72DSSzr1vIpcnuIdn9kzSGHWwZ2RBpmAZtKNTgGm6VHbTlpcWVNIJOKi6SvdJCMafh6IFibdrT7ke7QxeJUQKuvFDvLBynPEMdKZWR28trhTyDn0aNgL7tofXMH4maVmtgQu5UEhRR33mOFlkraDbH5eQWjKAGY6yqd1NQTc4WBccwU1kJXiX0EYbHJNTh3Catfsgid9vTMR1OT5yRb6Ns+7mI71u6eDiiP2+vNxGAyGU522VuM82qM8nPX0I18ILqZJ/CywbEsxZcJUouUgXrPexDeYhIGiPg6Gog4XyjVmFi6XtqwjuOeyLQqaECZOOvYLxsc6NGMYpdJvTyn0b4fCLOfe39YRexSCKZJSizUVzY+gEYJRZxT7/qhJu4Wr7EqKF0zMAmXhCjBgG4HSkv2xP0QM+AtQfd18Nk4BuMZayV4BAljYhnWJeSeLDQ5mlupSqAzMdtVyAX7JFRck5e69RalIGR4hW1PdweRGIz8R0qTOAuU0DTwlQhP+TBTH85LyKEfYgrjNJs76BzYrZFRJ3aj8WNxqK3ZPjccLpfRm+kGYLqW9nT+ZraSMaN4toNwc+wHd9WaTdJOIgFxrxWAgCEtVXpLXqfuBJ+KHy2o9rFz7FIgg79iV+6bCnOayb34OmiNcOpKiDkbFIOLA4lr6dK5ZBF0JXCndAU10fWw5oIcnMrzpIrcZ87O2YlIweIjPJ29aVK/N8a1+NQgomR7dbpXCDF5cU6eG02uE2x8qXkj8eV9S/EeqmzOXweMgh0W3Fp4FdIxouNsXSARzCbKBFXTTfvd2bJ+eMBEu6t6R4IDQwjVysPYz3MX/7wkFQYGBkdQ5v/iBAqDLFf79E6BKBqbl3L+alc4sv84E8oOFD44H5JOYbgn3MYFrD5njvFzrGU5xp84KpUwPQbYokl2CdH6W2r4t8R5wwNIJ3Qy3BM6gx0aJHXFJrEi3E5152+K/2dUJV+RlM41lt4gFdYF1fVBV+A6wBJc3TdqrDpfYpFvucF7wLyIdenooC6Wg2MVrGq2ELYaDQ1Wnoy7Hxz2w4fgW35NYy+xsTGIKSwheCjCijp+5VP90ITkSZ1OwpaBmayXIlG60iKrNoIhYBzonmQ3fsVLuzGvm2r491KApPibfATM4CZ2t+YGBYZafQ5JB8mO26MlPQlcA7jB/RWPmm0t1MxskVTjPlOW7XZ7/voalYImrXyTGpC/qEqfTnNrnKP0LgOrl3A4epYRsfuUqXcXjRWvztIVMdHsHh1RgVMXJtdmmDdaJOZyr/dZjpGUjolrcj4pTTFDwzTDS4vGHdleSnCXx3AdxIguIynKHVRUStsaTvJ3J6doMKrLOCezXEE5zRIrT4Bwdu130zd5PtolcCGZzZoNJmFA8hr70STnmMyPjvjQ/sVPoXs+5SmdJUv8Gzy8gIyiAdLqun71A7bOm0o2+mg2vZRAgsvIdm4koNoJHT0Pjjkks/BKMWWnTsfHMqcQ7alIEQ9jTK3T4FnbZzwgrtu9Mos9tiajjP4G/6WNaQ8Aw7OGxC9fOuaGYEDsBs0pvMIUdJSpjPRFLYHJsZcZfrc40Haol0bYY5mBouwMSsh6ryK5nIkR/cigghIPMrSmKm5FnxR4YL+7rrWqaDVZ0nzs5fedvnAC3KJanlMthUh3veFeNNmIukrRJTcPBNYUXLuARpptuJreOKISJnLsgi5xuzg5BbGFg7u1nZpQrg5KE5+zVpEkSR17HAVbkxSG/+psKU83VKQn6s6iXjmgxgFgL8C/9fLKGaTOT+6FrIk/Bg17JySlBxx6k3eAQNcfPT8sg7Bq9PrOYHMCtUg5uCCpcutXPTHrvChLV5hJC5NYerwe6Di8TXKjiwUhSTG9jGHgunONw3hRYSjYQzVMMicle+xTDBYdvL7t5SI7CRTPMRxHdvkgS6TXWnsrjPX+BA7aYyGqV0/zYgXDRtFZFvAcdo+VgWCPZzxYfM4gbd8KhaEZZidN8bt0G8vbbOzWM0sqPoRz1Uoam8V767N3oLG0X/cykhpIerBV7L9tCBU+EypKuEnbHfEcROHwKOH3BP7pX53Ilmzn8TjFbxWJD7uL7kHQ+5Dns0nkTIfPO9hWW05XrXO8iwo1Gt+8cPYDVuddlzmH3bTU2EfJMutSwEguDmqP5wnafBEDb8gs6JnskZfbA709qPij14za4KDM61LhqAnEUpP3MRGldGa+vCDPryYgqEdeRa0Y3aN9O8uatq8AGPRKDPqzfGirY2SeSoN80yxmsm57+n0oSDuJ7dkj7IjiwP9GmGiWHpJdywVxDX0fKQHL7rVK5y+U7xRHSueAYL+ntIIPAF1zs2VsACwZAm1m5U+IFueRQg8yHnsfCa6VwwU0pwzAxKs4pxx/Qn7ETM6zQ9nTHoOGeol1nFKlFqdbuNZLtuOYo3EsubyWypNT4dYfgxjzZKZA0R4ZCDN3eAkHhHwDIAjzatliyEIG0tQFrevBW0Eg60QQYM6UpXgkZqkFJygwV3o9nge8ZqfSnZP5G/1yp3NKFUEtuP4arDCQObHgIcNZd/CGb4VWTfWEMJ8Y9ZFpHUX81o64C+gxlUbfqGOOsUsh4cohsolh8xJnMjoOEsPMrD6Nzin7nb6UnjwFanqrdBdZv8JttndLQjdP4MptdYPCkQPHQr5KCp4k3idmcXXSUgHgup9mW9JCG8a7Ki3WKWWPG8WwZTi4HUlWbf4f6hRNNlbdO14GbID8Ko8G4HRR43eBctie8+1pvlwxD8t75ONeX3qnG16g+fma4VZOMjzyvLQi1xQK1ewA6GDylyjOXC1GgIAN1Sr1mSrqWl8Tx8L44xka0w+QB/bkbxZsq2yyOc8FXB03CgtjP86FDHnPDHoGQuMO5hrM6GA2P7BT3aeiETIzwOAM7slTKyuKYUKfjm/UQgFK6kmOEwxir/HitWNrlR4YAxQhLrHHHMwuFAoaR/ZtfepFpOAROWS50+2UMUv3jneNVgxRsL/tpp5wHUGVqiWcKZwpWWs3DWxwgYGqcG846dRqkMYlOjt6VE2qPB8JJszAceFUwEiLedILdKpnROPxziqejcOiRvHuTOAianPoN9FiRK5nGg+6tVKo94zH8lsTdVZOJsXsmxPvWWAQOYaI0LVlQ1f+O35E2URwsl9Tl/axjs7OvLSVe31IIJBJ0958UlYYZTxDsfN8ydeJwqsZ36Gt3ohvdRLaIc06FI6I8Ikb0QOxIotCmgt9F5zfM6T2cPI4ezVzAz37j6ZexIdp8epZ7qgWJ1th95hT6E7Bo6NA4p4vcwCQk/0HuHbgDIuYmM8EXvx+knePzz9oE7/ePfATgRsfahiP9bsJbv5E1cjtM04Iw2uUUGaZLK6GGVM/fpJ0T7dafZfkiQwCjotWcEL2a43HuvVRoK9VKjK8MPhgYXPs24g4qHZITTXDENI/mTGjKPl+cTgNbfnBA4Subxecr3vbkZHN/2s6t3Q4IAGaNE/fYpzMoFnVCN/m2ktYQEdtZQDt0qued0HVA64rOlbtGLXpVIQup92OZdsE6Kos5Sc8n1yjg2aFwYtOZPULU+pjqyydijERG7A97V8gmRrou6USbwBdffAZqu0o8/4pJ0iLQHrKo7dsMWfbZk1wpBxOrWLRH26lA6Ou4U+zJ3zNlnOVJMyXzvwdIF/Y4djH3Q4DbAX2298IQjWySAjXl1rAc3rexLDYqBMY4/1OvO3WPeJpvDEqj5kPKbIcx48RrIzasGP8WGHcw97I+mtyFzMSNpZmyzCm76aAhOT5rUuAAqqZxw6cV06wsPjVaCueM8Sb2TuWyheURTfa+++zBloqpF1odVpl8ICn35OR8la7xnNS7eMw+Fz4X2NAC6VNkGD2Rmh5JEuVDWXdu9khkWhdA+NcwCoPb2PFzYFLogl/GLBGd8qQloobgkCFr8sLkp2zWexsWSi03rHqkGBxfOR32NUlFtd2RelYRM/zQvBsZ7JHAKPrP9D+RIwA315P5XrCflKjTRS8R4fgS5kpebTBZqAbtY3H2Ha8ZzNVzPzJBZDMAuDacEUPokuiT0oawuEk8tNRbYEV+A6+rEqJwiiOCWchONg31OUhxsdHVOtp9UdGYfFdwV80EZ0D1eAVvB2okiHPXlVLwm7ux1BgGKvq5OC4LdTi1Z8Ynkb2AcqHYGYmbH7fYKoZA0C/oFtCH24+Kzji49rKzuWhdD5lty4G+YpthXPgFyoM3jvNb7SwJYww1XBeb6di885FZU8YnqIQfsFGtADjDqU5dDVPd/K3RyYSoKahpxPMsP8keQKAvO0fZuXrt6+6GXnqlYsJwi3quiOQdVk38N5g79u69d2Nk7opwHmK8mZ2o1frkuZz5t1hGAHF9G48CGCNBOXWMpoewwAql0r/siv1KHPF9p2fcRH5UpyhSNxytfOOpfui/FUlDUyw+IpUg8u4wCHykeEFAwTDoVuEc8CfpUYRwiP9kGpCF03+m9DwlJEH0J6eas8rm2Xo3dIEg5oEsV32QifiQU+tMPQXlxt4vm7253beCTTc/Slknt+r2xeOXjfLU6Ad1FqdDxdmA5y+lUnxpbkXEO2faw6kAv20T9rgMbf7CiCD19mHz2/qDBUP243l+RkwTUN2dq9dqoU4oxww8Cual5ujXfZuWVqL5hJWxqYhx/NDQBvBUmf5BUKvSgKCBPCaX8OKt4o6+Kwoykqbp/nsQxIlOJiMWZI9Gf/Zs7eGQKjb0mq2I4h4vEgxa0kT+8ngcrHAfFcsUumMS0s8ppGoHmKZJM/8VYKUhAtenE+1yCc5AinFluLkyFPp3kuEJ/+EFuXIK61XRsnDluYUzftaboG75zbQ+f9rDUHWU8AuPWCOmsfapfVPhnIqJFtlS+MIIv3hu0NPZR9c/4F8CSKLPr6s9fzI2ikmwOoYXQNs7VU1jBmDKuoljEJVgXz6q2lymE9rPqg+NbgrOSzGLMqO0eAvcq40t2G93qDs478cnRGUg/5atgK7NvyXQDTnkrYSF1wevjGZ6BJIWyiwoMGdTKLNe4vxM+pO4BcTx6IBnlCAVBdkx2ZOSmvGdGCSgzuebc3dbeLA2K/hhQupThWvnQ5Zimlx4rzD42Jl/m4kfeTwGK0rwdvCyuFh72AfKtqEw/nQkhgkxIfgJkG7MvyZTetZLFOf8Wa5hThs8X/e8i8jA+VUim/F8m0lxKoAm82bhgpUej7G9bUSFyHymUuL2mvvSUZKoXecnquHL5CllEeSyYa+8sbn8cDppTV7ID0V/9K2zFNOOklvIsinFye0FLILu3B/zHMNFeHSdW90AwsLb4TnGE6MXIXZeNuFy7NYf9TEhzjU93xzkuin+DZbxSQM/dtgYW6b6iFYG9oz4UrrOV84DS0RaQ+GJzfmpjtmzK94MSo9lmMx5/27bzM1RJeousA1EQFNaDFAZ/kgMQb9a+bxyhE1+dwJfvj+Gv/iPHc3d7bdHgpNxwJx6cCxN+PiyIpSc2v1w7+BdaUZvcPLXaFuJho3BdgLQLUMEpwz4d2SDI1vBlULxoNlJz7pA9qroR2kxK1f+qsMpcZYfZnLiTqjXmxdMuJUK3z1AJ1JSo7+8nJQKd0TPcqFQQNG4kW9KO8BAp6Qni4qdHNfaVe5XSWuiIm8CtcchwMea8Xxiu2gb+wRgZSmVnnzoyYuWRunZL96PuIxb1UMRo2ZF4wZ0Vc3k8/6B3FEDnBpCpxMT9+Aw6kOuDZRzxRMttVYJP3svESU7tJaKlBNRNu1U6R+H0vQvox4ZEO162p6MQSbOo4+loIvuguYtsD2Fp8T6PK6iMpsClDg1RGFv52mSohHiD2vA0DkuMxvXJzXMJZJLIVHINxaLyw6N0goOQv2swEJlGyykAivZodl+RwoSEUzk1SSHsB3usrL+4s4JBDCPVvfavkOUzBLPDxb9c1jwRAe0zvCJcVkpHs2pD5TlBspRvoNIky3jyYCDTiY9UamDdfQKpUHicQtJ7bmv6od3RDMIyfm6wm6nGvLbBpJMmTDnmdm2nFFA+L3q+CJLekSVyj19jNmDNNQUEU/nf6fw5fWDJxU4nzm07d8F6+qnB+m8B3WJ2E1F56wpQouETenZqW7lrn2ptRTrYTeGiHH9ILj0d8iL2JCYGlat3eLU7qEGYUvLt3W26c0sVDnZPk57oH+M7vwmoFi+0C5UT8U5rnyOoefTLluM8hmutpdDtwcj+wLFRxsCBWzTMjLcWmM9NX1P9m9/OU6V5vzIB4dihvv886FL23T+DUfRiwVSyIaoTxBeJh0eYXicUmyunR+bJoYpaNtzcVIQZ+ugJdgyOBCZESRDPIY00fRUnHzKHh2j3W7y2rSuOmvOTNxGMUYvr6vsKR4U2u8tslZ+MmKosUrjeTEmBQzBIsTKja1fXdKw0vtoop0DDjKDrePuwdOHPKtThQ0fNGieYHE/p5U34Ek7oXt1IG8Ry89+ofgkiRHItbVXZ5REoa9wq+ZsHl1srSWhVijtWV8TAmD58f39mAesC6p9+YOm11s1RzczdnlFc00ctYAxVEVVo8udOxArmSe8B6Oujha1fD11h/QBVENVSDXELfOdWE8KEM6o6wBmM30+wxhk0dyN06hPwUFQGcM4c2peJ3kiiAWI+e4MPhTTnu5LLrgYF/KkyxWJG2vctRRc2aupm4eBVCw7s3gFOPCyNfyafrGABAp9a8s4KPJJjx0cT0dZ7/0sHO/XOQ4rh9vtpakqATMAvCw9vIwHi0Oj4GeAPvLLl8c58xjIiVrg9veDTbD/bCHjQllPmE0v5W5wujJTz1GnVNLN4I3HMs/Tt6fneKbLoT4oadTGtKN9/472mfoIbGzYHJ/HNkxt2GIyXTFvAZ0vfB2jWBwOeQLdEOfeN3cGNavvwm5FPSPbvrec0UKZroTlJQOD4jGiE++G6lnRBabBB5IHkajtRhIqXHoKk6GtXa7tsLpoAaBcLYkUu77pZ6FJIUDliFIXRsMs9dkeZWImkUdwSgMNypdbvoZUCNW/QySpDk6UfkfswqMvzkyl4TZ1jLuy4W58SD6SIUuiLOpbtSSR4x+9ATN2jZpJQudvhVF9cxIIbqkA+97k8xfhjwXNt9zZOZRpq4jRRpkHev4lntjmOuOhv/K3K09IKr92AmHuQzio/G2RBdFp1qCPf1jnyB99R4kD0RGACOcz44+OsrzkFISiSlTp939uoqo5vzF5RcKQFh5z2uFekibQJZD3nfJFSorC02LHw8gieqcHCoPOmNvkLRkDWSiGJRgdBZXHiqp0KOxnhAptU1BA/r2mBAvUv5AX06vLsdJ3atHybBxb93yrPOdvzjq0QZ6Z6YMQ2DqtuotNP7Ngzr/jvCO+WvVZ0dD8nWJ8LpPdNqlEWljC7sIPDLeu1hyayU8KfwDfFteiMjGY6reZL5oTI9/zS7DEwlSVUAG4OdLNKqNw7TtuqBtN7rTsOG+eUX/3AROigi071CGHCQpPM+czRdyrQv3ICjAx9HZknH8bZIYNOzvEYlTcuHOH+qPgOSSv9/uLJ0XIMx4k9ipe2iWpGk47i4dgrSeq3BRlb37Z9vUIQGJGZ1vP6c7lompeJ17Bz8Vl4T2miWkbb0D8ORW3E4v1dYBTuQLHSZnoNPR8XSoUjbOIUd/Xn0pT9je3JTb7qejaTboQ/xBaXEJ5vz0oNeOcr4uCro1zJ6J3sk4kMTE9ZKTJ5KlGZKANAFJAzrCyQMi9an2mcojACVK0o7XwVTiekLvxvB9teqHdP8fOme5r0lNPXXkDT1GKie9rsH9l5uSjqVmkd5LAVdxL8GWC4fx26V3m8FmK2ZysLpDmmS0FzkVe4E/QTsNgi6cLUFtuRJseC0ynVqBn0GagADv1g6HoclM9vr4O6f16dM2VyUqmxX430GDIqJIBOS4VxX9nJxwThKQ/xqUk5jrTTJf95Wn0+lxkFKr0HptCIj0uZ9le5x+5eCHOARzJwgMduiT6MYpzyPH0I0HplEsGzOPKyfMxmcKrNO2wv1NTiYbGnZZx44HL3bNnioSsfd535atJmDPMaPLF6vj0WFkS/3tpfbuszKu/S11W+Dh6ADGyewsqe2FI1s8OllAPkqpQoX1Er9v5FaO6rBd4ifdCj73JerBvQch8ijEnLCJmtj4TRUxYWJRXfaEw69DajJwG6dRTVzztStMPJ5OTulg3qjEg9Gv7+ZsVMfZgS5t48tgUOvi6TE+47qXJNiU9S316GGAbn0lcD/ZLMHF+1ZqgcHZuOxIUbieABgx34RSkMebVC1VA8UTiT5okkBKQtNvmi41rtwUMim4uWMSg7RX3Edu4CPOD7rc+bGp2figAehZME254MgYMxhRDlOiKYjfGnbOcXmR7k+J2Mki4mG6kiCcRTwogkHFTZnAtYcOCn1Rny5aP9psQA26zo/InJoXT9S1OSFJ08vfNQV6/ZB7KrpCrUEen2Bx3bcZJXr/NEC3PrJqbl7M0UeM/HMqMUBJMYbhDd3AuM2nOXwZD1XdMcEV1vuZyRxWNFU/ln7JJlXjmgwK1wXuoK4df9Xw6O0bSiJY7nZkJEct61TYobzGdbF1YAnQ4mY38af1V78KRxK5BEnLIEXLqz6wfKnNKQu8wDmcnOF7nq5I2D84o52HKMkDUx4iykiDoPB4xMbUg6AhO/5bumIWxssvvA7fAc0TwSMYZB5TLPKfxXfGZNOjMCUpQoJQ577Ems+yPVd87Gw2uCgD/qjb/TD/cOfxibJaHklstL+ZMdX1rcJZMDLH23pQzUE5NUbnoh09e+y6BborCDWNLRR10QDGJDGHa1ndkwJa+o3zC1moZ32gVC0qBB9XEGY/W07qu5E6tT3ZL9lN4C9NMWVH7mooqZC84jGOWG//SOONXiB3HBdmqMfwbf/3Lv/z++pf/+uc//v7Pf/z1L/96/ndkxFX+f/7vX37/+9e//ON//v4f+v/89z/+/W//+W/nf/4X/l38d3/7z+c/w2YRVhr4SZNxQcQ87mEMJtfAHC04/w/1I2QqyFuud18ja8nW0wl5WqMZXE8apUBM2Dh/y7waI+5wzr8xL+9Qp5j/VKUXcmJz/mLNWXCQNjaLeoFhVSxMCXS0dKU5dfHXsYiIS5y+4xfKfDf5rxjMxCTzrR9mX0ALG/Xzp7Sb60H5lX8hHiNKoiseedF7WvrzhygtpLEALT6SVReeT6HdSOqlp1BgyC0COn40ly0YEfH386LaAGn8F9loDILCtwpG8jcX/0T2J9hYiXk4LDBB68jxkz9U3AKN0SnDF15iliP+hn7vXsqSzx/JxppZgdJpji+FsSb9pSztOXjDSG8tPtGcBy6ayfSBCoSLf6Vm4Va3iLuU6rV+A4twjMDnq/KDi+2tr9uvY5dVs+penKy/Jn/W9jGH6WgR0oAGvcqNsJAwXE2hkdpdlyLdr8Dbn65UIQdTy0hMKcYFAiqPZnfva7B/O7/zeVXssEQBy4uhGH/GgBasrLpc1fgZOsXGQ8mIXAjgUx7N6xhsW/g4saZjXjfmKPhbIxNJ6erGANuL3uPRZhDKJvGslXbFXtnf78VCFQ74IdTW6O78Jml9LzMF+hx7QTCjDSU/9hKfAHUaRc+lkTcksvAM6FZ0cwiX0PorvGDxouDvvLPyJJbIePg2pNNFh5eU7W69LETSkHO16QsIpifox8+jz5eGmUVL/iNNerjFYQWsFcYkhuA7EXKhCw5IMX1GeowWFQ+ChxUxbvAP9VjReg9dUfHMWDs6uRioaparwu8M1zlsj1Cby7tM/HJCWbOdk8MhN5bdrOrTIN3nnocoQzLjiv3qE2/BqPV7iFIrQrAz/okL/+UPMElhBfF38dG87kokF35mfvKgwfEDku9gXXrv79xi0kX5XitSzgiFOqdXYA9y0pHJl4JktOJXzVuCqkTn749p7BZ4GHmKhcKYbt8iOA5+SqoV5QFggOaWlstKEyxmkl6B8kWJY+ZYi8ML8FNVdrQaHTKPESfcKV1quMQ3lXjNtRPJsqCa8hlrnKWy7ldg9YY2WqR9IxAxKVQg87dMpSfs9O6CM9CDgivhPADtMqE4dcawbN/Evd3iSWY4t74xN6UFQBDum42LLk4H3AB330sRHxteYXepuFXAXamqRwlApNCyez0pTf34TkniG2Dewj+Ypr0TxtuKl0Qo8YVC46lCZq7ye63pwAvANXRT4FaV3GAA1i9ki3z33DWsiy/NMGhVsOhvnvfQ0aRzlelsS09z/7LkIHYozpigzpizNhwhd/jBGgbTpXUrVogqy5SOv9Jxw0wUQ9r/n6vzSpAjV2LtVmoJ9Gb/G1PCkMHWzzNzZ6TuqkwyDHCwaA7QveKyl19TvnceN4tkR6Su6PhhPNk4bkYSHvCauzFAmyciqYoKamj52W8J+xjiyXS9cxmXZYP5cFwzas/V77vKI6bwe/BRNEjj2nEl4GTk2No1B4b7hBmUA+tlLBx/29nXDcEjTnvY8Nnlbbw1FVo+8qUqRg26EyvvxOLEBH5vZPAh+lR/zzKKGF+nZVSJjvVTnGDuIQ96t3AEF9yI64DeAJ1MxYOCLYUKCMy8WFld68n0Ono3Xc5fB2ehY5MVCgKAfuTcBEkgfEBzDFybWWWkg53wGaoi1ZRambqo/78v2LltTHZs85ZfkKc1enD9bUAAzvDK85WT6ZzGc4evqe4pb68bWXswPVusQJypeN2+P2LdhSXVy/4YWSQkps7qNeF32VlM6BbgBrPqcqnpBJQzAgJlyz6hnGJh+9YX0k+/jVMhOPSs+kab2YCcVeGcl0WTEn1+HSUayKrmYQm7JWXgeYRpBV+1ReVDhhYno/Xo4Blsv6itshg3EaKVom3B44lzu2IedZIqOcg55TYTHLqan9yPwBCDaEwz1gkmVA8ou15VVPFpQAo3d7hbvreUh1pzWN05GAt+BE5RapluAvpPz6cuBnqc3KDYtU9RKH4XaMBdLHDViD/1kKf4Ea3u7GkMzsnp9kkJjnHXvSipDtE/3KL7c6e+oKhJ0zZwK3oEtWM3LIg8p6g3CIPGcMdqEhRZkGmVrUgBVXNS0utOW1U2K6gjnGWBY18PPN9YPnlVv5xJdKKsEpus3waXJ0RV5/TNiTkpQ79w1ipA3rgsrWMX9peJBzkMTCwTj1MCnY9wQOVofSimdUcnxZA2ovpLuKeECWcuY3440V8p3hGk0xNDcF41JrGx0WsO26J+rLRbtHWelEwTqe7R8ADlaMFgca/6Mm0vnEQU4U/WVpmAnamvuxy3ZB/3JOVbiqIF87h+QbUMQZzVe3Qof/RnpHxUvE3tRb9jSDiU4IpbR+HPA/b8KwXFRy8lTifYHSCYKcua8MwUHMY4SaXAaQG8RqSt1IjITfE3F44L/PTqNYIyhg1Qm77GBAkBY+a4yzjLxMWjgx/l1sK1L9jaIKATqlBnWvHmLVEHccMoa8+ufR7/IRPnz4XLGJL1HK2QUjeREhX6zpNVvaCX2Wtpxnw7EjbkrATMrRpM3sULOKz2YumTCFzc09vM76rP9X5fFE2x53DXTb0UNxbQ9fbj4i5I6fmaNzn/oMCo6/4onf89SYjDwSktK34awBX7Olzq3DkFgCiyu1jjSJUDRfj5O0/ziaCWRtM1ogg2elU8FsSPy6/teO8nszhQrmozxS0/SRjY++tfoatwRwdA1mrROV8us7QkLjqnG82OYD1qiuUrTYzQGfw1Wuy+aaUcpjCCCltZEyhGCJS6yoO7nzSuH9G3vRXPCovk56WZqzB+NkruFI4+2EbK4ZZO5igJRTkV/7gFDTw329gKl8NQxWhLHBek+1Y3ydSO8YLYpgEzlhoUpKWLGBYHLCFgDnXvXeRXPB08VZvkidxzCEYTyjC+wsA5M4w4x3C265KoVOS7JrD9cslrdG4vOu5megpfdLVcYwKdYrjAT7/Xtv5LIfN53NqP2u6RouUAtUPTIjGg+Pug/Z2yMBAy3TUs9BYX4IvGRZIx27jva40KlOt1QpFPjtCUkve2F3zfs6p44eS1wo2hFI9AjzrF+RpmweE/EW1hMmkWH1k/8HJK8Xf1VrTReE/jubw2AEyTdVzm9fdPJirqkIF0IfNkPUezgoSorGnmfGwFWt7fNhUfD/efYIPkSlc/K/tEqWsN+O1EOAy+y/UYX/OODgzmK11w5/7CcaJgAT2MihrV9ENvX1ZyLL4bxYnhtG4+c9bh1TL6DsrUg3ynWPF8E8WJrhkPvdp2Hqt6ohX8lTp1uCj8641DgWRwKTxXpar+GmmPOflsLmC22aP006PvqGc3sxiSYtA2HI2N4dv8I9hqcJZRtAJFVQ0eDqok/Qc0mKpi146QH7uQclYZ05WrSpJv3joulqEJYyNCHbjHemJAc40xPidaGI0hx0BMJoQVjCiylHCGvzgpYpt9MXV951CnoS4OcB6GOSZUOAK5R/8Otz091tQISLp+TNmaJ+/5SARK8buhacV0h3dK28kzUweia2wGL7NhVWXPUQJ+sKV4UrCiUKovEQ2L8Kbzvhv8JYHgRc3DT++rN1p7Rm00tdDz5fKRNDUKk5KFzmBLkmZ7Su7Oac/ucc+zPplaCdRj5p8az0W2jIh9p0lBu49R0/dQVTnRSRFkwyS1dEsGFn5fSxpnWcamsjZ7XdIUy+6OgRUdQomNmvHJuM7Ma1tjgE69Q48pCGjrhQeLO80CWmjPzOaetjYosdp25E5VFnl9io9RQwFFfelJ668iAgL+iaSYfAbYicxtTfYg+ifFO0dCT45GG5dioiBeAmIZa2fMrLP01LPdxoM7LaZ4dhmAmO/bvDtys5pk++tW0S2ukMm86zHnUvmzvJfkS4eTy0TVRkxCZ180jhkToqOvpdUnQLClXnZFim1KU2vRUp20SXXIux8Arkb9Pta+7xuqBOi/xlmukNolgOlXVA6i4lBfClpHXVuOBRf3mHOO2+vIf8WKuPNIhhRmp/T0T2gx946+jbUOOsrin4OGoyWKovZdeDsome3DkyYJ8L6vTe4y8BG24gPWFVolTxrzTY9bhEc5FWbyyL/jeWjVFdP2tUnpDFk2pX9HksrbNDFS/iTKN7XCyj9lHhHrhT1iCFP6s+/jAnTsqL+V1MfU2z01qqFfEfsWzaIWpaBC0Gr9BJEDE2Cy18Wb4h4oe50bhk94TyFO+oGvoUr/OoN93hZO0s4fClPOol3COHWZPHa7J4YKcz7cyfv24UjBWNBC5LiZImnlw+wCx+L7bke81XnNKdSYuwb2+s0BG73/DNpullRPSk5iOgeOeVWn59+X8jbNOLuFHSrez7WOmlZGr9PtouJ3nSrdrjx3Z28Imz5XCcNpxrOIobM8coNyYGivnB2kAGBEibXh92vjE5eyjTbCzLkkPjNFPMEnCCfqUdlTf3M7A2po8ry19WJUlR7cva6vyMtfQ5yy6AGnbKaQf9HGWB0SBg4lQ4It6c1iY6Hq6XrzMQMpoIfCrHYywTjn20cV4mXA1JeI+QwFKk32c8eRZq5LtjY7Q+klZ2yGe0LrMN0keL2ahgItXaAIjDZ4FPslJtUd1TzWPJNLk6zTBglD5yyiI6yscg9mvrCVL+x0151ppy2j25mGSk8zUO8WO8kxP2v3sOLD0Y/EqiMobgTzp5Ng0mr8eEwz14/ry35OjdHxdeWby6sPVjWFVhNRBnc2BugRhzzQRLMVL83sPMa6HnFKY+xDGOoaQLqLRlPJkkBwFmhz9CYcqh6CjUkJ2ekyr5YlAtloluKpnsqHmfU6YPA2zd6US680d0F4KGDazDoMOIyiJsuvLecKhXFJDgViCqZS/nRgQgnRty4HGYnxCFB/J3cFb/zcbqFHpUTxJ8o2KSXJ92D50IMFAWe0EVygcK73dTL6J5w2ZX41FhHgsuaBWg1wbXwNtd4w8IYUi/rMZ747R7ttb1mwD6Qdq3YzFtFK+3FrB2ZJPrczxL7vOf30K47tV5PhhE/HSibgeq4Hzpc9grsKtSKIuQ+FxVBtGgS8vAGsVRsgtoZYOWF1vKfDCSk6Vi2VDYfgfJbJOD5pmKfRiChUxmfuv7MQmyeH2cIK1Sjf26l5rPYlMEytvZ4pAA4vPcmHwqkdu39MCkW7aku3gDRsVtU97cYRL2/hVPljjgpTJ5Re7SDDqHVeTmoj2gBv6/LZQzPRiMkCb9geG7IpUcr9QRrtC7iBFQSx6G/ocTrh3Jp6o2o7gRXEXRUj+xj8mVt6vshJniJcGu40Nc+tviT4bvPz3FGTUWfgd7enc6T08ggAMvVPUolo3lrJwNdTZVcHXwc9eKaUYcD8rCYnz1o71dMRhTCT9ns09PVtz9OLpYIYZRF5f1pWGie2frjmMJgu9+V32uwLKNZE7HQU0L0tzR8t+mH1ArlNMn1pUmXOXBWry6qCHL7i1kTT7yffzzs/OCrHOCtLXIQbaerx5XnOjx1/7df06BXgEsZyNCcF8ANS6ejovToEPEGkjEy6HamI8RHwgN/x63GrxhVsql6lQlNdo9+FxlEumzMcozUmc9NyIA3lV/yHqn7B4bW4hznt0WDsyvYjT/Ixw1H1czHicD4bwoxbYXmBtA++fmEZXxQ8ouRQZglm+UhTUbjWbSnJ/wMqq8xxfCOl6hZt+wSDokjszu2gFG+2Gl0amvBNVYyPEeYooP+x0RDx4gfnc+BjeLbVzPiypvwsDiMNVZUx6jyTjS+qsLMuh95WJFBsR9CRsbtBTsU80bqUN9/9/TZO+nswkkPi02/9/X2ZroqyeNu0TT81d97NY3xVUo1GKyu30ayvdmsXgjHpocP+QQrFodgo0NjZsTB8RQWlW36QttYryCK/3uv1aUQxtbzfzy0XvSkLz9mmCU5+pJyd+BQsFb5HdxyMF/ueuznCfq/MWIoowidrKuPIYDofmOgwxchGxcb94eo+Rr9niZqCPb0apzy7PPqYzgVHuvXRYDg1TqLU/MMx49TyMMow+EktqUSWhSjaUKfkGKjvSaDVyD9q4Vab4E1PW+FNUMNwxpVnXVNOFBv+FNeHCukiEY/zZRPIuOh+V/AUe6BcSTcSOzP5tU8/6nja0IPtbcYL+zxaGwXd4tbYz7GW5xxeSzOj+LoCkVHC9+OE1+wIYDQk5fxklRCD5XIbWE4Ks0RSLZUePplfxYZCOtN+FMAg18xXq8ZwSuwB7pOWEZhUusXXXOQM9zvp1rpZG9ky3XlotHd6YcYzllhEodGBtqV4NTKSImUQhUslBNyNnp3Vy2rQ420qKwc6k9DEmA1QFN0MZtBd2uN4wUi4q93bl90wH9EDTyTO0/ybTEWK5DuNZUbkvlN2SDuPoLCdwFmoEzBraif5Fo9D7Y6XTUVEztuG8XziWGg6D3gTx5VDUEUFU9bC4pjof2c+Pq+Jq8+oFgc76WcEiKOUCQ+7BKqn+3dZnkYS4gpBjbb3+KHaeJRAcHsSiZ18D3AJUwkpy32dsJfGedwy6JMDX26KteTCatbz8Bujyj6vGULF+WeK74l0HjOA5dTB87MpU2xGLkiBjsV0O/JpTN6BydObQCcZC1urCUmbpqPDOAucONMaex/59CIPanDFZOiqrk6lS9IVfz+vFKCcc3iR9A5cW+nmFO4oD43Rbk3DK7zt+CKoV++aiZqmi2xXbeZkPyPbGevhcVTHhcAjCGIOVInn8pGviHWyH3cAcREasxpZz9hRzpeKB4c4tXXkSs6yqhyzUUqg58ENhqGHSwVbO7edkYzcdhmuZFa6K5XLrNTATUzDvS0qQ4m5QNdfglkKjFwgCaxjfcV1UrOdhoMHdn/m5tB28Dw8xeU61cb3XKrzYwHIFcZx1E4PfLNIycQoUQl1vnByD5sqx2Yrb1O24t1iMzTeuiihEb+O6ll4VgqruNPWV0O2UQn5CvOmZ6zyCtwz62/xvVlEs7aQaGomRlyi85+OA8ug2CJTe4e5ucfkkPO9TlpicUiMNKq4LXT8iw1Bp6eeAGw8eLL73SV3Z3KeY+g25hotWnJI9sdbrzEfLXZ/LHn5c6ZqpV1xiY/1HD8/yFvsJknHzZitOmkn67dIqaOUA0b76h946FO4PyNDR5p8cko8kbEycgkDeF9DmtehpcIUfFqi6jGEnmWGOdLclkxMWPKUQd66DuJ0oX4rJlw08pb1UjmWhSoxq6Ykn27Wr2FltP0boiysdqZl/Ph4m7+aVYs0OsR87uhHAR5nRF2jgQy8VfhDNF/lEklPqpoJxhcD2lGVtgqTFXYDNWukOIgrs9kqHaVBVteu5KGWfuXYeLKDU4tGgK7BJDmZUQFT05F5LZrSq0jM0PfIS11fIcKv5lgRcZpAmu7WY8hUcZ2xPGMo5ZkajCSPyX/SyxdlDC1ehww+cKY7v7kS2xy8YiVrCljTiTdXms9XhDitFj/Yo9dkG6HKJ2KLGz8TBV4q3vSpa4lj1h7TyaOZgXJTA7S8rlJGBY6VV2yKqYNcEr3xsRrPCz8oO4DQeZ9AlfSbOeZ2ClbHhBHFiu5V+lfVi8jKz+DVFW0GrhSlMZ2lF+FWOnj5xy4uo+gp0th/M7QB2iB1498ZinsFT7u5xmR3aRiYurmXGM2AasY3nvhZjbH0ofEQxaeCQy+fwYDWoi1n6wR/xeK75tDTKkzzFSvAdlvc59aLS98jfhvqGfyJ7HKJFstjDAMQeG08whnEUxUmWBtpxnJ211dgzP0AxyyW6BFrs8PQpMp06eSTpoOdPG1+M5+caBvi/AVSL4UHsHTZDjhSXCmqXtbybd9qgwtOxl7b7gBiFIebQ1TipmAFksR1OhVNcx8dZBakH62u3FqV4dNXP8CEqx0vqKTF9BnkZhY0RlmvZxBVhH01Gk2iptsaBnlk+D2Zu6Z7u5BPIG2N+z/05q1HPT85JNRRop+sSPU3QgVDtHEh5Csd/QU+8y5NJ0+B4jFdzDLptMplX7zFem505g2wKsLxf/HfU2HBVjJUOefvkU6hGg+gacoL106UFfSzRypcVNaYGjNjhHdFrUel+8MBnR1qRhKVhRvt0AI58gHW945FqbD52gOdfInGNEbZD4cCfQ95CVvRoFIDFZfndKtrJvo1YZJb/XjB3l6MOVXkTI993T68bJu4VDNTsVY4IRaqRIpDdBcOC5eMH8bSiCUAfgXqIskpKB1UOWrFLYzEj1Wj0OCXbq3NIBIpF3tmNeGxZ31KZ8BOcPsi6+sqtjJ7KYMtlGv9mErR6v66NWzaCCh+7x4jFFtDqTItniefMnyqVGRgsDDOGgJUiO8ZqnaADikbQ1vGOQTMDvCNqQtYvgfPIYOFgFQ7FkILwsx/2tVp4/1hRZIdEtercvLOXGmLePhsDQHNyiGNxMSkEq8kI6Y9RekxFS+pvWrceYwjXNGbM1ct0zZ09z14H5jcIcKYyuLOeZwKGlREzFb7Ls/pQCErZTRCYYS5hnztYsCYfrzNkaSHjBWrkwbZfFYeQ8VRTiCSPD/oor4gyibaLdRHZ+FFvh8B2SB41uO7ZyvtO7NP0d5O1STnH67Rqu4V9SvBmOf5EuOjUJbkBEvoUVQ0KKSDc1BUBdPFKWpM/LC1OqcBC7SyY1mQZ1N0652Z4NNr6drDMj1HMjCcDZIOn8xJnaZKHOttJjw6VQ+feLlP0GS2qz2U+Ujz8nMZYo6j2tUfMuUlSSWwaK7UN6XwwXAEkqULPDgnwvF59MpdgM3n4j5L0/RdBIy+M3w2yHyXV7o5g0PzQUNROh+vp1tHLDM5PedPgVUsq5geVlCnQtjK13GebASGgC42AqIGVntppuBakgk37T8PX4ciHsrG1w1nYx/THaU4s4D6MfMCiqXHF8r2RXRzz/fYNXYOU5rvJlAfdePJVggLZn667yVe3d0oNXH9+EfIdkfvP2r6spPWXSwj7ArXD4+agzFu1TmgLNIpdMhqUDJlzIlnXvEVDyPPipsIfU+pNdSz+LSEVb9DmmWOAGTgFH52oERztCjQz3ElsLqth7QI80ERLeK7djYHxcuGKmrNcn4q9ElkDTpIbRQGzceVX7r8y4leGto7rFQavxlSpkSf3XxOSfYacOagEVNxwr6BQIZkAH75KZ9JclHoZboKnuorMVMg85AkkCWmlz7nY+g/W9F+tqJN0h1vUJaAG8Da9pOjnSX9XY5cSr9sK7rpj12DEBTlOkoYy5vDzbe4LAQTycRI2GOm7SVOTSlCEt6GpLGrzfdSaJzhWB3vtEq+apCbCXHA6pg0OR6kwLcwRXn72gW8BJ1wq/l0Vpw0r2mSHOmveOSmDmtWvlRYOisApp79NOeN51+OkpFG5JJiTkg/COLBvstkH1PTao/xnHnG4+kbyQXnp6cDcHAFZ3HyuNdue+w6nDqV2PbjIKMMbVR/FspCmi15mp2tLK4KdeESqnO42x3HhZ6khzSfV4F3uNW7Kjyvcj15Jrr1kcdclauhGm53Lh+XRQa+ZMnBemQHCA4j4v48C2sqo+F7F6TtYJTPUUJn65q5/cN6wzaa5lzu81CC4L9gJjoK5Pq45fcG3jLmrHwRsnsOvU3SZ+DF7yW5C4HMmUkD5gPzJMfTX0R0JFB4+ZPLFs5yqnF6wdZ1TccGiTyJrbeHzylF55Yxqo4v9jNUHbCaOhFANC3axsFfdTRLzg9vfbptKj/w6unVPtJRAY+3jnoUKcW7HraXOFdxWX89iEHT+LhqOGO1cHzOOc77ubOvWrp8JYVMJgaZUPHcAsiC+QlEuDGEJYOwhQ88Q1XA2K29eatxrcHUqeUHFxr5K9AoChTGs7ynxwe0w1DactBN0A7NmORzjQyuVO1Vt1ylsEDC+aopdFEU3TmeCOTVinG3ZSl2J6VjewgtBAs/tCwO9/dTj/FUxug3Cco7jzko3uEYHXTpTLBqbVVmyIgShc3BICoSz6jEzyirMRvGkrb4WxSwYmXTQ9u0pOdcJFw3wR1yORAgQ+Wli0PGXEJ1t4pwoyAB7SD8oozDhlQQoO8WLia6fNPOHuUQC1Pn7OYSczsqS1ct2ZTKuh+tI37+Ph5ZML7aB5XSuG2GfFs7h9nOoKA6ECjJwo4DxPFqky6rFZY2+EUa/ZpyLvKqtiGUV0kTIhG9s4/PhqaXiZr9yAKxEn+UhthZon0y5JlrQQ5LvnvQ89QiKfI91PDscwM0jM7k7L/cC4z2sNucQRJF+sB3o/giYeuVwsIFAmqK9a16SvF5fJMwlUcT92wG0KQb874cOAEnXfTNRw0+KRsCx4XHSRvh+4oWfIgCalMBwNwCWsGOGZTrqGXhYD8CTwxZFc62ufZYD4uAd0aRNi+NQ22Wl8VyNd4tQJJtByAuSxG8S+JAjYOmeZLuuY0UB2ht56JyOzL8LnAbl7wK4QWOQhV6KZR0OjnxaeHb3DJ9ogeYDNLOLjQ4Z1ihDMkk4GBgocGDyBYYLtrI872uXSyrvK085YaSF3Su9QTtNM0i+aNzCaD5jc0TdGDsp/6TB2c9sl0Mk+XdbLKXbc5rV0AWyM8WtPUQvjjWtzVW48qm4LEzf4V4icddMuu70H+CD76UfMPVObOGFIcfaxWj735IWOkVS36LCKFftw1zbBp+2/GIEWCmlRzW4jg+qq0KzKqsopeOclyZg75+gRuGp6xnbixvPe9v4y1g7fD4h1tAOvBXmHOhXd+PwqozMH4/O186TrmkVYlNbpnOxdScSzjzO2Ql6wkTtLHmiRoioxvbdPWHXVmfoTSYxBd3EMDcmjJ2CRel9WJsuy39T+Nk2dLnN6W9wPvI+XdXu0TVlFYrHveAO1dDf1eZTqHFSXfiFtCS3Nhl+eTSz+VO3scdsPPzNAErUENiyU5I7KO5VQ4zAzfmnFxkKYdKFSQ1uRBffBVOW0dDwkOrOgSOX1uSmZh/Kq/RkWPWT9WgeA3qLrk/1jVvJaukh+XhxzCl03+qnkge6vpyTXlFzHjQF4iv7Ob/lQPZo/ULb7pKHAx2ZzxBnMFwpLHt6epMmKArShx8atWsiTFSWLaBepdtCC2Ub/zsdDna86JPBkNerknZotTBYYer+iyZt09UM5hQ1XaaTWRlsRo2/7b2zD6Rcbr0WLpwbYatyldqJScud6VgP1S+wpe0So/KwoKij5E9CG/yvn/1ZtOmytXwKallGGvP1Qr2J1WrRhCRX4bHH4xZZ3189RsOCrHqaYRPMRslZaNYVaEnu8lz8nW/nK5QgyE0ww4QzmR1I1/kknPk59W+kCO1Y8O2BTmijrI/3mb+nFgGfTeuBdepCU2LHZMNmzR0UUjocTEgEc9FCc2WjlZv0GDOSeGfUYwePXQa+3uIEjQPkZaS4A18sAkamSmWNgUmatJns/34mOThU6mebKoRYg6dS0Se7nzgEMN9QO3E137Hsm8bpOvStiomJ3VbmBF+X7B32dBBM8Jol+MPzlIt+yrB0Ivy057cUbFaxQDGEvLBY5D3YG3NgQa6tr5Pjr8fwmBS6Lwnd0FKkeE+lLECpnC6qYSeBjVJknwBU5O6wtZR1BFtar/5l/JNZ0PphKTOW5Ta46Vyo1n1eOEkjAfmtivM21SR4UM6xhbu2zx4lakxEY4ehFAkPix9wa7iCLOQFsH0bNx1LoX00Uvi0x5iD5Yd7+oCM9P51JMk+2WvA49/U6jSuSy+0MSOZE1rbacQ5bHrSl0D4K/mUl9Tp8DBkKC3M/7Jxl850p7TiWd5xVk2/2AsqMUtbzarjGU+B070pXjQ+9L2R3zIZQdr4O4amni7PR+QKhwTfTxlNs05+tl0LVAqMOkCK/0MNPDcRKm2ilQd4Q4epil8Jfk8QcrZMp6zCEBr057xFAObpYTSLJLvBd3zAqogp25rnyXrCatoH+JacgxILOKHJ+5DVJ3SzfHF2okMDXtXJ2nKIOsI0Yw43MchQfnvCnWNxONUK7uhaizKxlNXoduZ+X4+SvWgqsNyayyqNTLdCiPCBuih+AgSCvGVf4/pvOtbrHBdllKcg+Lyb4Ze88NQXq7/0H46VMhCVzOzabIFj8kKUEW/s8xuJ9i1GRd2aRyUH7kj55Oba7iDsRDbkkHpWwRTQQuOS4VQpi0N9PmmyfUaxRpt7i2HmgEj1FrfeR4ebRTmewx7Qwaz46AvT7cm4j77u8TamdsykyaZS6mJzZ0LIPcOnril9XChIIi1/vcscxyDoKqdnt+Nq3DT4uzj64qVwip9nwjtzHjIdoZmZBJC2FOrSWhfcVIemxmfDXe/3qljIrwpxqliqmLZ+VQW1DjCqVtl5dr9GKSWehRyelF7lbWPHI3CUfy854qbTGO8Xz/1BBasjGvSpYm8Kg+c1QmNGqh+ef12ImInAaX9IuaGReLjzBy2R3r6ByylVtiQNc6dBhTxwVpFaeX3GeAeHlDk7/6d175bAIpFdFW9ZyCaku+Dkze5ThJIyjCEGw5Gj4H1X4h91s1RRtHIWX22baPAulXyUxYSc5PXU5LgArZnvOU7ImBz9nUymqBlNgZ3I7LZ7u5YVYjdmB/4Io+hrpuyRkAXuYFb/ACG9CxiN44WULXC2Wpy1EoxCgJ/bmRvYZVizDOWBNnPuWZbfLAQMoCK30oZGhoDBMpAe+XB1GH/EhgXFAF3/lX8Gjhuqna58sodkgrN21CuGpoFisy9fDmUIdbcoK/VE25lxKFmUYd8jRSz7YAoyTu9+Ci6jVZQJaRRHY+pl9Oq4WWAZoRo38UuYv3AW6OP+JQQbYvboZzAFoz12VPvUi0qZgIYOtM2nG6abdIdIltDd8WFyVGq7cniPRjlPBYOhVs2lkTPF4Z49VqNbEtY4kLCCVqeegO98CLMwmmXgMOjnt83V1Zti1MYOAyecTGwFMQRg857HAiKVrTftz9PYBjBQpfqORw0ereg5COmpHWGIQffHbXGC2DnWcohzXIhl+Wkc8nFSJuQNsMG+g6RJa+3wrqc7PmDSpWoAxd+qmGuxQSz9ce0WUjlQEU8zcHm1fA6KTmYgv5zKHKTCybe/FYLwmVe2kOsR7dKUbkz4/ljEJTg7oBmGzEwrFFo3pJ+NTg752VE255SNDEoiTIAh7Ixn3I8tiBe6bU9m1aCV0efj5iEgDQOrGUV6vwHFnqko4OhJnM5H2NSY8+Ie4e9MekxXu1S2HA9t0DJw9CC8111aTpWDCkoFna/PM6GqauMF8ylTYrnYlq7PEm9a+GODVNMtUgZGpzynStASa4jFKZI/7GmoV+08ubKVrr0TP7uc2XjMloh0SE+C5LGr9cRc2YbdHYGEL4PH3oH5qrKPjsz9xoXPNHrCDUr01k/31FLnOtw8UYIE4QXmNnuo52nMqg2JwH2RibpV+Vq8YMsjhxSjaUiMqSKYL8QNL3riaiu1h9Pn/KUSM0VEleUVMRp9jPtxXLIX4DkuNh/C/WkpsmacQThHBIoo46gG/doJRGsGK4I5sy1R2bHAXJ/5kxwUW/L4Vi508PaHp4IvoNeog8j+IGlSM4j8l2rWJEmxXXTs67HGOEOnRYVMe70eqJ+E4O3VnFPv75dEgtqWTWkrkpjR7A9zdo7fnvU73AM0ifwXSsGFfAjpb657mcnvMew/DFv42ZBaFo0Y9zFsuadyxcam8kaxKnMgZpZ9HohsRsoZTyPrTSE9Qln4MnHe/k71esJAs8vgzbREKwdtpnQhCGO563kGkGojMMZwqBjh703s+WHhwpP0JU9dwm5vPimRPTx11HPd7wc+dzbybBlqi+Qw7Y0YhoHdKe5eG83cjILz20IKX/6F/+KbRYr1KLRB5f+1N85T2lx8txp0uSQZhBDE68eswp6KAlYfHelULeTLW6CWPS2vca2EPbP6i6qXgZXjW2h+vgVpFSopdJDuyjDOkxjnPDz8Ez4fmG1LsShqyH03/ldjIM/5XThRH4fQTvZn0RLIbMjg37VR1DuQiM0OgjTk0Lu1GJFzP3DJkSlxjfqFJq8OLGDkf6fAkMRD+/NQutNpstJhXDnC4fJtQbKVblD+RQ0glA8SDA+1Ls/ziO8yBRMzXbgy3iBSvx2aH09TLnsOG4brdKWt7ut/OwOmSaDyMuszLDO1RKwXusicSoHAss5zRDP8VdbevWBMmvaYGpt7Mb20tQBPJ4P6pUgqtSfFoac3u5Jpb6nfdE4sggRgBtGDk4jOFPspm1BKcKp6ffmt3s1k8Zand3ZlDJ2jErEGMoOKdwMxCNmZvezBsjUmuvhQgMOkClJnOuIQTS1b85TlykJARNlnOg3j+AddQbqGg5cmUdgllq0OSuIjxM0PZBn3rWzPUnoKk0hkn7kiBkw85mCnc99Zomkd9VlNTpTqzoBqn2e3UlJK/Q2lPwT/X+ULXC6DK0k1GPg8+rP2gdJh02iv37UNJlrGm9ROWzhG1ucWsfhsA5I3fmpC9jSnT1Ab7rChboBHzS5sqTRTk9/54Jd1GgZs+BRBOXADEoHP4+KFc9+43x1O942M6Po4rPQnCvIIE1nocAzcFWSOoSNtWKpxq9FqERlumQRnx5xKYN8a4AkVHP33h6aSlbcgudvIBAuxwvx16W0npz8oqOT3DX+02lRwCJpCG9RG2L7YdUBEZZAyfjfhjuXdihfM9azGTE7BwqkH4o41WdogLIJ9Qg6fKkImAl1vDtEoxThs1TxsH4kKUC5Kxj4kBqARnSfs6TX0DxDW/rrkhEaIYevI5Pb2ns+9AvAQRBdOI6JVxzHq/IqU/reeeqVaQ1lmVYRLBkQr/ya2A5nifnwRD3wvalf9ToVUJXEWb4+x2XC6O0fOl1GivAxYJUa6UWPucOUeDSEvJCX1eIFX2y5w9oz3ecHE9LNy79ZmkIq1EpP2A7jubht3jKH43tpj7RLSFCWBVPPtkTgO4TGNKyo7V6ON2W2dxYx3UIravpCScE4kjQipItReNlWZguy6bWyLFbFIji0xKLVszLbNroc+QkhMlDpHDcZB39S4lsqAlQBVjNdo6VMAA4Xq3fIj48EItG2vQZofGVQ2Zj7WDlew6TTqS1ViEIs0g+gGwfUesxw30+xRxh6uWHkfWfemqR91EQWFfapG7p3lnkSNfC4WocaVyAGnuKWYLFXvaHJB/57FhjXq1vKCHi9IiZzZHu1bKLhdwzaodO2Ei6cmsBo8tSD60byana9tI+EaayYB1G+051vUG8juFYQIRppNEwTUcVUaAtsz3+T6FuYT7AX3YK0YqfkPJ3vsfeacRy/d7GmVkt3jptTCO7hPlo7VjoEjpV3vFM5oOwBZsZtS9FaWfNkFHER5OxG7FP5dpni1pRog1W1eD2LEWxM+SmqXJAEqurHWzC8LiVHyg+9Nl4WNidKiskfxx4qVJJfvv9/vgEnYKp9r6x8quwh2jOgZghaU16gNLbIAaRZtURutwBxTmhedJ8ZkS7tFEQ6z1BI6DMrAGo9xkaRx1STj6MArVvr/YHWj1X8uHEe06gG/WDc7A64HtqxDxaBdrMlTUoFYYSWYVuMVt4xisGtuLWs9q4IghrOa1O+6S1wbQ7RL9gj1hwhBJtYMZq91IFg1UQxr33YhNsSjuedO697NEFAJmiYQ07Xo1EmB8easO4rgG5hVDAcMVNDeeU1OFq4Yd5ThxZWEVhrNSUyaHq28sMuxW2WDVcrR+dRGDNaU3d0sAbqLoaIUXJNwgmbcqaCa8CsCY7yv2+y3B0CgxCFCaJ1Z0Adiyx3HcDNSYGn+V2Mb+iPhIvxbNzCp2luYDPa/9i6KeimSrAfsAntp+veFwR0UAiWm91U323/sua4YvBsT4oKorzpU8hnDMQdd0sPLoAECQYJNNfEjNviL5Dc7PEKoVbfSKxuo2u3Z54D5cOfoxaXvwzNvgcDhjdiPdsLgqLkXSyGzTFTl9oET9O+z3u9kipKzl/bT4GGys2cTYeDK7v7xaNfqf2BH2LL09ff1x2O25ksB8KKrsRmlBKMY+qUdH0bJOx3SHS3Fa4Nebx0ZZy4xUXyU2zf0Q3Kpq3Yt++5o3lybcs2ZOeNqTHjjfhXWU4HWQ8GdoiSbjdSgZFQTjKh47vkhzHG28D5CNmwVdI6uvdDjEIwcizlw3ViEFaSZy0rLXzBQ2FJYs4OpjhiF0w5HWuo053jS+6oFcOsX4++knrI8vg0lFtZsvWZ8L6V4dq6T0eKQ8HZLV3KSZnhZoSgbbdGvF9I46wP7AUXAn/JE0eCbnWWh/y4KWHut5cn+AV3isnrWTuldE9hNjNCtEpKzGEIY0C+50Y0SXFSvwONEzxMCfmpdecfQQqPJmA0M6gWWsYwQ3BoKDC+bsdm1fDdIDSWLemxFmM71lJ81yC27h6iNSZDhw1Lawy0xvmsPolFQ6K3UiF+Akbrc6PdvHmHIcn6/DGyx48JmOZpP/qmglX39ynKqMqVJ0y2JttRqEVdXnYyB7fpEY0pKPDaT1WNNPPSjPF0sBI98gznqSecydjd5rVRVyIQfjndkQwr40rsyMv5jDQyDM0Emew/wKczNGk5AumuVoixS8i6kYHMhG/41PY9I7ko/AqxenKz7NIUxhgSDH2DKniIvqj9CdzBusuX+vmW8fznlyyE37Y+Jj2W4tRIpuI8BURxzPLIq5lGZ36RKrj2s/PRSyCQW1vcnpL2QfAoneqJD+5enE8igr4rWyeVzKd3+kVk03jYZ5j34gEBrbRdq0bW85O2d67fO/UIFSnbxSnzVbROMicepXC5KW8p6ik8E8sSOu7Z+5PRjOGPjSnFJK9yTOtCuVUmb+TIMeGf3/fD/SNZ3vvhcpQgy5u1ZLW6xRMuE9ALIrmmluzdEiftz3CC2e7ZIjwdoszkRkS4RQKZBSJj/0oyqA0NPpnp3VNwxQrEohUsL3fFh2bZlPmgDSiOppmeLMKkTB6eD6rOxnYU+PSdqmLWsaYsTBNv0YeqRxNfztGpTBFdH8sGSq2i/rabkYMNnYDkvkcISAtiq2aCmM99/7Rpi7ec9nuROMyJcyJ6c+WHvTAiOPTubhl+YhoFcwRkNRAjVkt5ypFV5tP0s46eY9oqMRX8JPlup7yGInGDDQafh3i9h0w/j4p4d0d73Xi+LJhM7CSZJMDX4LvINMMoLJXD18GP9EGRcZ8/n2yt79mdMAN8Z4pu3u8XXTViIkU/pSs3K+EPzw/Z50spgcolQ1v0FdsiSmRFrIbanfDMYtBrcnjzz926efffA12tmpD5KomFc48hmLW06fTOisLB2h4dKtdp6xGqQfRQSnuWYXx9meuZDN2WLY7FpDkcTLoBfjqLj8JDVq7IzuIZMlMGAGw2B1OpSSsy4XSZciOs2SqRxrTV82hhsNTUk1mdqPzLTyarkD6dinjxaTvDmygt1uw9/6a0O9rs4CyApnbqinEGEJPHTn4caoCHNYyRiTaQxpAplIubrnoesfFTBmv1WjApSg7qyHr6bCrgA2NE7wCnBGmNefLhmbSV07rPHXFt89Dwee/m0NVjkCApkpDygOhRAVy/tqjYiEydfS8O6aXQnnSQZSIaS1UYCbp0e3woVdLW6eBink48GVPv9o/3nh4zC9TN76h4E2Ue3xW6JJ3w+8ww2c/3+KgZpxxeMTrU4t0mcqpK6iZhEl8yqBazXLZ5c+nG5coSWyBLXHBrNjTW7NWgvDKjJosI+N2J3hzQlzOfzRwvzmqRix48mm/5Win7/fvtJ21c1WFKv6z6JqXzkRLneGWKHNRBmfidG0kOVybPhedEqiOSrLMLFRbS2LmrDBmcYc9bvNMrPma0auLnjtleilxXGmmZchOiM8mwzCy3EWlRcIGjZB1TPl+y7/zzRhDYlSYrrdpZAsn7k4oB4RG2+Xl6/qPWWlm/6yTd08JZrU3LQjKVkQ0dQ9sI5SIEpZ6q5p89WCYbQS4Mu3I+gdLt11vodxSy9kawo6HvKRZlg/EssYeEJErhWk4sZ2PjuC11YiRNdauEyuFhKqSgWLcslx+rdY57F83gqg/55QpeqHhZQXjKssIHH6+1H8q9/q3kYXsVxwSEM711jbU5PUR6rLieH2GpK3SD+UIYBxzpxceyThkYjzAk5u5M3FtnN1b2JEaIiUrJMsMdtlNqcJlRUlIORY/jjkJxr5js3zPC9A/H0H/t6X1/1zKSfEfmiEx23WEP+Mf7pLMQ6PL9Y83aGYQbjkvKmtgrfn92tnhCrgKtllkRZun66oFKnbXvmknLQso3Q6pDZgeJYmlOr59poGWQqwmtGMBl0uyN/BFBKt/kmEIRa03pERphHsOgbvOsiT0mxPX7sE0bQpjqIw4jw7A96LnvnG0t+mvClCtmQ2oWTjRwZKIORkEHvY6TMuO9Tm5B4gYSIF+LjumrveN4lh0TKemSzuaqJV2EVbBhycyknHpsGAt5Yzg4D5ajVKcVg+vpmFChJSZ5eRK26M/wWkhTkNLOrzKGxuAIVN+lv1oMpsy25wej1HbHgmLwi6JqQYcPNnRkJ30Nm/eDHEmQw9OsdISP8MmMRQuHUDGXEuxFR6zTKBYTgNRt3TjReA56qFy9BvqHEdaLM8Hp/BQUQBiEpS3YggI/CPbsrhmZ9shULtE89DKs9oQSliWG5202eJd3poaNoZydn83PJwCkuFgrpV/rqW7GLo8EvJykogwPimig5fgIP/N5trfHD15h8ZSIR1MT5zwipwINmZj3B/VAyAFj6L1gocS8BBr1OyRgWcQc16HNGNkpoVOCKkbi5P4Iy7j2g/7r+6D0t/yK3Zv8rhaBQ694j+uL9q4OiQuaCoGQLYxc0PUkM2YiLx/IF5eAY9SnY6ngLnHPWW4qITLwgILWpKhy7kRKVztEYnOGsrLupXw9rBl+fIU+vqknid9vestRhng+Y16ZvRzerhw27HRiDUbzk7DMRyildwpzreTPGdvtbXvpuFgG7Ra62WH46Xuw05SdPmqU7aV5vBAPBTT4M2b5THXIUuGuY3nAaFPf2tB8TATaxwxtJe/B6WO8th+LoexdhPRYrPwdzEsvylh+lVJTZNOZQRWKvIJ+i+6AQzXoFCiMRD5Df1Kti67Bmy01v3azs3d0YjKvuPbQyaDSb0/HjlZry0mem4NaBH5vzTxTrDnnIwZujE2IiId52C8xgKidDtSmeowJndObsOYqQECVyxtBn5xiIdnpydg0ptiHpjC628Bg8iImlH4sdAnCvzptcjosdXt1pnSkGXqswTSCJ8uC9MOHl4pWfzkeqh6nSD4H9zo56RQsdB8OjIPTy99uXnOVHaEdTx5sTPc3IbWLO4vvDZOsackZeSdlQhvNR5ioyNyH0qZoj0XPmL/IpCVdRIViE7sjsJmmUZ6jze0bHtGao+ZlDrvERVvdC9od6tisaWqckzGsfHqnI0tDv0Uht0rser6yjX/q9y2xQ9vNZBgKfmmct7gOEvftZ87IGlICI3grEZBgjzylhFDb8QsvWpVPDqiZu66sBXp8HNisYRTLOV/vQtJUxpLk6EYoMGoOUxg3OZC9EP7P01zQ572kBhNeht/r+ezXjQRaTZv+IVv0k4MIpmESOaOcIqdxsOPVH0SzTDStuiP4baCTehq/Dglmf4jMlTCJ/qQSoIUV+XmdNNh84hLm6Y3Y7o7kUScZb+WR67NkxKloZykiin/8D8/7JzBRIiOpOeBp/0Zq/5GCvxdyy+DW+ddWVsEGbiXoYl6K2ca8nUFlNleyO2ZIZTt07MxMzAe/Q/AQRj3p0GWnlvAkRHocVDRAQ3E+j0ZU9Q92iZzeVk9ZznFAsSr/NSkgXOMpBUDwY8zE9f2w0Afcaeb9JEkzMAWWtiQLAjQTK/+JQ9gKNb0lyqJfmRLuE3LM/7lGsYDdE0VeEi+xvhZCpevrAguiPUtTbn/YqHVV/sC0ZlbxVVAXNEdMbWtrWuKHgORYD+P19GmpPRoqoofizCm9c4iTXUUNGbLBJVty9QdeBTdHe6YnqPf2fuw9vpQxhRPDFwjIFb5KSlC4UW7+zSH3Yx4AfuDDT5hk2p1UJ7Sb80nsKdYkg+ZqSORQFMD3WSmqFWBZ5np4IIWHq74cC20VF3PCtxmmzIwFK6We2NNsIoeg0HWqisKucR8iCeOJiiNKmYjsp0WoUWYu9BjsFA5YMgcidjcJtU21VjPCirdPukUAzcEa90/N5DGSS895RjlfXkFxZ8S3dvfFLRjZTE0vn4YB6ec67+iyyKiW2E2bTu5/NcdWAjZdWMSZGARAQwQZM5qPYJUG4vz3kag+xaick6yVDu2CBKtHibGJMeB4xn8qdgx4B77vzOFz+G0JWjuw36ykjulDvxGcNIT9tmu0GDl7NZ0MpHYChrPJ1BdjzeVdVFGJfktL7GnEAzebg70BXRpLPwveKrkAUtUw/zusibHqwqlC6j92wLNhW2DY7fm2WAvVB2LKro9lmiifjHogp3hr/NkZhfF4WbnHTBQrCX7JI2mOsEqh/4S6FJNsZ4WunzeC5U7Is9Pc/PlgZo7bCSXszUjflNGJBND1GiFFPJ1ThfCpLCEfN4TtcVjwrqKGpByJE9+r+zhMitioy1qm3VH8BdCbZBcC060ngwjn3IyxQGf6iPTNnnnwuhSNrPnPcCZ4dqIUIQGqYLcfVI0J7oRHU2gyLsp5fuBdJT9ozDM/Va/Sk3YnnOn1Z7XNWPqD6Fdvidx06ibStD6G5cosNxaVF9FU4bTJBC6hZPv+MyZkpscEtZZMhdkrKdZA2IdDDMBtJxid6cmGRpvFsd7YHkbhrZUP3DSOKX5UjBxRoKlG+A7GfnTT2b2DTNRb7rxAn/DB309sBdQaI5iriAnNL/e60CMXyyJOXznEEa6Xzo75B4nHTTYWO8O7gek9/PeGNoM0iHXtzSh5UjsFk0rbGFxJq130cpi6NPPgS8kwb2Q6Aji97bNXU9Ka3TLQDlRuj9RtUCm2dqSKU0p8pA/cdKHu1LXstbxSGOVc4M9OwRSqKvlYGFIq94wjaeSXr2wafTooBflmDNHvJcOe981M5I6WRiRLzCZq9RFbFNkUDhAaQGaY6MRb14bd0LzkdKjvTFpaN1E+UW4ZwmlmZ+kq5GFe3i3HSpoNiWN9ZXMcYkZj/cs6hMdHua+7ql8lLrcTqVPkJ8tmm9LDNCPDI9v5nx4jNgpixS271cZBpExJoYywGaYTrvgxwklEFe3cetg1fkYYunLtuNJ8ol/osE/8yZZN+Rl4ofCDn3DTeEGIt2DFWQy+lZjwCdDjdcoGy10ekZZwHqKTdVwSwpNzDJ8hIRtGHaeDRJXS+Dw2QITW8Rw8wDyTsGf33Pcv01lUpraLWCs/uRqkK0dGHQ0m+r4lsEBf2so7VOdrDnpeP7XQd4bhggVkbnj5DCF9KO6gQD/xorHTyAR2ehgBDd/4ORdPLGvxhp23h/sYn3LZzhtcZP530RT0JkPw5LnBPrwt4feS0yl5G5dYP7JyWCPMhcRYWBpaHJ9UHNeRUo1wOEKndzY2/XueGqePdiBgckW2MaQI6/j41sOcxRGtACnDizAx3VKgjnT8UdmYSf8+XXZs+ILzydybYhrx4sZ4gzql1v00fH/DHOPZb+B5gaC5eEvPpckKY/X319aflDC6LfjudEjUs29LHmMzeo6C5esJB1zHJ0pxiPWjxHbOd6iGM4tk0kyBHnJ2sOO1mpTTxmHIirbxnUPqHrQeuHIWQ3X1yGBFquHVOcaoPEFRb9dXMaxwOk9ZARHliV9M7LU5D/Ud9NXR0nMYSEBkiabTzRNF1oDBN8LvsXvclhgo50Mr0xvEEFBTt6yM/+UcWxUWZIis+C4q9Z7DAN3Wjum6SxLkP2HOE8I006xmrloipwoGtMcsh6LEZ2yKUoQxImmSG4XvO3HTnLaT825jzUUHUmLNrzS6fQNT3A4OgCKpr4hLB7hV35pGQLwURR21D1IYH9Ai4T+qWLLXLMzFJOrPW3+CyWpcoLTm67X8KnSeKWgGHb1jgR2/rPWcyYOUKFD9higBAmdHmQoKODlEgLveDQnlw19zqVOFJXcLOQV3z7hBasoudllyedPNCpOby/AQwL68iI1LnueB1OVJo0sI8k8z03n1cKauCURMnTgU1ml99qZFjc7wUivLpkkWlHExk6AAoDzG8ViKPKwTgQlJ/QHsFFEkIJkwFzMJaHUlHFkhN/vk53GtuGYwGdnXF2ZtlONA8pJ0do8QoN9gy5anOD5JsRJLuTl4ujVMcQIjg+mdnct5DILQeSjrlcBs4OTTSqBNfSL3e81Ygoz/5O1GeaAGtQXGoux0znP54XqANK7tbrOj34mrty/s83XbGeasmy12LsoUyg9FDkdCCdO2ndPMkXAyCbQ2dFF0O2rZ1KH8mzKEcsnenelgMv5vO5Z8XVkcdA1fo7nSmVtskkusNOse3NzBRuHLEGiSymxlTvWd4ZuYKzbuiAXWTyzzsAOoB16sYdr35ZUjP+ZhZHoQNqiyJivzAkc5yoFlMSZ0xS1G9wKrRsnOMVsvESGNHrpQwjXPn0BM+TM6TVv0O1SOxsJPRebgtiuHWkj+wc28bMWSz/O2kJTZzSnrjsAoeTyoPo5MF4Md5U+hJmyKIj6PP4WGlb3GvkgeDsdqOkHjaJVG7Hv4pJanRicIe5VnO4NtqYYJugS4yXdddjC4TVLKr0iVzheWROdCJvP9qGCa2S8Vw5vDTMcPzCFCrZibLFVBGuvOBmXV9WCUvuSyo9VhAy9hkAe43EHm+aabTcaTrKD2dNdcOMlUlyBYbDwuviyvL3blTgEH/zwCv+gxsKJTjkWOZ2UO0nHJ2pagXx3tQwPw0E2h65FH91whPNYoSE4mgTX+wjWmeIzBvjW2EE6MmdEEFt6Z+mcsyFwy4liH107clvTne8j1guxNNOaxP/+okTgm5GzTie+4M2sLHEdJ/MHTc8sQEs9QqMnCG3sYZjEtY80Y2fGHzO4+FNbXLIkyDz9GutvVQDEm7i/LTUGL/8nIZEl24yWaYh9ceEDyrf7ucytJ8Fl7JTlDlqhZhJ0a8oPx4ONrPan1Z5K3HDPqOGMbKwhbClM1FA1L/PSzbftVvXz50JmsHrQIJHGR1gNvw84V583XsuyrQPMfYqlRIvY3R3dHDgWhDs1Zrp35EPtZaCHtBJbImmTmRucKLdVXkKvv5IyNnldXV8zrK0xllksQ/TANAUkWE8W8ylhnA9gCqfnOd7ZcyNylsygiIqjP9QBUiMZ8iI7y4Q+ZzHe+sHh8PcDJCI2JEmdE2E+RPYCwagMtOLxu9dl8kgC5QsCAz3SSCeOdh0gE4dSunMHvIDwQUooPrp/kke+t7ink0pno4DreF39QyRr0d7xYe9UHtabLOy55bgT40nrwyqE6xZ5plnJc9QrEbd0d/aAiaT9DEC51nbPKIeDUkPiki5Ha9eRgcQ3RaoT76SVhjy05AWtVLnCKHk8QEGQ8kOJDwAPuW9o55xhJQLyECyySYgvH4Pon1D1QlrZErEPOcnpxQBTVAhpU2Rhisbpm+EgpLmg+9XWbLq75wu35HZ6Msnc+EGeCGkWdhE40889NWQTEAXP9YM74TafwLVGWu0YkuHFEqgq2evNPQaIm3BazQtDDvBX1PvTkYzAGOMY4xKUxg+fCGDE8Jl8drc1GXU5oG8nRoCSrfB9hq5YkcOuaCEVRnNhyFqA/U1znYFJinuU8Ns76q4pDQxUp+4rdJL9uF9NU1qyqgW7ZZ1epHcy5SnCAMmVrLpXrwGrtqIsY36tCeSU7pLAwylFZ4hlMek0t89A6KTLvCkOYtYpfXt8TuhVmMXmMGUM/ZRgpOKwJEvwOvX51K4WDcptwGF8bE15cm0K6OvOP44oaCzKldD8x1cANc5Qw9iEk9l/x+XedvZnBYLNetc2g5rIZ6syg7hkyAwYtOirB4WFgij5Oy8JiUoAHfzFZIeTs4RS/QvCxWklND7DX0hDf1xXqcc5AZxZ9EDazXh+zDIJ2d8xB8OHxmetO6aLZA4lQVXLq1I7B0NdSo7WjzZvHTBiW6cI8DbcC2BgQnupxiPPu3YcowoJ10E9hQhTl1O3JtP6ODoEp+THjOyntif7OKHqV1tjNPUZTtai4XlaYJ24AMAG3oT/L6RvIBPh6GcFXHZ6JbbV05h567quPX/p7djLW75zCXBjhU92niGtcGgXylyOe4aPKRQKbhweeSEoDAXZek2hDVrkela6OdBO9zMZupHw0i5ZloRNi9uUsar8nJyFSQqebZU4/8nfo63z7Hm+2Ey3zKeJ1P2p/qx4Gr0UbRiABIdlLQHboPxbBPsmyZEZa5cc1PRhBncOHpc1TCTgvLw0a1r6f2k/B9/X0+CSn8Npc/UvrrkRGxHpVgb+oDdVg2mU29xtJPrruiUt1vM3au55EaM5tvtMmnTgO64Ht393DQXGjxhW3JS1xOB81GHO+9TKrOsw81WdxXlh4h08XkOhxHXGsT5tUg+9v2t03A9uIFuSrbpH1csRJRyLkE6TYuUfJz1UJCSfjjb+2YR1VGQT/+Jm9Tyu/msI9C/k3m86TpYZfpc6YYkNY09N8t4lEX0fzrpemXUFg5znLHWSxDP37TVfvTyTEYOF4FXSsNqX8LUqdxtAfXKSZLGqlw4nYTScEoZWlSeZQctiXg7L+XdE6oBGlZ9S/ypnmcI6rr12mfp0yEb2RvvDTOTCkdT2AJvX2DAHpdrAmMFqfxHiuLKi3Glovobnz32tpgbBpzw6XoyKdStNjemr1x3OsozayKdI3jgbXTHFUt871Kvxk6O76iQRTiMVZ9kP4xXO6tkOkmS5jfUqxA84h594kKz1TJUy3vECX1FSJJ5zieFSVmvK/zI9DIg6uS7RmU9sxqAn6Uwqq9pRna9kA0u0mvUDkXpSxeP3gUBjVHHe9MkuI05kGyNTfibOT4JvY1XuRobXYKfBa3NK4ushX41K9VriiekJUup2QHIbJE5OdMYZIsSfDBT7YrsO22PRatfHo4jZ0UowDJa5oOyb09OnR+x5aSV6KO7NJShgriO/CpfwVT2YjgA7By/yE+hBRxA2PrZ/4udcKnCRhQ+rc7g1EFAJGQ9MsSIYot2cex38/zThaspp2mlK6hvEQVewdMaZTgkNmm3KHjLq195CqiUBNja4u/8knwqSabC/k6NGU0t606n5sFApJ4QmdpNfdluf6xUKbrs2aaK+d4SaTYEYvu9vJMD9T1N6IpaxZoa6MKYFYGhg4S2qSeuyalc1M4aeiqac3oI0OVCpG1JQIkKTdfD7qsNr7Ey9uZ/ERJU4TVi4/mxIkyta2yhTuR2p5vILkqa3APnDQ2IIaKC1Hc4qvTVFa8G7FOcutmuZ6eId05IEAWTwjo/whEcyr1HO6QYLswipotycjGy5+GZB2d7f0HTw9hF+M0eGMaBjDziU8BoVF6D6CYcMUBQ08LelOt6B8WBPcs6NHvsnDcONXsFuES0HUodyqXBxFUukZvp8XQcGBQ9kUaI0nMIMTZ0MrpPKRZUza7e4xzxZK9gwkWBu4NFF9LZlcwMUWX7BEDHZxjArO5dAHMLs99/IA1xOVcIH11264O3AgH7kYRQDZmC7G0ZFDmGRomlw6eWiz/ApRf5ebOYYEcuo4kFiydEHL7i6GtY7NenpC4JRtrxCBQ4vATnO7yUt86ej+ftUZO1HGFRRmh9VmxGqSbqcMjzSKwF/Pac+uVa/2rtcCaX+TVzcMLqVyVVGKNCjD05r9EKE0fyp2mnfrPf3laWFR28TeI3Ce38LmP6BjgGAYy3rxSL6DXUV7D6rutNnvJH9xeSPKDgU9ebzKdw1Kzl3JL9mySSNJv2MMU4yvw/AgTZdJ/Cak3MoCZwFj/5X4IzlRSQE8Io83i+DtgwFP6YzDtlPrWrgYnU6xJyKvPZ5yjAAeYwPR8Z7zGlmUzjphimmrqZoTMzVV+74VLLqazVW4B+Ay/44wVyjUerJErydtVFMV550jNI0d6c4ePHL/TE2QbvUqG+BAweCWd8nF5ywGGif7k1upJIMVERhJaOsaQBsCo5JbKLUK3KXxVx4CHLEm4oa2eSim4gst4Rk8wo017tEpfmt5+DUc1D2SArmv8PWdjTVZe9zN+S5B5aXM0QNaFHek0TDXgvgWfjSaYQXgyvIEDKofSpCTtYBfvLj79rJYW5SiF53DW0VFrOPjbETFL7kkav0p5jXpQhNfCs2iZgbbSpuTlQrKARTArVsIIXgif1+lPG3HTmOIZWf0VyU8ZRLqs/qsTdEFC4NVdatWBr5B9VfOwJm8hWwdDlX7iUTMU/KTT8FMQpFeCaIuDsywngHNBgbdvr3gPIsOkO7OxvBZZyIkyU+ZQar3UaavyqC4ddjFRRbvNO8336wwv1HWUBVlH0+cElAknI1p5KyIJk8ZLmQ7Si9mjN8wWtTgw0E4TnqWo2wa3cdR4S5qSyydUUYKbQtBWEPuZQrFNd32uz+LVfI5ieItEkhyXNzppd2WPy/fTRDE3kCQB7hKFJKs0sW/zDjb5nOzTg0BeBbs06Gim8NBVbwWbcrU+T5xUVhmlyzqrgopP6rxlhL8WR2R026QJTq2lRRkiefu1RQy7oC3poYRkz4kpmJlFSj0RWu+tUK+wina7Mc4rkSEpWZNc2ylSehvYZU1fcnNU85SWNiHLc08bXZcYmzxC3PiTRRuJ43CNxKfVFOij+AX/Up5vmFmzNuqodKJsA+B+Yp7Z2xT2q23OCqhxqFVt/E/pU/c0jM3S9Ov+ohIxMYGa5zeujzRpVS21lAis+RJFp6OM//mh93knNfwr0Qodkbrwqier8YjoYE5RFWIFNvNUeRxqJZkCVooaWsMMTgrLPMhRhY1QWguJYOq9E/FWHUgp7U8XYXSj05NiGmMABRTeCJiwmJXQvbpyPXVFFIySIJFv3q+Fmt1tFMnL+Typ0udT5Yb7e3EYhQPaQeF24/PfFN0hAu0nw+c2dHd24RKAjIPTSUNondn1PTSq45K1puiNG5CGVC6zrr/fkSOgpGqZaRtKT2qcnlSjV3wkZvdUN8Ah8GT4AlnxpdoDx/LJoy4tzAwmkzJSIExnNSQiSrR/bT6WAJ07durw+GX0w2HN0A0vyPQQStQZ0J8P726FEX/0FbrVLvxUzrI2ed6I4iobyOgugM4AZ45ZnmKB75zst3OWIJshTxk+6xQJWmyyTDv0AsykJCLk5GdH56qAkBweMvlRvtBf4zwJKSkmPYOLcAzl2dGwzPtgsWsaiKqwtHrtOQeFXdcfoJzWajRDDPzMY7knh9cNx1T5T621HpMdoRt2zc1mLFZszLqKbiSTdAZs+z78TF9D2Pz/AE5m4j+XEenBMsj1P6mJ0DVzfHDPuP+7vdz3C6/1oiPJXoQW3QogPZBOTJnqElBZYMVPTn1rK+RK/yUaiB3cV9jGClDAXEFBCYak7GxHkoQF6Q4WZcyn+mjmgJJm82H66y9iwZqaSTycC3FyjsUxwjDUTxhbzrAs5Jva9bPweXu0lBDUzq2Z6b1ar/RpGFBqTnPrJ9aiXKIV1u4Nywfly/C0ewtys7TIJZHGaFbAei8PRmFp9AFCb2wkK4z39HPls3TAD8hOh5OHue4k8eVgreoLucuzBFQmf4pSgmyxBQ0hqKCrNmrIsDloTHXu5mp5T3TgU21EFFsglaPIxa7AUP8wyGmmI3TI8Eo9K/o2OFIfr1Li81U2guCRRJ1gBl52yts4EgzRITIClTLJ+uVmv20fGJw0D3CN2IzeTAauNTgljSVM7ZBshxlZ9wpMRwIT+LR3tNBjFNVhj98gzuWqsiHMkXDQDGALLTEOB8e0ajfV9QP+pUP8jLXlSIevoJDNQakMaWlyK7ybcRjvakPAZqFqnez3iXsOcla1vOiqrZXRxTqJY/1UhoC6Op4Oca9F0XuXPUtADh15X3iRoLBI/PuMVh1c5a+r5IMO62vltasYOpMQsnI/Sgnmfl3AIVbQ68nSFkmCqbMtBvuyEzFLpkL2D0/xV5b04n1+E6vbSCr2kdoyD45YxPFaCn+WwgBKk+LMA7gI3ndNKXFC6oFjk6eLtVvVucEbz45KayVRsT78ZHMoQ6iz4eWh30sEcV91VnTc31OgGSfTtdCb+JxTHXmqPDsQ0ofUoBYQxedWbQtEZ82bTJSsvgTPCiwTsX6Vws5dHi8kr9bTH0oXuhx+67Bkmq0J3VzL/M2u9egjDfC8/B9YDLgctC2gxsxqCYxJWWftDkmNCfxvwsTFvOLQcHijAWFUzZpfUrKgx3tAO6LY1QcWI62fodliuMh+ZJPhLeQXRHjjm5ee9MqC0yl9fVuShkykXZAizHSVXpB3p5R/AT2vCNQBL6JG/SoMYk+LUsnH2GRO4Z8AjvzO+7VhEE0f70EcI0XI0797+CQUIc/+MieptBNHWmFtKiX9NxyGIYHi4rJ0zm3P6m2OPW+Ajm1CxGZsbnajL3lDEpjRQW54/Scy8MY2I3wU3ab2tSRZwWjerbnDZwGG4Tat1j5D651yn4kwxQiaFynPQUk05uOIk0LGJFtEPmex70ySOS//D7+ouvRGtBEwNmY/h7s4GnDu1u0QdUi7c1LDGa28hXsQ0cUbM2CwLTtzmYn/2z5m/8+Ui3dkudAlAHSpuyZOj2ZNXA/2Ln1+NZYQe62H8cVDN4zcLaTDgMRKkc5fQm5YjjbTjAqQ3qb1klc66wVwFsuXLL8tn79ONB8Dn3lDxJ9zVeWf6M38+KKK3A6Wthd9CqteviOWMjMmP9Cvipe9dGWfs98e9O5iKrF/vD7uCSjkxDpTgXQEJfywiWciJTjQgNhWSFs32ljL1BWwmJSMpriHDj5y8psbM3xqEtOcsFznnx0GsMGLYUWeZGQ7DJB9oAtc23AAPmDG1HBfwX/Rn6o6rR18FqDxOok0JmlNUPM4iO6H+MaBq3fxysPz5ChALOHk72QbkianCOFyw+fzkMAXTeDWpxMDLGWqaP4n/vzxPF/hSr2uwH2BdvW9QwBlsgj/dxvigV9lOVcFoA4+fU+rRrbl6c/DP2phXakKHyVOAS12pqOc0DzgK9id39NP3HPin8yPbEjzhemtxCugt2q2TzFD7q5R4qxXMbhJIZrLt76B3CG5wmP2dLpzRmINMNKxSPPrrdngv4zDKM0e2C0ApvK0OAvZrDYks6JKoEd/jVFjgadD3C04pRlZwjy7qrssr2iqdZ44F9cJx2zS/EgdQbtYNZdFvuVmqAKMz8iy5DI0zk4qPspB/6LvWANkaGVqsxnWvrxuTNvMxyGjTJK8omKvypuVvsDDO7Z2CG/QUR/tfZU3tliistkJGkJxdYu6mx2U+brKbVgmnqE972Z2HjRgnsfnmTjX9p5kXYqK90/FIZbzUfLzIENJwR6byms6RRgJGvBUDPUx5+vnq5KCnmui0LgE6olCSXX+fA9miFzOFsMoi+ZU26GA+hDgRmu2g9qQs82Af67tdKNLHSotVNt1WkxhEhH8XKY8e3NB1ltUW0xtA5/9iwnikLLuTtMZu1cIujW1x/NO6assQ0fmmpWLx2ystHL0jSwMwSOkAkeWBjfkjH0XdjrzMqzc1G8ybYg7MoKgVCn7a4fNKB2fjfgNcH6HiYdzvzXDg8HxkxdwI51wxdEKwdY9iBUqdkOpT3Upi2SDjuzXFnIG8WMr1a3oA5vKmyKg7KctpN/PT02T6X0jlgwdGZzPA8WN+54uL6yzPQh3LrV2FlF9Q6Wko9dCtVBffaoYhlzOLc0AyBqi2kCrv+oMisvCokLv5Ze/CVHWk+QqVaPXHhUexam9mXgPajEHl1q+quo5owIOFr138vZKtPmLl5ObCGdt4F0DdP6550rTlvVXAxjumGHlAZnk4zw2DlxaZrHEyeKMezmKyD/I7N4y4vuLHgfGOWqv4bsW3E37ziHou2AM1KNbsa7goA1IArBEPYvI+83N2WpwsMKzTRt4DBDcLw5AlSp8cjYKQT+TqRg4TCTqBhrXwglYC2Ybali8jG5OpZ/I86H68/aaj7Zd5vujzPU5OISv6Q8Y9A6aG/l/fO2HDOlkh0N4qG18q+7f4jzyH+H8Tv9Z6BJL49RiAwckPH9m2FW2+mz9eXZ1T3Dljv1xXCHJ8CeY3pZeBYlvQiaaHnUV2tkA1e4bf4ecj0w2UvZ1g5LZxLUCR9zvxoA6eGKH9xtasVN8OT9+rXjmlAUo1JqkQ6Z9U95nh/lkqF8VUKvTEWd36vSmoUi4XSpaBJCOanUY16MQSiVn/hlxs+8bxwGRgo4G6ro6BaVl7yYBk4UUtYbBls5e95l1Qr1AbTYCmErKDBGDbOa0sly8BUEQGAlYO0RpDHdl3WV8BIb2ZyNWduSim7riYe1ZfI8tmf5wU1Ioc05rXLe0TxfjxQJrn0EZDQzqGP++cSyUL/fE6QmgkYjRjzwWmKWV72Xn1Sjj4Bmk9rZ2MuwRIApOYeUlK0U15MeU9tqrsrLYcWUzMyHUFxg2QV9QB6yxrfZ7C2LmJrtXmEs3CQY9W3vEsgzk54f6SFwCDhbsKyjxyIwcR7nKHm+aBC33ZlDevtHGkU0HfW1S4cac/v283Ms5tzct4Gwomd2gx0Odaye1CAnUbj5rMuTpqVZxwMoxaqSzF9xBHkVQQxUvktHihmecMg7kCqFt9yqIXviaI75uO44Mc6aEXCsYHSM9xBk20wEo70YGlFNXtqRnDi5jwHHK4bUOI465xVN/SfmXK8MnFQWdAlwLOTjr6CfpQ8uYAZxUG+0Na+i9UAyWG3w+kqelWsHP2O2MgYV/ds5douXKo6BblR6pZCcHuTthlRk8UhVJ6GEhqbvjtLIVHyow5/nTUyTVGl2TFFWMcIpwEmLreQ3qr2U6J1ZiGLMnky7AWQnB8sZUNb93LLYfxzKsrOWvo6Xh5z2k4qwIBPBA1ZyMSgntriKA7j98HIKhS/u3/VCdk3gaMfUAcT/z5MgPmkNlFso++BIuq7gwtAfDDggvmzBvlSWeJZ3ClbliynCTXBz7k7VXH0F9DJyaNqiltsMaBVpY/RdL51e6L7ITv1+MiceoXoPXrzOLtsvdfNTxFlLTC0LWg1CBdZwph3Wk73d6Tkl973WR5ZPK1kOISrjEJgAEfdA24ZHpsoTaBF/viLo7DsZd9jd6X8d78yM1QEuxiI6MIt9m5r5dvBt6WFbL1CEYQqPPBcny+CWKJE1DQigVQndyrp9QvHWgUjPk751nCZIZpmBh6OzbPY3SZTbAW2FvWvrinUr35UgvTgLxB52Uzy6cLYnjyi24nueqbXIBLGMzoR0+cvTioX9Wm4x0yq0Zbqycn+NgUp6mo2mMJ0cIum9nCbYNBPt0xvNiLvHfV3CH0jZJM8v59I2rkzTi/fvXC5/5+KMHGNsbloR+/b7oIc4ER70syVn4VNs3WDIg0viaqU1hLXwyPDFxM9Z6WHWrkNbn/jVGAIzLfRRnUChJA5M20s10SM8uceEV2Elxz4vog5KsK3kR8edaCi1lfVXfkIG9RtSeVj2+RLQjt/FKhouw9BbWWFEczz2X816C5pfdHQkT/A5LO0v3bop6eqKANm8MZVoaC4usi2mFEvBhDTHkk7wfTbagLCDxVnaLZWnQ53dhMGzKpbP1zFPRAVSLaoCcAWhnO0hTTa6cbhq2ncieOLr9rlZ8BpC/KH+q9ESnUMfSvI5zH/d1hJUIotG6aJaD6fFfJJ3leTa9iOizdLP7rAO8Ql3KSaVAT/FFbkt8AkKsT6VdQPPNBHEDyZ6iHvckycXI3NvcXVNmAg1hqgYL8n82h4k6XFL5CUs6iYAPD1caBiniItqIn8w/QviQbVfWOMiyi2WUUU5hQCIJcdEi5jty5nYKF6GRes7smQcH6TlEkN1S4BI6Vc72duss9gsSOIpUDx2dboqDhsM3LzyeIs0ZWuh6adQiqZ5LBDzYaEQPTGbBzegbZVbejHnUEJ+tZNyK+c4rwqNxvo3xEXkqMDC9nLkmqTNVO29kCqCT7GChaTxtxzt5/lhEqZtM6f5borz/L57dVCdubSYcY9Ty5KMda03eCz5PdVe9snH81CjHBlIEWyk6hCETZuECbfqqGYoSxum4EAMtOrjasQjyZSUXpZtReAhsoQTAZ/5TWPGyoU/6WgxBkLhGX4VfBCMwaqDfydHvJggXMtjK7ZSfqWnVhJ4IUPYSUkx/9Di6wBcJsRS55Payj714YKcexiuQVZU+IIex9G80ZJ+pqFUGU/ByVA55rXdHllRgzHkZv3kQErzc9i+fie0xFtfTcY4FZnc2OxrddX6fa0y4QL8ejaDzmbgXcow0XU6D68I0EaagxXziOgpD2iebiEVOlVqhPwzFlj9TdK9MR0rALVIZxSj0RaInWkkH/rRRZTjDAAwvyjdvXtfGSStD99Doces08cRu0NGeOkSO7B/Ugse3j1HHwpI7tnRSPPXe0TcM4NbUFv/sUOqpPSAvfjUzEdcCrAJ7RtXr5ql8+yBEubFX+lEtppUJtw4ZFnD78fHXZhaVbj1mdeWbM54z5b0KyQX3oBjoheizbc87TD4wpdw7dQDZiP7U7KxkzvpMhRvyY3ozE8SLUXDva9X975MNhwnV46HC+XlZQZfGG/FqP5j0FHE7J7H2eAHLs0o2TTlCcHmLt9x5JJ54+5VXEbTrUCpCFssCZQ5w6TMrgmVClEQ2fHzeI6AYERDMUT+Y84mP5Wvc1Q6FhOjn0kNNhCUJ+fkdS+m7j0yL/Bmk5m10242VMuWPW1IhfZVFPM88tnnjfGY9Bmgh08a/Haj1vdPAoGIj9P+mPvocleND/0SpFMVmSbfNeqRmT5Z7veU3NWvQwkq2SGCzh9pKn1vM0BAewk9ete5xOg+DRGpPE0+uxyKykr2NqWdUg37w/WEC2aXQ7VGyTStHsNJT8rZGTyY660VuY/oKjVQj9K6Yd82oxYcX2tjPf5S6p++Y6cdsJei07UZBhxMzK6xHMSzy7PfgpNCZhpzCDATYlxdeNUS1p6BdZaVxBgG/WBzWjTh97eghp2CDdg/yqNnhz1NquFcnszjBF9PfQYE6owoJBimcpNkG0onqssww6t53XpsdEKZzBxm/gJOHM98seEhE8/xMrveCDx94ZVwgySmjikJ+K4wlVnTIxTgHzXJ01PPwJ9d5xMtSOvP42uguzOTOCY3yPAOurt0lL5THbDqb6ov/2ajYIiKuFFL+ViQCJW4bY0D1IodsYwNfESoOCwObKYdMk4jhPj0CuGzCgjnAAUuHtMRicJd5OGkqQ+AO5Ojtp/yUy2BuqXaDZagzCjk+0uPLQ76cY2BAiksEcVdrFN9u906ILhntieU/fsASKNOhbM9zqZZ6eFT1KoV9ZcsC9LFJy5vbIDlGJK0+BbqGgg75gguuzTTKexQNMGlnp7hzHdd7fZXBKSrclksApEMA9OR/mMvRnI0+rJkW0HKBKMexGExZF/qNxSoz/qLBStNQ1sZFPlHDWHNtkQcxco9mzaMavhBkr99zvViufc9CUj9KSYk64zil6/YJwjoq9io9SQnlUf0JzYfQsBB1lPRi++ISHehcItipEWLsmSTvznneAbuasTpWAvXME17lqy0R0CkcNu1eKgGd0D4nG0GUyhjc3KdYm9hmNvtcQvRwhFoe3aAIDQjbbhEIOpiBpXzl5qsXaGWhEl/h9NE9WZWeaiU+6+BGDXw1ZOtwHNfkX5quke6LvJNc4EjBqCG1IZXcxeG4w1FL7armq+vzRzFDK/wZWG9uCVs4udJYGpiG1/0NjaKpsfxkPzugybSER9lVOrz4b5t4rVIMzGHB6cs3bPJtk4og6h97tXjCKFCwLUbh6nCyapxU/RJ9cbUseNK/9UcOgMiiamG7mq1CchBpAtU6Lqoi/rCc7QvuoCpZki+/xBsS4lcvgDtNqLWlitFGSTZRkdx+8NlhKdDm5RtlQHYETVOF/rMOvl6HmtR0cxXcx2CMkvZElXG5mQP25aip50RecAb9OLo5d2dCpSbuW+j30BU4945x6K8TpHO/AcOZnDUGwUATmXppzEC0vV7FYvtx8kxP72bifB92caKq53g4uIN722WTRSkM6n1JWSarYKoApXJjoRzp1iPsOit29qgn9S9/kEw2Jc0bPWb75jNCWrDhHBjZf1v4FVNLZKsWOI0Mh0MMgOOUPSkA8QhIn4qh8RBVvwcH5EZofp4t8aQLBSM3EccRSnSeUkuYhWjkO+185gCjwEnjVadM4hwOU5tndTHxEnHHDe0jbvAMqYL3+b35MjM6U3O0QszSZqXxPf7dtNelBVVJdnERFLKmeaxMqaN2jecaRrA4vJENk36ElkC7p/zlX8RCLdV4pBUQ9HO0LnAn76IaGQ/DnqBJJGZdfVwraVYHcn/SQzhiWUHtgxYRMnDJll4sZ8AtYCJWWkFI32V+aRAck1A7GY3ypKjxsG1wDxSDS42yvfZ8sEiiyMOBnDFiH0uqyk4lHMaFjRK8Kb2jPvLeiAY6C5aDwdJVrZFjRkb5fBE1hRFxGTJxh/1NbxJqzyyXax4KhVG1bMquZCfcfySYj3HJg2qhUbhkiYuEFzlUedDSOAiv7SHnkJdSCc0Ui01N/dN06IjIJu/PkIulTmcsNnak4bvo9RwTjvOmZ2l4lcHi2ZS6LoT0Tim1jhJknSy+lALf//azXOhVLk5PHuD5It+WOMnKuNdnlv9+B2kGkqb6sbrmDqfZu1vlqzv1pqcdEIMDaOBzDo/SUhO3kQjQje9fyqpAlzbxdHC17o7zYx7ee5gmrydhTFZqi2dBiGZW48GK1PfgMfzxNVJFmVaZb6saCbpbd2gzm8K2wIFaEDV8io2oTkdSO44rI2tim+pjlGHsgLqWZRANp7MALTRM9JwUPZgArhbOXcQVqTfG+g+J//0VuhZ5PqgkgyqFRXjH0uLzpfwmLGiD4BVx75yTc0IAVhvWDw/MUAcitCGXQTYh/HEg5J/jUEkwi57jm6PIR5vfhOSUfcqTEeM2rDqJCXSAqwC8MLtExitQNj9Vx57dj+V8x4pYIvEb15krnQxd1kccPnq4HvXoikj1BwVwXdt7ZP6anyvVwKINEqRuOJ2RigsmSEoy4x5Nmad60E1Kx+uCpppjVvhCPTUZLRnIDtyCb6x6EsjJNnjZ1Rso/7JpuvMsPGNTjEIRcjziO6pfzd6Yh8mAinRSzMaKN/3eqwibD/Jn5g+EZnlkVOQehU9xxTJLrhnZQRQcVIll00Wt5htTBo9ELDb5vHGBIsSZ2ph6NN+XJiMTuBUsrqnh3+8C1i7DrXR6A3fPAyzfOQE4FEhx1gPEHhvzvs17x23R+IIVvl3ZAwOcXuPG4CXENkL3aaCLdJn3BB7KTgEU0HJ1OrPCyM9yRSmZ7/m68h2M1cgw6w1MO6xMMSmV/cbGRhx2IvsvUxYUhfMQSXRrNVxU9i75idwYTuhZnqc1MlPUqaCVLr8ftktLgshcOFziCrjKQ27YJakcrxSAmUMTSUnQQlMEMrO4gPI9SEprHo4cq4zcELVHYE2tHH0Gsc/1zXJE2dp4yoBIsymKwcKWVJ5RFIY42KW2TRyRZ0melcJrGul8UKZH5qzZaJktED8fnPlNR0g4PdDd/JabEAn3tSkNMPW8Py0/ujByHIZDrwfBxBt7fB0au7aivc8atJy8GTdnlBK9BtR7FMmA7q4n+w9zjzcfepc4kL0jw5v8czk+V2cvMkRbAohFdQl7p/SPJs2h68aXIsxLZMTtmK8J7cb+223QamlVN/cRHLFtTH29/d9zoqxlKiSunYFoekQ5byBMcBLPtGsE3/Gz6r48MVu9mTeZTsppmEOKBOGt6DzkCCZD55bdc4qtS3fI5dOUGQpb8g8cxd4x8nfowQIldol9xPaxhnl95tG+ru6AYEhfXBi6pZMjWBjY8VUmaeKQKIWxQL1ZLfs+VxpVHD2qPL58splaK4NOyx1EEqAt4epAvHQrQrgBr/hYHbGBtzRieax2g6VtLBTHnp4aOPhMib7YFiSRiw+QEpVE4w/JgsQ8wuCCoeYznr/cC7AOMyd4fwG3v7nsBb9ZN9bsB6KYCcGTIQxa2ChlCxxmk4OpiiLVmu0jcAd6cQcfmVT0A91c2NqMMpJQ2O6ZuPjzeSFESnpW6b4Sc9zUfGap+27njjAgElRnu7qvSV8QwvUToDfziEQLvhKRRs60Dnkhk5C9+qRl9uXFFl8dmvpnIVlrkBj9rU10tvh4IkNY3aeSWQZcIDlVDCL/vGDxwobIy/W3VnyzkV+60ZXqJ8S862tDWJxN8AhwY5YPOKfhB90IihMjKymv8J9XJUy6YrCTHFShNH7luO18j2yIoVCzK9DWf2JPuCl58lDDsOcm/dlTw//g5CRKWG3vZ4d+sMYczZsSSmZrh30ozq3iIuZkVCkE2mN+P6J2h0lyvrTy0Zjhm9y1oidp88+c2GaD0IfMElEKO+To6h8E9hIrtiM676vwM+HhsGeqXcjewFaChXSFicGHWFx1hBTYtWkVnkEmDtpVPEmIjdKTCawVotS9Dbzyfa7NI05qfkRxxC9VKUFsDgNujIj39bVlcH826VsEQQlP+nOqLoYQzCldoYDRsl5Kn2hF+l5PPXUVuTVuSkgZbahyTzG71CZj3yY9r2sVBn/4JO+iPYELSK4jtYIhTDL2oGbQINXVuMGL+vyYRRm0fd8wtKbC/9+5PQ0hzLBN8laQi/OTOtxK8Fc2t5LOjGrPvDMRRzNEfTIQcFWLWGmQmu3iKiqpfvKPcsbt20d3wEKV924k6xVNJhz+yn5fmH+K8nvkJLY2J1o1Mis+/WkS+XZ7ay6LqcpEN0TtDv5IFXOQHxPg+o5n2DUQWa1XbSqdxfDCfobaloOcnwd5cgyysYwd95anXN4117JSeueMuMvbeXB1jaqXGd0gIy6YkRp1foJ8gFyeCM9sR9nXnLX2CRiT/S/+4qlxfJJcEe5nsp8V51ZKVXXZqTY+RXHOqQnaz9BZZUbwhL6X80yiD9JQ3M9cvdDmK6+SnpR98mYyOw4w+Cg56w0nTEuDpNo1vmkKytJBEzWkZxSf7WU6T8kq7ZHoMe/dsXsaJAj9djhKKOg4mFZM8K3kouarKeacJX0WLNoHacN2XrMTLOX0Awy76lu5scqsQ3EF4NVUpZ2vVeNc65sYvgjTO2E7fBPWDGq4QJ8hSlqduXStWQPB8Zo5KBKggaK24a0Ztktx8QFj2LKESwpcNFmVzZNsHij0dERT2n3c8mzYparyl7jrfipFvXJoGGdZIQtVR/XQUz2Td26cnx9E63OMGstq/8Aet6s4q2F+Gg2gTEtvj05AhzjQbE65eSgAXj0Z7TGuomf5akxIOKilKYqUFvTlUXQaAkT1EOYzED/ZN86WsVg2aSSzAtiPtw9xYhhJA0YoYdOR5ZYtVXk7ye/NguCZgg2F5GTZG0HGwnR9fir8lJnUOyD/p6zLuNi6ae2JCQF5pSDjqNJv2KfplJckYBfGaf9J0gu6Sl2hK3OT7YbJnDkyRVrrXAlc+RQ5JuWxLyEqJ4eaqcvOO+TDrZ9TyOqYSx008esfRhcl4iF0IG15CW+NxUmztNIyXni0PMh4guhk36qzu6eezUxiAN85mirJqwMISH9sWWpHGo7flpOsgYVmLMfHFbd84kAJ8ndTFQdrvRzt6sMy4TNSb7KV2fLFLIfWjBnXTluWfzfv7Zewfj3KbUX+N6U8YwjUwq87wPA6wjVm34yaA2cR6KqyuB9XMjjHDZ0ZBzyrtiMdCzX4dzM9oMb7qsDTrgK/lSpQi6HsyoYgZ0VL0KOx/Kh/XyHCe1dQ/KCTqcRSfwW6nap1mPQi3uBDrgmvnIheMZOP11qGDfABfJV26JSVK6/zp1N9Y9jinghs99KY95cZQoyqRFYMi1qyjHfAJuRyBJ/0mnkedVAQSFTjXiz4HVShd356ziEiN0Tta5uizndmz0922QceP5T9fdQ9/sEkMoSKADgivBlVyXjsJlbDkkT99iUIOzl7uV7aNp6Wgo2Xs9jRdeBc35sL0atOuy30slPIq72zybsNYo+IKw2v4u5Ny2/cgt0CC0cBLObpHsmKAlpOBor2YqJE8AGnbnP5rQvQVdZjGJxyNZAaJLK0INnrbbphGZgUnL4DWbR0SB9j1Q3EU0XH+ehWo/Z087IS7tulz3e65nTk02ielA7CFm0cATMA2kgRmxQC6d3senxfYIlCwsJ6xR0DRCFmB8pQKbuA/OU7yEfh6rB9CaE26RTyUFfhZ7Z41tbkr6aZB0pjHhslsFDTySxgvQPDBXqMzQ5KNs0mzg1xGKMdWdJtM0pQPLHc6iRtMKaajjOqhE5isvcc7bCVwdD/eyvnNJ1Rabr/pRJc8b7xsGCjw+zFynpfqoVvLUKYcEikn+TUndXtWAQPQKVCZr1QLyrQX/SSpv5Weu9gUgpJwO0TJ3ic+n0mNuRjmgbUg9oNT8ePEvfYZAOWqgY36/vKsEw9/qGgJGiNeJyvMTTqSdPQSkoFijIMZGeY5EncXmcJjBam7RmCRZZgiStNOv6NGl6gnnroWGc7Z303mFooeUmMfg8q2niHO+ZNBUMZ+qKPlfd0koBIyJW2mZsHhKT6di8HRwwjPNpM23QsgeM9ZjkskzRXOlkjrlo2ZqKzDhKKWXK7Vlwi9LOaujooS5q/0g5OU03/8K30lcwYW58PPKYjpIS4tp9833lxMinD3GdqDrmtrAcBxQGsT21Z7ukSHUtfhgEmoOmrR+f0aApmRuMv6iMyI5AH6HwJ7d8zNRonH2X7rRgyMyeAxm+KoZGeXbIBGjrcLR8ppWPlrop+5WkBZz3La0LxeGPz4gdpPexfufluB/vxJokiR2Wq++T1kvAU46wi2d0a2a78g6LYMPFdsdsPBQoaQxLT94D0OvIPNzvNdC3xzF/q4+JnPQw3fA28vHHT7ShadWPyX/T9tjHNKrwZDjwvPrrxo3huhGR/BqHrX3Y2wjNaQ4gKjPhDjwVJ0VV9Z/FZFTXzeAJUzsmfJnLObIh4Mwrnm0IzIkXEb/PuMAhDJN2sUWXfcbkBtAlAFeC40Ft0Q8IIWPxYU/Nllv/PA6nT6m5U+I+pX4WTpMPY+f7c5MsDrry1mn1/MmhzCBhcWh9sAReGM44QsW0elgXMS9hZ1A9oIfYUvxoKa0wuyu8Hoo0/JRkoAqxh1kwBAwydhv1jLKZ1Vq6X2oi5h3p1g50iwK9attzEZw4HiScUHU9CFk9e+k/b23N9clkhMc3P/cpVoD5mV7yrZJA4iyvuUwgpXHb6CWC1nNEsddufv/2+fFn6U8rRVv/nM8XzpH3A45tHBnH3JNthgFR6eylSno1T/hPaIwcfpW4lZstBhn94M17MbSHGIX1MFIgqeCO82v1hB2HbuqNWBRS/C54+fVxE7CMnO5dWNzTBAqH9cSxsefjbnlKIcUZz+qPigKVQ9UcuLkEFhgUQ2rxWicDFwPyuxTEGppTWq62o2bLcciQYZydUU+UyVgR6gbRMnd7qQ97dXXdf6e5f44uCP+tTXkrMI7X2HntLh8iVaWJr8XeEapO5l+emhciULwko1kthCOvxdacKxO+692BZZjhJFvIlE5Lk/hDR8NNPjQDzunE1XKBhTGVA1+XZK2IyVU2M3MlCh1f2l79eg3EfMbpMurDKdsMyjKa0ZlkJAhxs+xXnnnN1MfKxS5UBH35fu6ce9JDY0/9O7UW9WBY65K4AOYxje0LH5Jtb+FgY2YHlIyclACJeq96h6ZxqHCHTdNsnbkW1P6hikmEJAZvWlgM5IgJ56zTv7FWoWfRfJ4zrhMS/ceEIMpomamr4rNL79MjBUZvs1N+MRZduIwktjTxeowIcMgLCSjcZ0s6PJmCaABcO7KC0SJ+D0NQ0j2TXA0qnrib+s5uaR6QzqgCTHcXqF+LKIuhoIzyyw7nyOe5xbABXnftZ7ci8ID2c34Pno+AstITa86kUlWYOHBrPoRRWG+g14uTkESepVVsGhreU/p7NX+LDen0FBEM496eHFkiyKKay9Mx5ueZndz9cACkgTaqAy06/JZLRqBazB3d92lqni2XO50X1RtXdQZa8rIgPTab8is2gWlMzqVGeyZmMAGs3R6jRcPYTcGR5WqZ5gzdA771ufsbvYqDs8VgjouFtp54u6LwZQp6FTM5RJ64F+j3GABw850MBhJSIJ+eO4rNiLSaRy9Gz36VVs83d/JfdDdRfTi2YThHkjFCMEIMaQ34/8YQBHxBy72GlbmwMp6II97M3zXVjxxytCc2Bj86jm0r6LB6eQYbX/nO9Krw4KppyIyrTQeNyYnm94SquQRRqwRNl7W5nWeSUeCwGuM5CrF+mu98l7odIyu5liedbUceY/+OcAF/RsC9C4f4dRpt+72VnfN7GzQUn57fXCmKZdh9T5MsvqPSeb0aKk6HPrRyDsZ1SlnpFjUacBqw+VfcJaAU+f4CIxqhFn2A25OjD6EqHBnevUf+PnmNlheDRyM5kf6L4IFxtl9vXTbESm6R51gZjVyeMIN6qs67b+sIa402t0guu58R8di/tl+CDfUrj+qKHsnKuDcNazkNw7bzO679YPIvznEfqtq3L8iiQfJd8TkV/VecbE0gQ/mgUVDLECD9Lt/1cozrtnU34v1vosJ3HqzgPymAizi+KrQq5JOiFegDRMe48vPh4K4d/TFmdeaTPKI80uQ1vTfTVGD+tqNm4VyJz/x3JdWzORREZtt9k/5xdS67tuxosX6VoWrTSN9tnqUkOtCoDiBRNBDi3cn/i3DaqzpHh117rzXnGJn2f4n4IqwNIaybO7I91eeYSLQKZx0zurWvpDBn/CzO9+UGUFBF8R3jdBl16++5vc7wQepsBdsoTZHYdzg777tgR8EP5MpSVCIzvfGcYC9SyLNVHcyTsRXXo43nah4XhUfzunb9bnx68eCXXF1KDJxuYBmcEPugl51X9PL7/Nhdakkt+rxye34ZxKcL2h0Wi6picExryVO/ell0O5n8WTMca9jxj3kz0U7zb1UFa80SfuB+5ywXsbZik6kDkR3outwtFcKTGvw0dwZwqJA9eGDhneu4TIHstG2MpRbiUxpSMupsH/rtAnr3cd2VFJ+34vy9AvlQVC0DKDgGP9X8zhqwwS9phfBevk0DAkA+88xAOHXOZ7o6hJkrPBTwVE93ygLPdhRhj9SRkKu6Ak8ea7sjDyKdxyQARGteWg6sIOki5YKsLKQ92XaBhoH7WG989J8EYzu9pIv9F0+81jvoFVhVLS2EwgfA4Vetunl+pZxJhzYwvV9TTdBJY82LM1cVdPkBZDR/1MEiR/MKLcYxfBKsFiqA9+qSMSvu5K5vardTqHUug3fZDpsu4DzMMAIGHBFPQYpLvO9xkOTeF50Wnl9855FPtAkuVXoMob/zg/P0/d/dxTGbqzjapm/qGHHlocBwilI7f7xRClBtx880lKxbfkrJ3KNlgFoxS9x+bn4EGYr0Oig27c/10PzZi+g5Y55Sz97wvSjhCdkSnu+n8IW9xAE/ipXSGYqPOrITkFikMGzXshOBU8bMtp+66WzKspzFjb1/XF0bo+OmgoDLPTRDYSCJ9bUKTSSG5/djQjoZQW0/NkrUg9SXpNXTHZ4JkU0kMpLUV7LdgxbAyBE1YDYDGh1NFH3BkjCJ5vnVO6oxVDBdp1l1sDjitMhunNqBspdF+frWTpY8aoASzimNVDQLDwOXpuM0/+sS4BD/knq5wFMEfvoQmJtLMuY1Zsgs52sUEckq+a5onSxJqE0hC8W03Jfxk62juAnd6ngOzkkpfPMkm2k0268s8DjQ5nPFs2sZf2XGzFCJlu+XQyQaO7WYbSq2a5iD7FeRFzz82HFHl22u9QzenIiwiaf7RFySolYlZzPnuDiRiUgGHSO6wKMjhwzTXP+TKESHPR7J9Vjqkezxfvp9O1NcjDiYAubauDwA8bpK8eg9bEFGV9blAIhPA+IZzwMGb3Dzo+yU77epLuNmOP5muVKXA5m949fBU8QIrnHleaLczW8Ie3Pfxyii7XBy+JdJSJDO6LKwLjq038UUvV8eiEk6a7uihuLaFbfYiTtiBhMP52gOTaEvwt+jIMMTrhtDqEaUj1oNArZNJNCKiRfiuS7FzlbqH7gGTl5NHwBwPrf1aHZhYfexFw9JTF0jxVrn8yy/7m33Z4b3Vtk2IfThwC679fWhtok3eO6hccXa9v2hz9hRfjtrLJVtmpqWh8UpNAiy05cFfKKWi4XK1yJYrFKjatd25eCrWgh+T4wPpsnaz06W3Qo0+aJMQQozLXH0OceKOc6AOTXLj8Q0aqJhCnw8qqNdKjVa7u1M0on//u5Kgnosx41FzZXawBnL0+ztYPzQY9zgn2G01T5jeBe85+WEiI7xuZyMQTH+rXKLQUmPwAI1R92LCEKfHwlcIhzrl62EtB8QyKclXZpgZCS/bMftaI7cgju/NlXJCKZCGEFHpGN4AvwvY6KhW0TI+Er8YsRQTD7NRBNKucJYx1iHR8OJ9xiQnBf9KDaa9uW3jXbG1HG9RXv/XmUa6AQ9BCPO4hmz/xgdnLWDoVDM12oYmlR8FWlrZRXQeXw82DEm4dRm1oKBRyaflGwvSsk4SSVkDDP1KcnrLqa/kWwQeeibXKZ3tw9/RGEqmtfyezRHL7fCbjiW9ExUi/JsEhgBtOKPyVbxu5PQ0DTNEf+VwMzi0ETPWZyrHXv/CyNINRQrt9i52toZjcvxy8aygHSjPffNBDiBOC3dCoVmScaW/0DbElTf4ww2wjziz06UpAM6xwHPca5nKCrNlI5dm7sRYJyLGZrwoztRVwITFqjes5n7EhyUu6IvjziLM1l4lKK+wM7lriH+jDiuWpmfpqhqrqaXmRnLRb9bLGF0qXgowN55XQTY91xiWGXHEhsEcENeB2m5d2WF5LITR75m9L276jgm7SDR/fLNJUwAuhWSsyM7EBvYckxOrDT+5ahTs6NgDY6MQFHXGfpdsMp9t5CayHreqhSxxatffVScZYCyW1LDo+CYp/x56RjJl/YymEl8LJLUNoRMGq7o0oiDEwgDw0gW18Sv+tT7wSuhiLpMxFz3cSyoV4c0g5ajVX9i0KXDe7yHew8ZpeNwwp+k1KHovYwXGrK3vMXqWYeV+wdB/hlFZHAjstXQwIz6dJcYD0OOAZkGwDGv6eVGKpZwUOeLK6z4+nYw+rTqc5zUVGaI65k3ky28YVfG7APlpx0DS0TMTYQ3yynfnGbjdOexktWPpoM1aO2dIY7HilEPtTovW66u4cskM3aLMOqO4Guo2bKXbrHzoCMom2imOygecDSGJJxYxaNSjpPvRMvEMKACfDUvGQNj1XpML0xnCLiwkT5e7RPvUJQhiVKMdWpUmVzL03bE7PCZjkaYyIT81N1TKbiij2GPHw/yuvWAZJWNurPeYsB6FAkjK0jpm3eCAxNcZpdYIViKTffsTl9E1pTPNiZWX8+1yUca6HVpsR40VA44y+Tj49oG6CIhBCbkfm56lt6AtN57sX4foTw+j2odDiAloRu/FWNBbrb3pqNX59/IxwQZAwN0CkUxT9yLTZZrOejxKq2LyiGVNWbYZxOwmHeaQB0GcxWg7y0pzxk9yPFIeYzXj1pf8xTKtqJ8hN/eZYmUgCaQI9lZDxHrF6Jkd3Gca1njIZWT1uOemAp03jGHDRk9FSqU/H4NMgPZIvtX0iRnkErHTcifASwYrGXdH/Cj7unR9o/NQQwZ+lZ5vuceArehzEyJoeI7mrIJR6zGL5vlt0zSxUBYHHNXJcgNr4ru48oF7YJlmahX65XvNZXVrUm/5wDjN5zClP3LxzYrbO5JeS3DPps9yR6GxH2jH63tiFvLfMjhHJMx9O26Hhu/CMCqzeZSogOj5cxeUBBOQk6OwwULyuEz6YwknTaOhpL4CCmPSvEiOdw2Yd/W8j7tnMmh6RrEQaRA7yu1/IElxAhDDD7mZJDdskXtgNRR0g7jvqgLBKuzDhX/fvueyviOejsJLuyatCzcfSPRjAhJ3kavOuqrraNOyXt9fMjr/DYBs/UxtwDULYpWh44hRuH0kzkWjky7muAmbNWVAQRAqx6jQyxb25XWR8EDsNvTtRSz1VgQBwRlbpUbTczUpATo+SSvXtAq/WCh0S+e4uOhI4XFiGco6uWp15qaV5/0cnkH8i9dJwNELwUrKTMQbdPUDnNTU2yw3A19WOqbPlM7LmvUnqT/NVMrm1xZe4RDfk9xbgd3ce/7uxwq2TgHWK8ta09iaDmPJO79maqdVm1jlpSdOS1mRaO4jvqX2ICIVClVVbLym5+TRskgPKsp1nVE0snlVxlkfI3zFBZ8Wg530rYFJyWmsGRv11s2cOrrofvrX/7p99e//Md///0///vvf/3LP7///6DdVf6X//un3//+9S9//5///Df9L//193/927//y/v//kf8u/Hf/e3fv/8MfVYlu3NqlEA5is9xCqYvSB0ldXtsoYoRZTzOsxtFLsJ87NhHGhsdTGiitqWaR6HEZbwUAhn1eDoQdQJ0Fr0K2DEl5C3yJN4hsgK2ULykBrXO39CfOb/YLIIVpzhfMUaJb6g8SjGPeHLqhQ1EbI6Wev8D/QOriIKPIM0TK4iknVTvczuOiBjtntfI6Y65Iu2kyYXmOZCha4ugmz7UjfQegg293/6eJcQ9PSHiSlTLKJDP3bCssNs2fuPdtPGwMrjUPVsZwMfAZTi5/llKO4mUcuvVo7SOE33zl6LkDCtedmyObFyxt07aXQQkg2V+CXqTinQW2f38sWy1wxcXX4ePDkqd7ymJjZlGse+hPrYQocfpk71ojX0Z+dVD0U1azoppsa/8WuUAf//JaPsoEExLtmOEuCEw+iI7hWqLD3hzywuDvkcfthQf8YM1nmB1HeDJ+QWNmnW8HP/ESM/4RPhot3mgM3SL78cR01B2+FOG49+yVfhVPimtfVkadI9aKlcl/432CkI+9vM3R+HNnz2Vs6YhfNyIs/hUHtq+7Sdb7rvHL2356CBxcZVwTKrBmRpG7ScB9gdk1/c701wkEuFIOMlb4Rcjnu9jijFEjInK45V1cKBhhPqDhpxDruDszs6RB5JP3tHVSrJ7/2+jpxbGuvgHaY9eQF/OJQk7Kn69+NaMaDLbvlclC8PCpkFjNBq5Mfg+uzAzD0/jfkflnmEVpaFBjCWgioWl0zKRWKqwOxh525iZ8EwrPhjuRvO2X/zM1H0RAVe/PB7YM4+m8zBC4sp9u7Di1VPfv/B2DBWnAsfb5gEdJl4dDmn7f2Ny8P4rjhir2qbG59g3UjxR/q/h4J/oHPUOq+waP0gf/vJCNsbT+D7leZO+A1oZKUcqZGqBfF1Sa5u2TM5yyV5xi+YTn8LbO4wtkyd9wgc5oyx28O83o3NB86s4Ct3mxPQlWvz34HsUaK3IsLaNk05l5ONoZkDpV9WcUUqsB9i/oqdh2MQBVGVSip968MIMj3+l+Hm+Ww6ENQZx35V5Bzd+Fwpt1KMDDIUj+RBsRdrurB8NEZon9UHmignO+7JueFVcyu/71jeKM8BAUaJp7jjpDPgpTEibSlF5T5Fqv0NUNkSBbnBRJd5xfK+hZCJgwqaWGVj/QrPxljPDD7OSf0IWIMxPqjK67ys4WlHMSfEmrh0zyd24FIBD1gPwya50FTJ9I+z0HFWpoUTeB0COPDkc7++z6eFkK3qs3pfFGp2Qq8aB/Fi5G0CawUm0FWvAKqrORIMZu/LZ992OypzX/P2F8sYo6tDcPQWosPVVNsBZ4u6wqjhr59nWec10kZf2/alZ+qxzlVDpKCY8bfgaMmL+ZndZg4jk96t0Iiqdmr7Bvknn0Vh+F2O8Uo+TIZvdUGJ4vQetP5Kpid37+m4RXxaWuwTKei+O0a29b4WuvfceBX32/pef2Knq1pC3lKeAGfSarnqzG419vWYYGV3QgzFcEkbW49tO2tPw/sYV42RWnBChuSV/D4oicdL37WncEnrZUiycx0jpumvttd/weSzsdleIwnf7cKoQlFI1DqnQRlb7ChlmpdBO36/LX0aEgRZufroR1PvYnZYimHLWoH/fYUqgS7rUVbaEHwxHvfPwuNR0lmxxEJhUDnQ9jBhdJtEFTpvqssvHj9rNn8T6VMJor58dX0v+DkbiOXSGzbQPJHIX9p3FBBfXzvtULq+PCArZLNFggPon9ded5OPfFxYdTIQf8u+k4z7M5bxJRGbrTNLNgDWGN6nsoE5sD18hoAyBSv6Drc+Z3Uikl6oHFtn9ORUY05mBx1VdAsMdVELvVacssKnF3+5WtHKhRhmi93BeVcVXaOYc84x44vsyWR2WWEDeomn8GDVtfld2gvv3jPPUEHjanusEDqkiz6a0i6T5uab2O48mVxWm+k1synrCJe4LTs9a5whjOBfvwHuW2cz/HpPEs/bqKKnGQCyuU9t8iqIGokQ2hXLgJg7jWtZoOwi0MfTaG9X4IYqOBZnsiiFx7wfxWJUtI8X5ALQO8IOj8mjJ+vSVNUIz8TRaSi/EZDxgbakIjaJjqNs3ExptTzwnm4AaaX9xhukR71h0VXJoWYfNhSZiFdNuY6KT61d0w6PT+v778YdXl12Eh6g3s+onV67Ig9v8KtUcuWMqycZW7+r8bNulG9h/hEgaSiCZ4g00PSZcORqrfy9SSOYUGryx9u9RqivWLrv3R0ci4wOa2KdC8TPND24c8l8nMEgTq7zzmrc8sky+3yan4oA0n3WprS+DaokV9HzTEgaqU6nBTuUrzx7Ux56/qmy30Rms/0NL2DTwJp6gfUe6cGAhVMiegRTRU9uZA8Qro2q5Dy9Icc+X7FUmhPVMJa9XHuWK+v5evDUAkIpUSWYFMX0Gei3XNogxM1eujv2umMF9hgMj0eeqjCWQCvHS+FSMi6NwxG0yeZyHRWWZepusueZz/aFJexn65mK4a3gXS2hlNmwsJoglXgu9vs6L3IWawK2D01cGBtroGDO+74Uqtfebi09opounlU/1JFBZgdEks9+CZPz+cs+XpBTQg++iYGQTaVdBD7L0J4c77P2FtWfRlPPMGRjx8TbPuWl1QzCPEA3TDb6vVzir9/uhKcnwS7dkjiSmKioNng8zKPYRySSer/opCk8LBFZljZ3OfqjC/bL0K3YV6gRlBojZQtVNbLCHacpUVu2kAtGT+IkKL/fIuiIEhiJENYJ0qHgcqsrnZ1qIknp2qRl5nascAeLULhLTrzcNiLw0XqDdHHw6fF5rjQ8eDFC5LsPHpvPG3sfObAWyN/RV6qVj/vPU70MMrSS/0Nf6BoZIIuqcDCV3HPP71Snx4Zd9U82PL14uu3BEeqw8r8vAuPi38Wrp41LmfJVVTWlVoE/skAicXP4+tASTO4/T5TZZ2AiKytus5cMw79ghcuD2gRLCqJjhLGcqoXvL50HHOdue9v0RwbKa5RziYGskY5+ioIsSwnJTIe0xhu0a6bhQk+ylfd+BjLX6DjzaYwMfP2jPO7XgJwbv/lNiIN3zOenjUisqShSbV0js/dpg9rqznFKWojMWYjHXqzLk0DZa8wreQS/xUvSHFFu9f8+5BuLRGe7rRVRo8jCGbXiFK/y5qr8GI2R8vTVBJ1Udgg41rvyPq0ZAA+3ldwFFZ9zUzpkh0RbQ412DpfAnB2QkGnIDZ2Jmzqy6GDmEYW7FeSHIjZTbU1Pj0b9nOSFbtko1hoW6tPmY42SIL2rpyMH3Uvlyd+0Qj5COfXvJV9B30Ffz1FWh6eJjtXokZE2lnQ8ogEtIOFzBsEl+kgY+6YsQ8wwz22HI1Ri+f8XdRADLJGVLIx4RAvV56DBMWwSpJ6jqrpmn/+WRmhrUy88q7dE34JzCXmaDxKVtDA3ONxyHvz1gpanZBf6nl8GH6fvfdM+5nz3eJKPz7fTSZpYigX5MvtD8hm6+OFdjGAzwvS+T/t4zgeP7R4JapHKN6wEXaRNHWOIs6W1Vt8egsKVx5kRxdTzMwIQdJA6q0Q3br02C+nfyLcJkmFlrexV6bg3K1cdGFcJX3/WbNKpv/ue14deejzlNKsPujTfQk10I9wwlau/mLavdbnmLFbBc71YjNsLRbcWcRrOpKs1EPBo29DzhMq7fDTbRYapWa9sMvRgobyPZhq2uIRpdjBt1SzTvW4sSmt76T+0pQqx431alIkDq3d3kax/TY/NwOi8R06MQy8OOQMSA+sRn/Uab0TO8TxznHlykFMPP7MX/SJ5KuVZj2oqs3IwixOycJVImTYXDUK67UV5OLZ1iKSIfjw/MV4swJRFW/hYFhjjm9dMCoQ7neqemI2yYqfGodSlG/+h2B//l+4i8kvJVK8qVZIPuUbBY7wrncSfNpNht8rEa06P6obKblTd7ceQArk60iVKej/jdYkeXRZiK8mdeo/zYaMWvXJI+dVI/sZ/4B8Mr8WhI4Bjq7iIyb8HUezZ09beaJ7eKabZkdSoVTkRcPo66KbLIREcp8rdISE0LI8f/xqHvM+sjfa3nlC8UQ/p8fD3FvmtSvogBiajw8Tk4P0AVr5zv1tCT+85Xq868apxd0IFhfGdJUNmUN3duOTJmT2EQk0QIYX3PKKmsnjODD/CBly69esfCuC4euw1k5U76RlqgGDu9x7CNGu6QxADumRLZmcIJfcCs96Jb10U3hfkKyox9BRhm0jms4p6v9ZsSpEHeRb1m9Yi351eymwOWMfQ4czYa64ivSJ7cZqApa3xDAEYp/FN/pRPCn6b5Uh1ITsJlmMrWeNJ6e4nkUS8jUv5eoShdf/KGU2nPckQXcY4wpbVMLO5TvXhqzOYkKO79VtU2P2yD4lx8dt2DnmQxj3Lc98N4/OscsnI54sUyeYeIykr1+Gyk7ESrRwfoFQje25gb9GezA4pX7LqHoYasds7aCG8hW9yzpBhgxJIj1o5poyk8GqyfpKQo3dgqlKHhmhtNJ2rzKevPDFslk4aZHVUB3Toz08t73TM4zsfOKY6bXXv8oeDHDsz6G1HqClhnMc51Fufbe9FrP0be5pjXMCKm2OwYtN3AFpvPUkXTc61u9dtTkOez7mQPxT4wvKYOtQQu+g0O4WzQ1CXPJzEQaNeXxo4V0jjY9WWis3KBZPZUfMTjrLjlxs3nhNd8tXPFPebLSiwWd1rV+dPI8MmnkgVtnR4QVsvRYc0xnKdxBWmnWadJnhF7dMpu0ue9oPdAbvjgr8saEzKytHwWBwdBV9OA6ZlbCw137T2cTL+IJW40c29DlfYenMFcSRL6Ru3Vr1PZlGSXa965jf1oyIUYcr+hUe2zdy1wm6JKTh8Yj2n9XuJGqJOQ4nuN37bM7cgS4M+cdz/EHsy7s2dsKDtVr8/1hwr7fa3sEf1hmYpV2fz22nRS61kbOChDVK8UKqDcWRu8TQ8m+lhy1UvqMJDxru8fKMYwfeCjhghOjVVXdHy8NaTcqVYIhlkM3Yc4oEJTn7OXAn+O61ZAL4hCqFgnMb0zU5+Jbt6flaMS4g/N7IO0/YDt3/NZT2Y9zut0SJEHE6uqMrcQLQ2/ndJUNl6JRk6erk4ChD3oTjvlL3uS0dquQNjT7to5jpk4rYyLISH8UZyQng0FQ9XvvGqUjjQrYuEiQmRbUp36AAi6qc/ykg1D8oCGo0kGjYZ2Gx5080rBM2w7o2QoQeM90znDRpGI7tQTCmoc6ZsVQh3AVft+Z8w137u3pqNGmESvjmubVcioGFfrSZESS4PUtxfsbXD5qOXslwgm3qr3m52WO2MgnmekSORGTCofQbtgCOSihazrwbg8Uzqn5VTeL3+14x5hRN8vdIFL2+c9iP1VSoaxyRrAX8/ML0nLNL8nkn35Q3f57JV0+Hro4qabG9Ij3qe8rx2NW/W30pjEWBJ401sk690FFZJOtQ/WMB6l6d2ycj5PGUr5hRBp75ViCB+U3fe/Ud+CGu88vzLLalJn6cMCb5CpnmQhizKOxaj678mT1uiK7XYqyhCdJtZzP7NXbOINQlCZbmUkC9Qkex5VWTxIU3PVbrNHplP+rh+cq4tzYqdQLP/kz57109iYpRrzj5hkvl2XI5GarJL5fS3LxqtJmte7WZVxRUQ10VUYxlYypGDv7zo/PCQtQqALxkYKYKQv72WaTshGFKC1fdlY0r14CRGEbPU2LhZinV/9hPU95OAsfatyK9yH6bu7LYu/hp/17aKZvsVX5+a3fWkfbD9itcFR2oBfxqDksYhDIz0f5oEgYOoT6wn+74eJ2H6gdKXGFbEeJaT0iOmJ29Jy0AZya58OARoUHOcTcMVfH4rSWC/ajhlkAC0s8jaoZamVPJZdZODUUzTEIIsUr1ktIhUa/X15NDSJ91FvgjUTSK7R+KxpYdXzqQk3PmhmhRR+ApWwnHgn5eTQ+MQYZ66RP0Ny1PUhoSzGFE0o7cIAhowIen82tyL2BRlc554Q9xCb5Xv+98AG2VckzZieDkuvSV3oqrI0TVEMJiq4/JEjpSLxrluBYKxclGSsFR6j2E9sw8ptpqtyaeH0Y17ltJURo9j5nZ/sm5niuGSNj4xRiSJoGEVOPZVCjMHpDWfoW08W0+Bl7ft27miVyxl3V1KJaGvtLgZ2NNHSuR5/FG69qzAEPcjRfDsAsZhHqTIg3UgOYXzONC3r/Wp8z9ZYDa6vc1AkU2Tbvi2sfpsnyeUe37e+XhA1yA7sSesSpWoqpce1ZdEwpuhYHdWw6nynSMRXk+o3F8Vut/K52mjq9/H/JULwsI7uUkzZPtiQPC+Im8x0HyNViXXkYav6FRXGMenBxqeURv",
"part_4": 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",
"part_5": 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",
"part_6": 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"part_7": 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",
"part_10": 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"
}
|
{
"ground_truth": {
"compressed": 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"
}
}
|
codegen__primeintellect___1971
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nJATC's math teacher always gives the class some interesting math problems so that they don't get bored. Today the problem is as follows. Given an integer $n$, you can perform the following operations zero or more times: mul $x$: multiplies $n$ by $x$ (where $x$ is an arbitrary positive integer). sqrt: replaces $n$ with $\\sqrt{n}$ (to apply this operation, $\\sqrt{n}$ must be an integer). \n\nYou can perform these operations as many times as you like. What is the minimum value of $n$, that can be achieved and what is the minimum number of operations, to achieve that minimum value?\n\nApparently, no one in the class knows the answer to this problem, maybe you can help them?\n\n\n-----Input-----\n\nThe only line of the input contains a single integer $n$ ($1 \\le n \\le 10^6$) — the initial number.\n\n\n-----Output-----\n\nPrint two integers: the minimum integer $n$ that can be achieved using the described operations and the minimum number of operations required.\n\n\n-----Examples-----\nInput\n20\n\nOutput\n10 2\nInput\n5184\n\nOutput\n6 4\n\n\n-----Note-----\n\nIn the first example, you can apply the operation mul $5$ to get $100$ and then sqrt to get $10$.\n\nIn the second example, you can first apply sqrt to get $72$, then mul $18$ to get $1296$ and finally two more sqrt and you get $6$.\n\nNote, that even if the initial value of $n$ is less or equal $10^6$, it can still become greater than $10^6$ after applying one or more operations.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIAB/8N2gC/+1a/Y7bRBB/lcEKau4Iqe04jh31QBVCqEh8SFQCVJfrXrJJVrXXrr2+XKgq8RA8AM/Co/AkzOw6F1+bFWx1ovyR/JHYs7O/+frN7J50r70lU6zhypt739ei4E+k4nnOF8obeatWLpQo5aVkBUcFFAm55DfePJqlI6+sxVpIll9WdVlUhPBDmV9zUBsOqzLPy62Qa1iUS/pBnaucF9A2",
"part_2": "9EYqKFnXrCjoPWdy3bI1CndqU8p5JjP59eOnXzxooGBqA4qzxYbXwPIt2zWwFte80SCLnDUNNGXBQaDnNW8U4elNnUlaRl2maMMOlqV8oGDNFVyVNV+O4Wm5ZLu9R9pH0QBruhCaMXyF1iQwqS2s0YuBHIxgV7awQGHF61VZF29FXaKYUe4a+JXXJZQ1FGgOFKa4mQMUbQ6Dm8GcHpSocoHxICxc7UgM",
"part_3": "wy1Gy/UjOYPW6yuhalbvoCobodCjvTdnY4DmVa3mUPMqZ4sOaCswA4Mso6XX8g1CqhJYVeUUKmLeOji6o1W0DSaG96JFfKrGz++G2/B+mIxKJXcmQnqjBOXiJR/Dj5R8YQqG5RZFW8A1y1vcvzLJ1OUheDK92Ah+zZfowxK2R7bKtrjCKuDeg3mEKPc7DdodQ59TCI+ritVcqnw3AoklkZTDHoteSiy3",
"part_4": "fmey2aIFVZpcdbwYYYA7dHBf+Q3PK1IvNHomP6XPE1m1Sj+R6CmClRJzngupoyV0QSrYF1IxQYkDaomc9+kFw0EAWYZCaX4C/5d4cPbnH3/99nuHgSRgeZeLcc+B71rV9wCbWiLzt+UeHtnXT2bf6NEqHBp2yZtFLa5Q1i87FumfioPMfNUKaraen1/esKLKedN5qvOWydAnBRNDJgMfwtulaZBE/cUY",
"part_5": "oh7ct6Xit0E/MWVdiRrZzI2hQ8fuu6BHX9OP0wGVnEbDIPD9wT42qfurtzQY94w0HCu5fNeKMW5s3dk/CzXheWc0SHpWwzQ2Zlc0WMlLLJweHBqCVghfK8fGDQq8ayBOc0qs7hCk32fUSJjxhqYRVoSRdeLVCISpOw7PPMfqL2iermvOFHXBBleMIrAVSXRQesoRqbvJdij3eM98Q/StwURwPAhuQ2g2",
"part_6": "ZZsvsbWIniiocUrnra4FZgN1S6qxCXBLa93Bsp/RhFNz1dZdB5dLPsbzqeYrHJxyQcfVkq9AiOEZniaAn04b7Q21Y8Ozs0ySTvGOTi4aNSxYhYpqBJ32uMExTbu6bbllm9DA3/wEF9i1cH4OU4pC4is5k8kVW+Az8rqq8ffZ80xuNwJbnOTn+vvRBcgOmVR982i0JHysdS5Q3ukYvU/Q3OFdwsOHF6Ro",
"part_7": "REiKRU+7qsdYQy6XwyGqjGBBHtMCIRsg3CHhMwi6Xb0deGIEpI8aVd0tFzfoZ8FuhnQG1lCNQM/Wqu5wCwofR4R1/SaEW/8XyIi3oqb1R/jdi4FE5zqPtznAfYcs4AxHFC3TNUcXPrqgXZ3JaqkOJu861c8UaqGVKpM8b/j8duuoww9G5Khm8XAvPkMeaq4gB/HMFhLfO9qe7kinO9LpjnS6I53uSKc7",
"part_8": "0ge7I+1BGm/+zHvx4oU5T8yl5nRfOt2X/vP7EtUbeeg9H3kKLyfIS+/Z68xTu4pn3hwyT7fFZUd4b4QSzTGziOMQAbS0NGNPi/Vc9N6M4N8j6el5DIvGqBsUzkb62DxzhUvxM0uPopklzKpjrNM0mYX3FG04jY8ihTBxRZql6SS+ryIcTz+YsjhBzZI4mtjSFbvmfhJE0XHnJjj9HMHCKEwSS/pdPYv9",
"part_9": "qZW1SFvXak7CZOofp22cOqOlsX+8ArTg3ABBGsd+YqmoaxHSJPSTwNKfAU5N93ZPJtZ2TybO0U78KD2evCgOnQdlGIfI4Hvi3CT143B6FGzqzBGcu6ll6PruQzKyj93o/cYulW+aWCs7Tdwra5skUeDeE4E/tTX/1B1tFlpqgQvOaGFqi1SvuHsXh7ZRN3GfdIgW+ZbzRi+5xzsNYwuiWXoP7kW27kAu",
"part_10": "uw+pJEwsAzmIfPehYj32XR2z4TgzxHY6uEZmm5Wx+/XIMnOdQ7PeTN1H5FEkdzpNEyRUdF/nsb2zndkUWaoX+LPInQp+bD2gJu45C6Mk+f9dlu+LpRPLFdmZoxZ/nNNtuaT4H2hAzSyt54qT3NMfb6mlXsEHm06BhdXvcV0I7+swOM7qwJ3WgWUuRRrpOf23TnPZSvGq5d5c1S1/8zeht9kQ7iMAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAB/8N2gC/21PQQ7CMAz7SpTzDmlHW7qvkGkXECChDnXtYZr2d7IxCgJ8SRw7sTLhOfY5HLsUc7pggxPjNdxzGhgbODBq531tmQNjBYyqdF7gfKGWDBEVaozfO/1e038uKFqx8nYZ9Dl9JFvYbT6gr1QZPBVFUG/5L7cF/bsmPpHbGSsc0ng7yaMxS5kfer80QwABAAA="
}
}
|
codegen__primeintellect___1975
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given a regular polygon with $n$ vertices labeled from $1$ to $n$ in counter-clockwise order. The triangulation of a given polygon is a set of triangles such that each vertex of each triangle is a vertex of the initial polygon, there is no pair of triangles such that their intersection has non-zero area, and the total area of all triangles is equal to the area of the given polygon. The weight of a triangulation is the sum of weigths of triangles it consists of, where the weight of a triagle is denoted as the product of labels of its vertices.\n\nCalculate the minimum weight among all triangulations of the polygon.\n\n\n-----Input-----\n\nThe first line contains single integer $n$ ($3 \\le n \\le 500$) — the number of vertices in the regular polygon.\n\n\n-----Output-----\n\nPrint one integer — the minimum weight among all triangulations of the given polygon.\n\n\n-----Examples-----\nInput\n3\n\nOutput\n6\n\nInput\n4\n\nOutput\n18\n\n\n\n-----Note-----\n\nAccording to Wiki: polygon triangulation is the decomposition of a polygonal area (simple polygon) $P$ into a set of triangles, i. e., finding a set of triangles with pairwise non-intersecting interiors whose union is $P$.\n\nIn the first example the polygon is a triangle, so we don't need to cut it further, so the answer is $1 \\cdot 2 \\cdot 3 = 6$.\n\nIn the second example the polygon is a rectangle, so it should be divided into two triangles. It's optimal to cut it using diagonal $1-3$ so answer is $1 \\cdot 2 \\cdot 3 + 1 \\cdot 3 \\cdot 4 = 6 + 12 = 18$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.125
| 0.625
|
{
"part_1": "H4sIACb8N2gC/+1Z247bNhD9FUIwELvxGrpQlGQgD0XRh7ykARqgKKJgo5Vom4hMOhK1zjYI0I/oF/ZLOkNJ692GRBsCfSnW+2CJpM6cuZwZGfs5aCpd9VwH2+B1J478pdS8bXmtg3WwG2SthZLXsjpyOABLQjb8U7ClRb4OVCf2Qlbt9alTxxMi/KzaW070gZOdalt1F",
"part_2": "nJPatXgF5y5afmRDD3e4RFY2XfV8Yj3bSX3Q7WHxTt9UHJbylL+qgZSdZzsxS2XpCId3w9t1ZGTau/2SpKz0AeykAtyyzstat4Dyg1veUN2wIcsogXRyhwQElgM4Fh3Vbeq/nAWPSeqa3i3IW+Aie4E2m8rdJaoHRgbjc6mRA9LECTcGw+3YK4f6gN4UmnCK7hCGvwTHj",
"part_3": "G387nx4csmui6k0KJqZ/w1LnbmpFTkVInOZQjOwaZAV3puckMOFT4lr37jncJ4VWtSycaY0UqDEVwzTrXtA0ywxT8OsA0xwrPzKbx+5PwYojMX+4MeY/M4XACEz/TDEXfxnD70j/kLDfGXveg1bqzJ2XirLbBTvBoulYZEVv1cKc1Qm2MmxQZeANic+Q3Wyw9VWyOpERn",
"part_4": "KShyB02ShOioos0sIJvb97PLsLAKV8go/L+Vp0OYKlzAIO9H1mrRCcvRHVwKex3JG0pCSPe9MuS0XCSlLWJTjVxqGixX58/c/jCU5HG+4SfB93UJ94s7fCvwhl58G/ZAMKFVCOOTF7oz+jW4/zvQDgz9+qo4nyN1k0sSilAnuj1xKyfBm2qAPN6J8BJqgXkEq75l/X9cg",
"part_5": "PNMCFPlFfBDbe5FZy6rhNfQW1YuLNKfzc2Uve4FM5+UVWbxGxQP815JdE7EhfLOGTEpDwqJq01ZQg6ZLoLIucoMnzI1QHRw8KDgwyIktmN2MERkboKkVPobxYYmN/WC2tya9gmSRRslnmkgORQ/M60GjaHZDh43BnDEalf0Zco3GIiitulGaxPNFQl4Q9ogCUFbQCZwcO",
"part_6": "nDpQgLs9Qc1tA25ATriVjTAxcRRn9UlPhvyUj+D+jlpcRy7x0R2bOwNaNjkZhFdJQvE/QfSz0l0uZkuKLqCOzFcRPno1BvTN6HAIENQz0Cy15BD0+zuYFRM5E9GGrDQgfF2MGUDJOGswtrEv1fqjHvTpJoHE+J0XA/dGDwYW3wDA6/jO2hWssb5J4EOoC8NjeVqVUpwDt",
"part_7": "bCUu4UuIhC7iBMfBmtQfxXJFrBJCPwwXPPX5ClQK9W5LvxKgYEw3cJ+ysw1p9agXNUd9Bb4H7i9jRZnybr02R9mqxPk/Vpsv5/JusM0gfbt8H79+/HAVXK/3bKlhJMBe/WgebQNGGyvv1cBvruxMtgS8rAeH49+RSsYcXQGDeTEpw0i2oUpFllZvXLmvx7IGoFAnV/M1J",
"part_8": "qRUo8kJjdOQ+kzO5dFH47VG6HYh4xL6xQsU+oJk++inrsheUAS5K48MKL7Hg0SfzwYjtemmRh6INnV1HCaBwyHzy7mJKMFpGXvy5JpblfrdiFlRSsYF54dnnRME8ir3zYNUajImde+bALjSYR84qfQ2yUJsxHb6lDbxSaCqM+CqGFKyNFHBZF6INIHYhRTmnsxdHRFQqa",
"part_9": "siz1Qcxzh06yJCtin6GYu5QXxlmeeXF09K4siVnKfDKTFY7uxaC9+vQbmjn6Q1pANXrVY+bosGmcUUp9MpM5ZhRlYZaGPhxZ5ph64HWY+GSGOeYAjtHCq8KZQzNQO5nXewNNHZqJQ8CLfDKTOjQTwbBnfhwdmgkzYJj6ZIY6NBNGWZx5VTi1ayYuIDGhV3+0Ox1Tlnt4z",
"part_10": "OwOw2ikPm0sjh1lU6Rh5vPOFCf2DkFjmNE+Qx9e3VzxA+n5iC9hzlf/KMpzH6djh1SygnlVYRQ5XnR8sOz1l2Y+b3T25GY+MzmyN9XCp+dHiT0BeRyGPrKICsdPOhZ7JjSxD6Uc0uCXCHuFwC+TxOunSWJXGbzNxLkXnj2AMC6jWbPv8H/+/fUgxceBB1vdDfzLX68P6w40IAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/1WQzwrCMAyHX2XkvEOa/sm6VzHDi6KCdNK1hzH27laFtZ7yEb78ErLBLc45XM4p5nSHETaBR3jltAiM3UlAoREJAn0nYIxv2FVmfbDSqvYtNQ42zhenD885Nds0G6+GQ9SomNjXBnnLhNQYlti0t5QA/ZfAg3K27tbGIVusBtNveNqhhyWtz2v5Qsyl7G+TQJKXHQEAAA=="
}
}
|
codegen__primeintellect___1989
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA string is called palindrome if it reads the same from left to right and from right to left. For example \"kazak\", \"oo\", \"r\" and \"mikhailrubinchikkihcniburliahkim\" are palindroms, but strings \"abb\" and \"ij\" are not.\n\nYou are given string s consisting of lowercase Latin letters. At once you can choose any position in the string and change letter in that position to any other lowercase letter. So after each changing the length of the string doesn't change. At first you can change some letters in s. Then you can permute the order of letters as you want. Permutation doesn't count as changes. \n\nYou should obtain palindrome with the minimal number of changes. If there are several ways to do that you should get the lexicographically (alphabetically) smallest palindrome. So firstly you should minimize the number of changes and then minimize the palindrome lexicographically.\n\n\n-----Input-----\n\nThe only line contains string s (1 ≤ |s| ≤ 2·10^5) consisting of only lowercase Latin letters.\n\n\n-----Output-----\n\nPrint the lexicographically smallest palindrome that can be obtained with the minimal number of changes.\n\n\n-----Examples-----\nInput\naabc\n\nOutput\nabba\n\nInput\naabcd\n\nOutput\nabcba\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIACb8N2gC/+1a3W7bNhR+FULFMLtN3CZDW9RABvRiAwoMW4H2Zoi8lKIoi7ZEKiQVxWr7AHuPvcPu9yh7kp1DyrGSWO7MesAuQrWySB5+5+Ph+WGBfoxSaqnhNppGb7Uo+RtpeVFwZqOjKKsls0LJC0lLDgIwJGTKr6Pp82ffHUVKi7mQtLiotCorRHiniitObM5JpopCNULOCVMp/oBMUvCS1AZ7KAI",
"part_2": "jc03LEvsFlfOazmFwZXMlp7GM5WtirMZJYQijwCklFS2AAGjjRGREWKI5TY1DM0CRZDBFCp5ZYhUBdrklVKZ+2HdhHOcn5EelCb+mZVVwEkdL2tJlHB3Bp1L+V8eRWxxHpVjmVBS6ToRkuVguRc6kSGpdCJovRYmCmm/ImSOS1LZjbwCAJskNmFh04lLZCW7zV1W7/lxccbneMuxYSSOMxY7KCNiSawbnRH",
"part_3": "6iMAZ7sJZrMyGvLVGScbICFEYlYblSIEXlilTKCDw9AvLOQh4aabAc7M07FD9P7WYBGAkBFKzSPdVefELewXSGCzllucdan2nB5dzmyLinMVXcyG9tp9VxzoQ2tkfa0TF4rt3OkBRs730ONlmLVVyXtfX+pXQKBNAynTw1Tq6hEg73rZOkbjM32lUtLYp5bQC+tr7JVV2kRCWWgtaejzUC9oLawEdFSQsi6",
"part_4": "zLxam9A3ritwvnhGRp+xTXINXRl0Iqp8pZdbbTMue0sdS0YBkCVC/TuFRnRosppwq3vj4kp0evBThtKzvjOeLCgh+oIitbb5h5Ld+YWTXlLrrfTe2yca8byGNsbWdXWfeHQe7S+BPWwmKObotXMxnFHJ+Tv3/8gn8wn93v6158nz357Pr7j0B5hwKt7un+pbV85pCg5ZL8t5vLWR99JeHe+kEX+xbH2GPzg",
"part_5": "k4TpODhjxJLShKGI5wf9JKHY702nt+eZF0DzCRQCGkWBvIyFBOmOqHegldsoDGgIi6JehyXIKoTD52fV4FyXcNf5FXE0t7X2QQ/Zl08gb2uegZNCpoAsLcpKachPKxPLR/CeOAZnquJyFLt6MLHXNo7GsXRMz25kJphv8dxRP6QLI0Dn2fmz2ePTFziUQVIVGLpu3Wg8Qa+oRmPI5wTaesU5RO9IjI9fvZw",
"part_6": "9OTvBhY9ISZd8bf4YalBZnZ3PeogaZ0anL9ZYkP9v4MTsm9MpwTUTWsEuEDyWTS4Kl5FGODP+/uQuCxwG7p7D/Znjk9nseD3lwCtVjZ6N7wwcn4z9DvyRGVtn2Q7eTmrEcj169fKJGD8e9Xbx9Onp+Ajon8WRt37m1ExvL+po35K8r+58OoUN7K0UXMVUhcBibjWEC/Q7z3oo7w/l/aG8P5T3h/L+Pyzvax",
"part_7": "ATTc+jDx8++DyLMA/F/qHYDysFV4lmR5GFuALXic4/xpFdVTyOplDLnBdcdD7piqY7aT/pIgRs4YuqDwM/gaGCE5+PyH5w6QAeCwGst4LV+wNZbFvBNjN7AV5fX19dXeFrK6qbcyL7QzcankzrTGfwbpomg9Zo/HajMAAf+Gpw3I06Md1JwHLEgC+3UDs8B4GLcbbZSjq73fS91nyx3V9zBzTIqRLGWDroW",
"part_8": "Ck8Ic6VUIAeAKVh7g9Ukzwv8qKeLxdztlxshwexeb5YFqxYLvI5hFpgrA3ELktYiDk6M2+3c9LZOdkfuG1bhX/8Q7dzViDi5OClQm1/yMNsB5i2tA1gB9tKBvm18AQdGKV4YOzQgeH9mA25F+ZyFuiz1EfzUDAjaZoGgyc7MwWCJ+HgPg3thHcWD1YA2AMe4iI6BHS4HAf5xYAHJzQJAcPnv3GyoSMC3woA",
"part_9": "vIRGfagN5NsUBC4v05CsS7OMNk3bbq/INGtaeLIA4Jyy5QBdFphs6EGL5c2yw1VfrB7bISGbrxP63pePwTrrXXR/UFMzxo3J6qLYdUq8MHVWm4IHHdgXMu060QYURtoesDBuknbKOR+8LrGUM47XDxrEmA67RQDnAX9glAXl1GTQa0NvBhgH9OZppWyle7lfsMaiXdAFNCopDlLZVhX8xU4FnYFTcA1Wya5",
"part_10": "VVbtpsvcNYF1DHb4FXxY65xgquujIUNVdWf+6G8muawPESujFIdmR6HB7QaDtIUNw110vNMX568ywTd1NKWjrJklMPlQ4TG7C/iXonsGrUpJ8TQL2b3qn7Qqy9Ur0OpfzviaIhknspLCVwUEJ7FK/Tfv+yhW2rWo2M4fZzY69bNnKwRQPq72v9QBKh8tzX5dXNMP/Z2Quaikuax5Nra75538AaKpTo6gkAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/12QUQ7CIAyGr7L0eSfYVawxbTHOaJhh8GCW3d12RC3wAOnHB/nbDW5pKTFccip5hgk2hHt8lbwiTMMJgVgCYkQYBy1sMYuEhjG3lQreYCYyID8ykzzcdfW7Lw3Vndw6nLNJS8lNTCb3XkNTECbHmHqDe0OCGPoTEXIx6zW30/hGJe1PrFMXc4cR1vx+XnWuqeixfwDx0fTRbwEAAA=="
}
}
|
codegen__primeintellect___1993
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nBad news came to Mike's village, some thieves stole a bunch of chocolates from the local factory! Horrible! \n\nAside from loving sweet things, thieves from this area are known to be very greedy. So after a thief takes his number of chocolates for himself, the next thief will take exactly k times more than the previous one. The value of k (k > 1) is a secret integer known only to them. It is also known that each thief's bag can carry at most n chocolates (if they intend to take more, the deal is cancelled) and that there were exactly four thieves involved. \n\nSadly, only the thieves know the value of n, but rumours say that the numbers of ways they could have taken the chocolates (for a fixed n, but not fixed k) is m. Two ways are considered different if one of the thieves (they should be numbered in the order they take chocolates) took different number of chocolates in them.\n\nMike want to track the thieves down, so he wants to know what their bags are and value of n will help him in that. Please find the smallest possible value of n or tell him that the rumors are false and there is no such n.\n\n\n-----Input-----\n\nThe single line of input contains the integer m (1 ≤ m ≤ 10^15) — the number of ways the thieves might steal the chocolates, as rumours say.\n\n\n-----Output-----\n\nPrint the only integer n — the maximum amount of chocolates that thieves' bags can carry. If there are more than one n satisfying the rumors, print the smallest one.\n\nIf there is no such n for a false-rumoured m, print - 1.\n\n\n-----Examples-----\nInput\n1\n\nOutput\n8\n\nInput\n8\n\nOutput\n54\n\nInput\n10\n\nOutput\n-1\n\n\n\n-----Note-----\n\nIn the first sample case the smallest n that leads to exactly one way of stealing chocolates is n = 8, whereas the amounts of stealed chocolates are (1, 2, 4, 8) (the number of chocolates stolen by each of the thieves).\n\nIn the second sample case the smallest n that leads to exactly 8 ways is n = 54 with the possibilities: (1, 2, 4, 8), (1, 3, 9, 27), (2, 4, 8, 16), (2, 6, 18, 54), (3, 6, 12, 24), (4, 8, 16, 32), (5, 10, 20, 40), (6, 12, 24, 48).\n\nThere is no n leading to exactly 10 ways of stealing chocolates in the third sample case.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACb8N2gC/+1a3W7juBV+Fa5v1p51EpGiSCrbKdBiC3Quul1g5m48nVFsOhYikakkJzEWCyx6t/f7AL3ok/RR5kn6HUp27ELeJpqgV3YyjnVInp/vfOfwGJgfR4usyWrbjC5HP1R5ad+4xhaFnTej6Wi5dvMm9+6jy0qLDRDlbmEfRpdJpKYjX+XXucuKj7eVL29Jw1tf3FnWrCxb+qLw97m7ZnO/oD/Yc1XYkq1reqItkFxXWVnSc5G563V2DeGmWXl3OXMz98dswZy9r9kc1lnj2V/y",
"part_2": "G/t1ze7yosDWKas9yVe5vbM1qxtfWJaxK/i8Yn7J5is/90XWYG0J/4LJws+zgi2zeeOrzVfsz76qcnj1FSN7f6jzhW33Fv6OvKrvrW3IgruupztLnba8ZlllM3pjN87fO3LxyrI7W23YdWXtYnPO3nqWLRtbwTE6vmRNdgMVdNityyss/JenvsJiWdtiOQ0eO/vQdEfvEXc4z+wDIig27IY1yFjNSl8REJnrcLV3uV/XzDt7zt5BcpcVa0uWbtj4hv2e8Qkj71lt5xUCzJHya7jSRuEdNCMU",
"part_3": "qCrP2ZsmbC1qvw1ylTXMZsA4eIV8XGVIMmzPswqRY7X0dcPcfljjfEn6NsGUWwT1FAg53sa5sEhMTrl2c+LfYsIy2kjWsI747ultG/nSr6tdQnJ3R7xbnIc0vs0WxWbahbF6JAi5HwQ7NNwUbGlYtS6hDQzKNjt7XXZq2nafberW+7lfFwu2yojjcL+Fez9MSl/GlvmDXWy1O990gpuAOjB9d+9bpUSduXfEuwobFvlyiQ8OkC8peWR8P4JxcKJeBS+utj7iYN564ivoaT0N6D56NgHi/mbP",
"part_4": "QC/5WjXlOaFItQYnsZVyVWXzmwNXFqACFSBbtbtq2hYQvu8QzCsiRhsjZfIR9ZbIK1vcEtVbq1lzzn4oLBoRwAp5t6wuMxABVLr1dU1luq8DQFOfChp2SaNMVq3JJShrOwoRcajgPKvX4K0LAc7cGb3euNt1Ez6RiIqF+hNsFXmbgJw2UJaaLHeBB7t6KdmYs8+//Asf6J1Hf+PJ5N///Pzzr3sU2mfQDr4yv141aFlE+kMOTVlW7zNy39e/rpt9Z9GuXRt34PrWK/foQZk95OW6ZBnUYeth",
"part_5": "tjvUgkNft7naVTHqftkBR2A+9hdipYNfTV4vN9tG3sI+RePZOrRLHbUg8nWnbj8PrCsXStVZGzPIXG4VsTPG98P/00NW3kJrB0DI3MxxWm+RmTkTbLnHz9uFRO6t8Gh/6Yy3Njor3/vG7iB+0xbWMq8QSx3MA6DaHgbZNUXQdxHqYNukCCyknnAPqQ634V65AQr2mpkpagbQZC1F2lzVu0NAZO8MZWPMp0xMmZwyMwk9ob+aw4Xo2NWm7daHvWRyvhcergGPQnl2fKYldhdHIlHYzaq9gkLF",
"part_6": "5kXe5La+PPB4yj7//A8SxFOWQqw7Sbc+ZVw9ShQeIUpkJ4pbEVbEVrQ9BIWiEyV4jrAF/2TUyXbHIDNt9O/2COlCdIHQj/HxqA3wWP7cFtHqALyt8q51hG6Hbl030B860savt128ZfqGbrPaF2satsgD7PXETfr5Hk213s1V2zGK9ODuXlfdJeQX9hzjWWVDg5/TtEZJgfZxcGM8mcxcMWUVhBHh8+oVVzP3HR7fP7BXr1h8HoV6fKC4KoxjlhLAdSS5nnzAznbrK/z85r77VU7dk/2OVZji",
"part_7": "GF4lDo6Lb6oJu7hgopXhgqvX5ZjcKy9w15PGcI99N8FJ152kV4HTJfuG8VZk0Sv2Vimc8tuZ6/QVFxeLPV1Q9vr1TlvAelxMsJ20sAPx+IxPJt8CwfoWrAV6uPNyh+cO8NNwexpuT8Ptabg9Dben4fY03J6G29Nw+/8fbrdK6tHl+9GnT5/acWrmToPuswddwh4Ijj5MR8h2A0RH73+cjZrNrZ2NLtlsFBL6sUvVaApJQLdd5DOcD0Lf9pkgNUH605Q9XZHpVYR+9mxNaHt9qs7481UJ3auK",
"part_8": "J2KALiMi1a8uTo2Mnq8xFv3qzBDQeNKrTEVDcslF0p9PGQmZqiHuqSiK+ymiZRINUSnTWEqe9qdYxykXsdHJ8xUn2tCv7NUrjIqlTsSAdKeHrxcjOTc8ErGMYp70I2zSJMVqLLQa4DZPVaQ53rXs52uqo1grboSSA7gmUy1SKRVasdL9/gupiD/SRFEqjBlCFSO40REHK0R8hC9xAkJxMF/yAWwUhHCSJsboOOqvHS5jZSKRahRROqQDceTRRCoC81FM/QRKVZoKrXG1JbHSYhibtFKJQUbA",
"part_9": "mSOEUlxhT5woODSEU0ohF4mJlYjgar8RIWSUmpjDjhBDsp5woVIlI61FfKSctUScRnOpVRoPykmsYiChEp2gFfXfXKgck3ID7iZIzZBWJ7hE20kjHXMTyyONnvM4AZopgTokJ5FKQGCpjZFC9EcC/2PUUCKjRMRDcpIim0pqdFGp+ZErBsTlGt0K4ehkSCC4jBWPAQXqLO4PJOXASacanSfRQ5p5d0nEL9fFo8NXPzaphOeRgdv4HdJuY43kEZ2AbXyESkPcT5II3U1HAleFSfiL6VUYDtLY",
"part_10": "oG8LbY7c9UP0yvjlfHzZ6/zIUDigbRy7TQeg1a9JD+BJr6Z4QOdVRwbU52vqZ9WQ6jp2X37xtGhelqy7l35Km/li79UTrAyhwKGV5AlWhpD/0Er8BCtDivXQCn+CleiL8yKeYsV8qRX5lLwMaeGY6vDV4MUq4wVvQxSslv87mSLlMsFEp5UZXmRbS79JGaETkyidDikyoxW+Ewn8xeh2hDL42hOKQyuRYCQecOvhKL6lhfdj0w/HV0QCLMIXB8G3sXyg/8pYf1y7/O9rO7psqrX96T999cWiCykAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/3WQzQrCMBCEX6XsuUJ+tk22r+KKF0UFSSVNDqX03Y0U0ljIXjJ8M7sMWeDhx+hu1+BjeMIAC8PLfWKYGIbmzEB/0zE7hrY5cqxwU+GUuc5KWSX6Im8N5rjMfFOXnxxjKIoiIUkhLGFSqPZGB0NWDBTZOO2Z4o7UZItQ2lEksZNWm7407NZwhRamML/v6VN9TM/6BQ+P2IlsAQAA"
}
}
|
codegen__primeintellect___1995
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAnalyzing the mistakes people make while typing search queries is a complex and an interesting work. As there is no guaranteed way to determine what the user originally meant by typing some query, we have to use different sorts of heuristics.\n\nPolycarp needed to write a code that could, given two words, check whether they could have been obtained from the same word as a result of typos. Polycarpus suggested that the most common typo is skipping exactly one letter as you type a word.\n\nImplement a program that can, given two distinct words S and T of the same length n determine how many words W of length n + 1 are there with such property that you can transform W into both S, and T by deleting exactly one character. Words S and T consist of lowercase English letters. Word W also should consist of lowercase English letters.\n\n\n-----Input-----\n\nThe first line contains integer n (1 ≤ n ≤ 100 000) — the length of words S and T.\n\nThe second line contains word S.\n\nThe third line contains word T.\n\nWords S and T consist of lowercase English letters. It is guaranteed that S and T are distinct words.\n\n\n-----Output-----\n\nPrint a single integer — the number of distinct words W that can be transformed to S and T due to a typo.\n\n\n-----Examples-----\nInput\n7\nreading\ntrading\n\nOutput\n1\n\nInput\n5\nsweet\nsheep\n\nOutput\n0\n\nInput\n3\ntoy\ntry\n\nOutput\n2\n\n\n\n-----Note-----\n\nIn the first sample test the two given words could be obtained only from word \"treading\" (the deleted letters are marked in bold).\n\nIn the second sample test the two given words couldn't be obtained from the same word by removing one letter.\n\nIn the third sample test the two given words could be obtained from either word \"tory\" or word \"troy\".\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "H4sIACb8N2gC/+1bzW7cOBJ+FW5fYmO8hh07CGCsF5jDLJDL7AAJkIM7SPgnkbJEtkWq1erBAHPd+z7CPtk8yX5FSd1twwkSL7PYBdyZtsRSseqrj1VFysb8ulA88qDj4mrxS2sb/cZFXddaxsXJouicjNa7j443GgoQWaf0ZnH16vzsZOFbW1rH64+r1jcrsvDW12vNotGs8HXte+tKJr2iC3RErRvWBRqRCiRly5uGxjV3ZcdLCIdovLtauqX7EaaH7azd2BD5rQ5spf2qxhgD1huL2zisSCto3krD7jrdWujZwDicN1DeMO4UvswiuFaHSOq9b2",
"part_2": "9P2Y+BrLea1J1nANFyKGnFej6w6JnSmAKM5IzHBKULumVz8PXAGo0pTAw7IL7RCcZwwnrNDCdOPE1jyhYFvEE9+DYG5gtmdNciNivDKUX9i68HydsVcwABGJjYtzbqFIwicoFC+q5WJ6y0a+1Y7D0Fo8IJk0bLWwDVFBNhHUbVEYPQ0PYickSjWIFFS+EELG4ywDhRBn66OhIyhOPDKZsRdYGFrixBH8GayWh8IDxN412aQESGW7tKTOgNlxEMedBX6wgmycfgO1KlkMhtCvsNrVNDxPA5MaZQuTsMVBFVyMoxYvY2rey7hHYOpdaujIa5g6UzvkfC",
"part_3": "uGGa9Z70d2o/sHPGWz3lQW8hDB0SCTBWuo3DiINAAwuLyI9Q+LaBFaSTZ8JjwtuTCQiyQGmE+jB6aZBYEnhO2ft7yKV3ATElRL7XrUQxsp9cWdtgJs7COAcOeR08CyYt6VdNJGqX7s/0eeNWXUx3JHpHNWpbzK+JIBijtAipQkosk2NH5+yPf/wLN/Tz/OyMnZ2dHbM/fv9nYnpiD87vLcTpbDtomFQPjKcke7vTica2j6qMZp7C05tI+XdQxWntZhu0yvcT6JCgv3fxkCF0w5SN1K/QZGZiZgJc1whqA8XDlHy/y1sU3D5dxlKekagutQSeSuYQxE",
"part_4": "8bTpUQJhhp0Zbu9dK1mlMfXTpYHG+WbkS8dOepgkbVV0sXeq1xF4zWq0O1swO1CxjyA1kbDlVejlAmMD/7qHd8vHFjY09JExJKFtEMkpRKcyzSkYSx6yD+XbvxDpWQek5a4uUizhEt2BGZSGUDxWkt02I1vL2FyIJKX6vj0wMcU4J9FRD3It7D8kjrQ922uvFrqtt9tzp0OGbrtweenGmbOvIcugfrC2whey6wFotdYVhaI3SiuiZLIYKmlDfUg6bqX6XshKDFTlJ3tEtTQkHX0zrSv5/R9MJuQ573X7LT6ti1Y1S0p5xiX2912pckbfNKF+NOctSf",
"part_5": "sHCMzZjhU7FrdjbeIp+ZpVVBcpf6CL3gKBzPevQZ9+WK/YX6xFF/nLyGG/uB/ema9TfVhwPd0fYP1+x8L7MFRH+9nmfD3RcmT9H8Dc1R758cmpw03rWdJmIcIgF7R4nmo+NjlEqSpBFK4nAQaHTzYensGP4YmUVkbh/U9TWLuE64Qjzlq5V26ogeHo9CO8Hpz2EnxJsrmOxfHtxfHNxfHtyfPzC2F8RJcPFQ4+KhxsvPCuYplw81Lh9o0JJX+yW3tGueMDcv+iHMao750O9eePGY8PLBdOp3tCg4mB5N3vue3B/1cNu/xPcC38udfzy9Zi9enFbeIm",
"part_6": "X6mfVdIvcpldOSHUjiYdLC4ylXip5geiqwlNqQHx+jRMKqtnTIRQO2DuOpop6Pvc/H3udj7/Ox9/nY+3zsfT72/p8de2cjYXF1s/j06dO4Dy/d8xH4+Qj8fAS+fwReOhTI4sPJgroACmZx8ytKGAea5eIKxZzq9eNUiYsTSFIGjQ9fL/etfN/LEWRS9GMbTprnSfrbCft646+Wc/Ofu/9jhs++3fDFctwuxv3iMaMvn4h2hTY/XUMuw8Qcx1fkNLjFN1voNIUTPC5zmhQUteRZURJAKXJlKM6RmKS1wKsNPkJLJZTiXEshuJQ01lzSM4nyw0BoJbgQ",
"part_7": "UmsUjYZQCA1txXWScilgQAiFSQICqWAI5z5BSQWhgitNM3i6V5gvBdfQUukDCcZwAk9AAUOSJnDCAjcJEGbAUQJJEATZIGycHuaqsJevaJLF66HVRhqritKWcCQtN0qbqio4UcSBo+RWVJWEUIpKGYgAWFfWytIqYXhViEJXUmFcwIApBTcFhVIAtMJUA+XS8sKoSli44wpepZXElNYlGLBK2wrGSsSLF1auy6qoQG9huSgEt2QGzrCMVsoi+RGiMEABbBqO0ValgXUsCySIRZhS4oLowL0xBVcGMxWg6LKU3CD4CszKoioKWWBtNf3Ek6Ik+7oogN",
"part_8": "tgEaqqlKLEY2MsgHMDnIhVFwbraCoMq9KURpb4QmiVUSVFVxSqKgvFjeQYgV4DKKU1giKRlQZUa5Q1iEJVwKaUAUlWcMRM9GjQDqpobJEE4B78UWYJiyeVBjjQro1AMLwskUlYAgC1vCo1lhL5SqmOkMoKjKgSMOFPYQVNriQaqwsYqWTGn2nAaUiXJNiJD2SjwvQwTbivIfZa6eYpbviT3ORp4CMxmT7iC88yuuFfdvPdialzI378we3/MDGqj6Ft4zYWnRW37aoXm6qVm+Bd2/tB3TbCbFo0u9t1F+ywvbsd1l3drmOxadbtyqy2q4Zv7dajQQ68",
"part_9": "28Sq0MHLENxmXVXYfHxTb7O42X6Nm7wZI/iu+sfbuaDTf1Nb2XUCsRff+8yNY3qoD6Z9RzfxvpvMpTT2BzE2vF3n41MEU6ObY+D7NrlX3Ue864z7wPm3uZmMPclNRmL+S2e+dP3+bjISs6mGvm3a/o4PUW9NvGuka9vKN6Fey0avnVxvgdqt78pb0QUntu1qpUK3DY30onGhXq196Bxf82GtxMZEvl73Xvm2t9UGx6aax8fdtC6/myzEXNK7jJDzKSPX8egy2UsvM1J+5s3riWbltMPlRisTCZSmWdFK8T3MihEtjPOsJPDRLM/LrRjt0dtd3gSb3s",
"part_10": "Ilz8ut+C55K6azfL52P3I7LllmbiVP9ujtPCu3Y9Vmz1uRYKKP5c7bVLwic97uuBU5M0GOeSuEzEzCmLcydyYkEj57LDz/D37Vl6/CXo2lMP1qjotsv0O8GLewkd+caLnYbDbJ7DAMORdswzcpD3DNi3dHQ14iZoN5D9iviIr+bqV7M3Txzhmup9F94f3LN0/4inmPWgG4Lxl61F6eML7CdK5sfH3vzzlt/Pwfdp6YOhtkDCX5BqmzyVvxqfHn7ftTnudM84txl9r1qGx/49Bt+qNczsWKgEivQxG79Rdfiz7Q/0oSPnbO3nV6cRXbTv/2b9eLVrWLMgAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/7VT2w6CMAz9FdNnHkDlhV9xxqxIxMQgwhYghH93a3EwYwwaBbKznV5OW7IeTtVVF8eDqrTKIYFewLkotaoFJKudgCjeClE0tzJr8k6rW5HLbDz5pA8fByyIe5nFFPcu0ct8v2ljQWpTnIBgJcDOMEWUBiQD81EYEmVf5JUO0h4tEOHoGccOo5ECfA+cvGjzjYz8SoY725BgatcU/Tmk5GaDnufAmugUEJ0ofWPrrlqcaO95NDcas1nYH2WUL8OdxdwqC3sTsrNoZUt/xiDxe2u4ajW7gKELWL/dLfHbDxBArbpLZm56pQ0Md7bDK+8BBAAA"
}
}
|
codegen__primeintellect___1997
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nНа тренировку по подготовке к соревнованиям по программированию пришли n команд. Тренер для каждой команды подобрал тренировку, комплект задач для i-й команды занимает a_{i} страниц. В распоряжении тренера есть x листов бумаги, у которых обе стороны чистые, и y листов, у которых только одна сторона чистая. При печати условия на листе первого типа можно напечатать две страницы из условий задач, а при печати на листе второго типа — только одну. Конечно, на листе нельзя печатать условия из двух разных комплектов задач. Обратите внимание, что при использовании листов, у которых обе стороны чистые, не обязательно печатать условие на обеих сторонах, одна из них может остаться чистой.\n\nВам предстоит определить максимальное количество команд, которым тренер сможет напечатать комплекты задач целиком.\n\n\n-----Входные данные-----\n\nВ первой строке входных данных следуют три целых числа n, x и y (1 ≤ n ≤ 200 000, 0 ≤ x, y ≤ 10^9) — количество команд, количество листов бумаги с двумя чистыми сторонами и количество листов бумаги с одной чистой стороной.\n\nВо второй строке входных данных следует последовательность из n целых чисел a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 10 000), где i-е число равно количеству страниц в комплекте задач для i-й команды.\n\n\n-----Выходные данные-----\n\nВыведите единственное целое число — максимальное количество команд, которым тренер сможет напечатать комплекты задач целиком.\n\n\n-----Примеры-----\nВходные данные\n2 3 5\n4 6\n\nВыходные данные\n2\n\nВходные данные\n2 3 5\n4 7\n\nВыходные данные\n2\n\nВходные данные\n6 3 5\n12 11 12 11 12 11\n\nВыходные данные\n1\n\n\n\n-----Примечание-----\n\nВ первом тестовом примере можно напечатать оба комплекта задач. Один из возможных ответов — напечатать весь первый комплект задач на листах с одной чистой стороной (после этого останется 3 листа с двумя чистыми сторонами и 1 лист с одной чистой стороной), а второй комплект напечатать на трех листах с двумя чистыми сторонами.\n\nВо втором тестовом примере можно напечатать оба комплекта задач. Один из возможных ответов — напечатать первый комплект задач на двух листах с двумя чистыми сторонами (после этого останется 1 лист с двумя чистыми сторонами и 5 листов с одной чистой стороной), а второй комплект напечатать на одном листе с двумя чистыми сторонами и на пяти листах с одной чистой стороной. Таким образом, тренер использует все листы для печати.\n\nВ третьем тестовом примере можно напечатать только один комплект задач (любой из трёх 11-страничных). Для печати 11-страничного комплекта задач будет израсходована вся бумага.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACb8N2gC/+1b627byBV+lYGAAnZDe3kRJcuA879/igLtvyh1FJu2icqUK1GNvUGAbAKvWzgbY4P9VaAXFH0A1bZiJbYVoE9AvsI+Sb9zZiiRkihbDHeBFJSjC8+cOZdvzmVmgDwvbTf8RsfxS+ul37TdfedXnu80m86WX9JKO11vy3db3qbX2HfAAJLrbTuHpXXbMrVSq+3uul6juXnQbu0fkITftpp/coS/54idVrPZeuZ6u2KrtU1f4HnadPZFt0NPxALKbruxv0/PzYa3223sgnjk77W89bpX94K/BT0RvgpfBv3gNhjgexicBx/D",
"part_2": "1yL4FAz5I7gMLoJh+EqOBH0RfBThN6DQnHPMInqPZ58FN9E8lnSBz15wg79IsuR7KxkG4Z+D62AgPIjE6A2PXq6K4F/Knn74UkD9dXhGHL3gPR6GwYcEe3gaWTkM/sP6rmc6pEWzPkFnH5RXIrgC92XQC08iLe7KDOlX0mom9TGtsfncfQEIWIt06FsY/U7QI5D5RNgAi/fSBDg4sqdPLAJfNPmNOBTkPz2QlQL2v2YtF8FAE7QGHyXwEHcaHgvyEPhLfvbsFvaFJ1JEeBr04eRAHCWkzhLEI9fhGyILxu6WwiAmlx6VXPh0Bvf+QQtGUPcx",
"part_3": "0AMZbr2Gt9cM8ICWiGaNVPcl70sMDimASOkAJLDcgPKeAoenxET2GBWYc67cHANMCzEIrhI6aa1GSwjXeyqsklZOmXU+cjNu1n//+ePLH2YhE76G939lUEgozNamZWKMp10RDpMOTeJEfpCToB9z0MCLW7nCEyEqw2LkIwz5uwxyslp5M4pN+kYEhCc0bwTFQEaktG6cgzR0R5TcK9xuyQbKvDMyk0xiTbeyeKTjIEHrKSUQeTwRf+GxNg5NCdkts6nwoUwE9zeRdPw6G8csqsQq17d3VIAkGH2ksxwb8NyISCYTiUKPcPwIKyWiyhOueQQh",
"part_4": "uE5k8lJUJwqFlkAPKuM5T/UyZvXMoJ9Y+ajwyPIUfiuNlFzsWd1boVfwLjxWcXpKdl6yOfzA4xKEeC5+iDJrKKv5+VgAoTsSwCvC5lxi4d7CcJ41UMZIBsYbTD3haVTOqPosGeLHv/wbVZ0+TV0Xuq5rQufHQw0M9MPQf19bljl3T2ynWdJqJ+xW+RXcxIKCloUH42HGJPq3uAYZnAxoLOyS8mNxOIxXnkyLIKOH2osiyXSOJ51qLJwv3oyVwiP6l6Hhw9TE6uoq/XruvYgWTfY2uUC0bsvA/oJShFpjf7zeQ1m3zmWiT2GHYpIs34IAnCxu",
"part_5": "/ft14IlwP71PwOPxnBFSVZJ/gkuuLKWlzGuVWMOEbyosv7xawD0aM/ukV6Exp0DUPVNYwq57ZVGJYJvHrHjuIa6ai7iKFGeYwjBE7PMewg0JyzQwJ1GjTKmOtFhqWYeKIDuphJUU3bV9oY7Wm4723mQj54hUrY00XUWSVfeVoaqqD0fkTHXnbO6bkRMA4MP8vW5i89LjEnPvaiaWxgVIhN8x1wXvlaQ0DvJX3IytmJIsJdkYzV/EwGW5EYyX2mkwZgJ5OzoKEfyT+Cxg/MyK/+UF1mLxFO1nPwe4BYJrIjgWDC072dp/tvAaabmJnx6ybFdu",
"part_6": "5WnnTB5xMiYzHbWpyVEQitH5mU4JN1qyaSWPEdFW5Jx2FCPt1KbUYT12/lLJEGUWoIDQz0+G6YMax/ycMF0C+1tkEC8ZHyVhUfg9EDOMlcRu5URmyjLg+WHKn1ncUZjOy0y5f7yUwEG9vCxQLSw6lnFkUXjHNps9RvB3e45wvYOuL565zaZ46oiOv+16ouFti6NWV3T2Wt3mtjhou55PhLbotJpdulgSfot4W11fdsRft57RmLpDiq6MSE7b8bttj8lbrW1ntaSV2s6O03a8LbqZcvcPWm1fdI462n7D36t7nnaoHW003Y6/tN84WIJmjU1c",
"part_7": "Wl7tHDRdfC8v172v7+ZY7UDwEn41vM6GXvd2Wm3hwl3Rbni7zpK3vF73BF7ujvj6kfv4F+bGhq5Iinz4cINGvvrKjNHpdbgSDSTp0PRgwxjTnGbHmZhK81Y2Dn85MfOQLIwTjqSKJBE2HT1MWJmmOUU7vZ62ncYfJHmCI+GyDIKHG0ZG35UTCTQSCh6kS35gfLm4crIsYd4yIp3jEVHutxuuh2eVGMWFa3HhWly4FheuxYVrceFaXLgWF67FhWtx4VpcuBYXrsWFa3HhWly4FheuxYVrceGa54VrJKRTWn9UevLkibw6qnvF5Wtx+fp/evma",
"part_8": "ZEl7upsuf0Wf0R9yqPRYK/lOx0dOlR49r5f8owOnXloX9RKn9KZK1pIGCmeIHJSba7lZhyQeBt94nKkvNJFFZDUvkRUlcnrTPkuBsbgCQ5SFxQpmStQzSNSxmzAIAYt+CFgLJ8r4g66ZStYWV2KJCpttYu9RywvsqjArgoyxCeY1OrMT1iZrmtZQyYCNAXvXeEFrwtThRBVvQsgmfXZKLBpGFmfgDvtiAnqT4Tfy8mMN9hoUGwZpETa7UOFIzQcnXZhVYVG4yJUggAx2wVTLMhup2uK6CByTXaH8nQ2RtbhYm8KdAKmy4TaAml0VyovLrkGY",
"part_9": "zfDrosZ46ADJ4kURZl45ZgtdSCWkQL7p/tHSjbxqBRkcvWI/lVKpTBdlvO0UpXaWkmdIv/KroVKglVsJHSOv63kKNX4Kt838BOpzFuYzXDbzi9eyxJALXlpBzRCT6AU2+17jQi2lU89EeuNtUQ3EW45WU/pollzgvEMzsmiyVUaeiQoyDipq9M+u0aOFckNNfK0iapawLFFFtYEdaFrcM6vYQ6B4wgf0AkwtUx0CGx7BaaBVgwcyLBJZWxNrJslZs2kIMqEeswyIws7JYhUQUqEWAPkWSmeFpNWABHqMjb4gKmj7aJ3UP6G2jMYJPWtkJfSU",
"part_10": "wVvjSTZ5UiHoWHWlSkrXaqxLF+wkBIMffsK6qkHmVHm/UiUdIJd10keSymRTJQX6WpbtoqpDIreUpA7GlShly5Ity9NKdF4qLMS7AiIFikyb8UhojlBYc+q88Tk25ua2PQ6qORXKyLZNignOy15DibXys9O4087PWCorP5GV9My612mvkr0+2MLIOyns/JCesydUpByzJU0XnwbKKUcaO3u1N4X5cyKl53m5IROgnF/dL0fdKqVIm1nyX6aoNSf/rex1Kre8sZP1NM/Glx7TuSmx4lV2HiSP6X+8dza7nvvHrlNa99td58X/AOkV8BQyPwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/22Q0Q7CIAxFf+Wmz3soINPsV+zii0ZNzGY2eDDL/n2dm4OokEI53N4UBrp2bWzOp9DFcKOKBqF784yhF6pwFLJwYJHGwekqVEDoAA8zQ4M9rB4sDEr4TeCULPc6N+rBC2XGJ6yG46QxqplP9ofkPlq5jixdnRdHxk7DZ8429fRm9QzbGLK3JnGZyraM/2RZU18V9UgF9eH1uOindlG3cQLg0+GobAEAAA=="
}
}
|
codegen__primeintellect___2004
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nIn the evening, after the contest Ilya was bored, and he really felt like maximizing. He remembered that he had a set of n sticks and an instrument. Each stick is characterized by its length l_{i}.\n\nIlya decided to make a rectangle from the sticks. And due to his whim, he decided to make rectangles in such a way that maximizes their total area. Each stick is used in making at most one rectangle, it is possible that some of sticks remain unused. Bending sticks is not allowed.\n\nSticks with lengths a_1, a_2, a_3 and a_4 can make a rectangle if the following properties are observed: a_1 ≤ a_2 ≤ a_3 ≤ a_4 a_1 = a_2 a_3 = a_4 \n\nA rectangle can be made of sticks with lengths of, for example, 3 3 3 3 or 2 2 4 4. A rectangle cannot be made of, for example, sticks 5 5 5 7.\n\nIlya also has an instrument which can reduce the length of the sticks. The sticks are made of a special material, so the length of each stick can be reduced by at most one. For example, a stick with length 5 can either stay at this length or be transformed into a stick of length 4.\n\nYou have to answer the question — what maximum total area of the rectangles can Ilya get with a file if makes rectangles from the available sticks?\n\n\n-----Input-----\n\nThe first line of the input contains a positive integer n (1 ≤ n ≤ 10^5) — the number of the available sticks.\n\nThe second line of the input contains n positive integers l_{i} (2 ≤ l_{i} ≤ 10^6) — the lengths of the sticks.\n\n\n-----Output-----\n\nThe first line of the output must contain a single non-negative integer — the maximum total area of the rectangles that Ilya can make from the available sticks.\n\n\n-----Examples-----\nInput\n4\n2 4 4 2\n\nOutput\n8\n\nInput\n4\n2 2 3 5\n\nOutput\n0\n\nInput\n4\n100003 100004 100005 100006\n\nOutput\n10000800015\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACb8N2gC/+1a3W7byBl9lYGAAsmu1yDnh8Mxmi22wBbNTVtge1NEqcNItM2YIr0iFa93sUBve98HyEWfJI+yT9JzPpKyZFPZhtVdbdmfxJnh93u+M0MlP82WWZs1eTs7m/1lXazyl1Wbl2W+aGcns4tNtWiLujqvslWOBRgqqmX+w+zMGXcyq9fFZVFl5fnNul7dUMN3dfk+V+1Vri7qsqxvi+pSLeol37DmbZmv1KbhFZdg5HKdrVa8LrPqcpNdYvCuvaqrs3k1r15Wsix/n1dYcqKyizZfy9CihpNNq16Wd5m6zRr1tl7nS6yolgrT6zwryzt1kZetKovrXK2yH4pV8SO0nKo/cn6Vr97muAXaspa3XGVLlSmkQdUXql",
"part_2": "JNWyyuG9GXVaqomna9WeVVe6q+zRZX3bQqGrW4ytbZAm4VP0LZ2ztVtI0q8+qyvVLl+U/Fz6cSCN1c5otiSYs13IFPGdxYtAi7RLKQPwmss3uqvoHh5Sbn4iuYub0qVid086GSrYoGTqpmA9+YkLsurj5sTEJ3gdTVbVaqDOl5GMemgVJogFJWg/fWyG9d7Zg4QXBce1M3TYFSdjaaepUzZ33GkNoMejYVNZ6q3+eVFL+fxd1V3aqM0MA0c/NdN3NbMGOSOKT9PEYtzzWF6YpwbtUiqx5nrrh4gDaA6iZftwWCRqCqftvk6/f58kxRq/rln/+m4v7d9O+2m3whUzL+Qkbp3zc7xujBW6JpuRvynuv1xQmcWav8h2x1w5yZjx/6",
"part_3": "X4Vh/fEDfi1+UeN9zUzMvfIHWnpT7uOH7tff4yorG4Aka/aBSsigwPQYMN8suqbskVlf7IHtr9vPkrIhPLTDDeAGxKwyIjwr4Uf9QE9+D6M+O505aYYdGJ2qP+zGk/X37OROOdGQYwRd3rSZ3N8S/oO5NfW366xqkJyVIBaNMOiCN/1CK9n5W71BXt5LE+GW2547vt+AOcBp6pd//AtZGtpks9ppjyFDO+1F3yTfl+AIcTtTF0WHQKKy2V287efsfVaUGZulS/Dv6Ni8+oo/L6ubTSufOMQiXBTrhoxV5YMDBdcI3aGrUB42X9EW7znT5pcIqVLPOlhXIuPo7+75xw+I7eMHKqg2JLpB3UN3TgfLTQ4by0+Zrh6ZbjqGU8+6du",
"part_4": "oueh+SXR/ue2MXdjuZ+POm/fVU1LJIrTbN1iuWvpD+qerqqyq/zHb92/Hgv6qw0JmUeMs0B+u46/23Haib3n8p67yy80ori5fmwi7CeZV2+9r9Cq2Mcrsrov0VcYQfo+TNdm+ue0t275KRFH+xGzLY1e+2KEt2TdMumS/U+A5t0VzVm3IJrkSqOIB+q8uNdAWaBWtrKuXrT/Ut5/pNfdjDqWedt5t11W/Hy/wUZ4N1foFNtVrwqJCt12DRV9Fr9QUQGqkvvlCJ+lLFz+dVhQkYfiYePnuOEXJdwf2nHzptbsoC7zgGKPxA1yu54flr9eULFc+rAip6pfPqHfXNq+vubYE3JBH8h2q9U1+rqNeCRqWid6/Vb5D2F1AgcTzrB7/G",
"part_5": "NdxYcCYaLA/W36mvVDwYHyZoqb/MyyY/25+JukvcKavWu24VdEusXz92sHitfqv0jjaMF/TqemeMP9e96u26neu83N7VbaCDYruj5PrhDVx1/dD8/qq9ONfMSIEKX++nC5Zwj94fvB4GBXbP1s+BGKkz0AJSLypc9wB7Okk+nSSfTpJPJ8mnk+TTSfLpJPl/eJIclDSzs1ezN2/edHv5vHo6VT6dKn/lVDmvgJfZ65MZz3XAz+zVT/NZe3eTz2dnaj4T+J73wJydYETQ0U3a+X2vAbMy3bFFN5/K6M8n6nNVds05pjKapvJT3TxmZretP9sgw3aIoHsxPXbUiJ6gO2YCYo1QNOLo33X/CiqMR+O0j6bFgf6+/423cjyeeIKReK",
"part_6": "hOFB2r4F2OIhcHtZU6eiTjR1KLNOPB6dh4bRI9xR86ZOM4UYPwIyKlCI8F3H0sYgpNYUaEHRGOIhkRfkSkIyIMwkRbQTcM3TBmK+xWuK2gIeP3BZUa6rPRVsRbQaXW7As7Ity+SPaFHxHpvgh7wtENF+8LvRVmK+xWuBGRiBgFktXehdhbPRHYNtIpkpV6Y4All3ifwFowGjn3MWoKJghxAt+S1IDAMJcEH6vEhgitEKLYm6NRKxksBk/SiEf3BKsccpbCnnGg2BRlCAmm0wTJNuBeDRe5WmkdDK6ALY0JjiP/Nnh8ckF5j9yyU40zZOrY8FKhyqmK04ChOMQq8KqDHRQmXBR7bB4ByI6TBKXQwJozpIAYdlBxtA4SlBC5DmZN",
"part_7": "1DUBNwOocDE0B62PlaCEhAzWQFQRGtw4YU/gMPZpUNoYGk6RkMQjD5H0SYRPxnll4LYzTBRDStAv2qWp8qis8ciA8U45OG2QP2hhFhzCQoDQohNGA0PGsbMS9BMogMqIes/dDwBBO6cegyxMnHimL+UlFhomElpgLEW1HPHPiqFD6BoEJlFlaU2HVLMUOrDKKarp4S5Qjpjgrk5gxMIJBcag91BmjGclyVcalTfS8Vqqi0jSlDFQRJZs7aFSH9irPToC7n1+cQL7AJgBGrBRy4nACY5SxMU+grfwJwCAxJK2IAedAEhxYglkqwL5EJ0IIBI3KdQE8JCxqJMOoFJRGBNjmtQSgGq+A4lMLndTZjhBlY1JguqqxiuyqqARKYEjcc",
"part_8": "LmSKRzAGQ0HEiAhWQPEQw2AWKsZ64t9cMBJtjBUfQnnDMBxhzuQXioIpcibwQiDxCRFAPu+1iGBKCRVF2HiH2EJgbjWl7CPe/hT8QhdCG4FrYt1puEtWe/WSZRp4AorOCTF+AnKnVMdbAdVm2UUJkmDyB65wGtEASBSBaRZeGYiQALYwTgAWuZGng3zq42MiGd0KmaBxHHGLDTw4tUWhY4ddIm4HXUCX9emojMLz0QkFFjmfuEvJZwdzY8YHjE4thHEUshxOOio/IuUgx4kBssARsAqcDGisiaBCaKSRQaNqEnfSbECuGL4gPgaH5m3ceCfkIU1cCpIu0gRTijZIBzX0bGgRtQr0hhS1Geu7whJ8QkkZRhx16qBBWaAHDcVA12",
"part_9": "dKDeElhkZC4LtIkDjPHCTIZRoMAxdo6jcq/h7qiZf2t57AA7kb0YFMYj2Se68moBtPWgGsASbge2LncS8DL3NkBep+j+FMVPI+5d0tVSde5MgcwGrR7ZMgla14ptzzwARSnaGjsXsMudGhTLaAlxoUTOEjfakyo9eiBm/wqXWgKSJQzgCisdyrMfsSZbmCX5JNzkEu4x2IUhOInl2pA+gmyYUpqY1EFOIkVhOYuo2c6GlA0mJyUxW1585wbsxh/FUDXkNYmmP+TpAw9G//OzCjlp+D3wgGencIT4fbTTk+nUHe9JNxWF/dOU+uSnw0+9/Y+dWlbQpEqP+ezOFB1Rpdt+w2APZD6dpnTIcZCf0bdRczKTyr3xBJbb9pK8xjfF6b",
"part_10": "V0x0OnlqcX6ExFL4hS3okXK588PoEnOX+gZ8PEZ6ZUrABEYsUfhFOY8lAW92GhyABVKi+GNM4TqZ3a18OXSe5gUXQyrdDdF1Xj2EmmNQMVChnL36hmE02kuCCpZpqlluNYiSeC3glQ/AGPpyWD7rqD3Rmn07qeaGB+dZdjnq8jfSjTZroN11eRBg7wy5TdYuBh6cwDB4ypdMg2JPr4oHO0TvH7THs8rnUCuyMrHUFIB5NDCImmOk5KPfTNs3XTtHbNfeiLc6Onw40bzIFvySdSne3+BeR4/wbS8ec9e3biaA+Pyfao7D/ht56oecCDWBjV7KJpvTf4zH9aOabXve7Qvw4Wsj+cveb/6m/ON1Xx/SafnbXrTf7zfwCCW+XZFjAAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/41S0U7DMAz8FSvPPMSOHTv7FTrxAgIktKGtfUDT/p1zgTGQkFDT1LUvd2e3p/J42C+7+7v5sMxPZVNOU3nevS7zcSobup2KTtOuUV6CaCo3NBVbc1yx1vtjq5c6I1ozV7nkEbB0il85/ZGL9Sx9LibWr9UvGEkBi0pNhKmNcJLKYDfqMojNwInbrZMIAm0VkKFBTc1JO8DapaKAjd2dDNhWIxFBLHblPNvVHkbikuWUVKFheKuSLgaInKEgGFNNBRNI+4D/7gpEHxSAiTNGWSuK3Dt0JBJmNCIH2o1auJFWSSM40BwCfTh5yzYGUOw4HembvUFpgEJgCo2mD4WmVcwLZlVawkZqCtw6bLO07KKBKZzXLrfZ5n6Zrz7797DrPyPWv+vbc7kpx/nt5QF/2GHB4/wOjgEJbnkCAAA="
}
}
|
codegen__primeintellect___2006
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVasya has found a strange device. On the front panel of a device there are: a red button, a blue button and a display showing some positive integer. After clicking the red button, device multiplies the displayed number by two. After clicking the blue button, device subtracts one from the number on the display. If at some point the number stops being positive, the device breaks down. The display can show arbitrarily large numbers. Initially, the display shows number n.\n\nBob wants to get number m on the display. What minimum number of clicks he has to make in order to achieve this result?\n\n\n-----Input-----\n\nThe first and the only line of the input contains two distinct integers n and m (1 ≤ n, m ≤ 10^4), separated by a space .\n\n\n-----Output-----\n\nPrint a single number — the minimum number of times one needs to push the button required to get the number m out of number n.\n\n\n-----Examples-----\nInput\n4 6\n\nOutput\n2\n\nInput\n10 1\n\nOutput\n9\n\n\n\n-----Note-----\n\nIn the first example you need to push the blue button once, and then push the red button once.\n\nIn the second example, doubling the number is unnecessary, so we need to push the blue button nine times.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.1875
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+1Z3W7bNhR+lQNdJZvjyrJkS8bSYQN2kZt2wIbtou4c2qJtohSpilRdoyiw293vEfZkfZIdkpLjLJKxEAaaizhIbJFH3/n5vnMoI5+CnGiiqA5mwc8VK+iN0JRzutLBIFjXYqWZFAtBCooGuMRETj8GsyQOB4Gs2IYJwhdlJYvS",
"part_2": "IPwi+QcKekthLTmXOyY2sJK5eUObJacF1MpcGRNc2VSkKMw1J2JTkw0u7vVWitlczMVvRO0JbIlCsFrkQEDpCu0o5PQDW9EhvBbOVyWFhpIIykGu0c7tm72KAqnoDNcqmsOy1lqKAV4teU2bSyAWO2eq5GQPauvCVrLAaKRimmFKDKuyodUQflhr",
"part_3": "WsGKs9W7No9j5MZzUXPNSs6oshYNNtqJulji/cs96J3sRDuK7ACn6iVmvtIKpLDpFta0AZPi2MkQbrAEuo0fAz+2VVqWCpbUMtIkN3C3O1fLipJ3CnK5E0P49Q4WVkTY2mA9lwyjqRjfI23VpsVW6FkgIOF8PziOyN6m2gjE0HD7o1zCjgjMSEvY",
"part_4": "UN3uFg+y+X2LyaBGWFEXh4zXrmYK0NIIBEEK8s7QBLLK0QIXyGrLqFUjU8iRQkq+N67n4sq8bkRZa/vJLJlM16xS2qrBBCCFyY9hvdGbWWDmBlSz0IQJZfgzQWqGLdLKA5O09xdwMYIvf/0DSGFhP4zCP+LLAShakopoI5i90XNJsOTDo6he1/o4",
"part_5": "LOxI5A8NkS9+IPHLn3/biB5WRWMDO5EISnNbl7JWWycsp/aKvq+ZkWxT+CNxYPExQ4S5R1UT2U8fSVFyqprYbPnmIoaJsXBhz0VkLpqtUQij473MgTVwr6SmhzRvmj62BFDnCPaytlncT+Kob6VYoXYbvsSdzV0/WpPhkQdFkb+8dYH9Jeslbzuv",
"part_6": "yRrVUgtBV1QpUqGSlYQdPR2JMDKxtR+2YnJq2THOsduw7XAG2lBNVtgPNc9x/hlycQHbUvLaDFrjAW2lqZf5eYX9pg4ztR2hBqeiuq5cUjhg6RBHc0XXOO8wYxzEOV1jRzBxcYmjFPBllXiNa+UFeh24+C4uh9hlDN8vnRW2iRk6XBO0DQeGQLO8",
"part_7": "2zKjPvgOigauMYZvr1sb6wS+uYbo7toh3a21OC/v4bSrV439y+t7292unLura3fPf12+eHHwaat8gQCXrqSmMouF0qTC1t0s7IQ8VMmVbC4eGmB9bamwtjj8mMDrho7nY+/52Hs+9p6Pvedj7+scey2ICmZvgtvbWzdK3aB/PgLPeATOBVY3eDsI",
"part_8": "NFUaqx28+TQP9L6k82AG88CSvWhoDAa4YgvsNk3DoGu7LF1n2PXIrn4ewP+Hsg3WhZV5YEHUCTV6PFTUE9XIJ6pxJ9T48VDjnqgirwTDTqzEh8MQsuxc9coyDK0nttBPYNNzETCZTAB/e9SfJF6IFrITcRKGPhlDOsp6OmHsCdct4WjqQ68juJdi",
"part_9": "r5QNHhjos3WtRewZTa2fxyFG4xiSyTTtzjtKPWo5CiPAP93sxEniMRiMdnryxi2vfh6ZYRN1B5mmaeY3cZIeBcVeMWbTfvnEXnwnVkC9QveIMjaIUwz1XONsdCK+yHfy9Byc8RMZFVnoqO5uwzj0oTpNJ5CN055zPvQ5UqFbih4DFxlJT1RxMv26",
"part_10": "zzQjiM/5TNPbbpnX41Y/ngcT8Sm81Ks/TjH7VMYWIp4cNE/icO6f/pFHylN8nUCcTjNPdZ/tq1II6TSKzibFNE4hTiY9X0/SsY+4J6aE055nmyz10E2Cr1MHSjLxasITkONp6jN3Jmf7MgXj7oOuCeut+SewWtSCva9pMNNVTT//C8vPY0BFHgAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02Q3QqDMAyFXyXk2ovW/tj4KovsZmMbDB3aXoj47osbmAba0I+cnEM3fMxTGW/XPJf8xB43xtf4KXlh7OHCSBQ7IOoc88jYAGNKEcglBRaSpfZ8khRYI6XImhbkcvXQsZboJDFGkBNP4GUDdDL3I8OBppKraJ6SujoTNJD6hDqGD0EFvjZvg6r/4mHHBpe8vu/yKXORtn8B5PxMnCwBAAA="
}
}
|
codegen__primeintellect___2010
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\n100 years have passed since the last victory of the man versus computer in Go. Technologies made a huge step forward and robots conquered the Earth! It's time for the final fight between human and robot that will decide the faith of the planet.\n\nThe following game was chosen for the fights: initially there is a polynomial P(x) = a_{n}x^{n} + a_{n} - 1x^{n} - 1 + ... + a_1x + a_0, with yet undefined coefficients and the integer k. Players alternate their turns. At each turn, a player pick some index j, such that coefficient a_{j} that stay near x^{j} is not determined yet and sets it to any value (integer or real, positive or negative, 0 is also allowed). Computer moves first. The human will be declared the winner if and only if the resulting polynomial will be divisible by Q(x) = x - k.\n\nPolynomial P(x) is said to be divisible by polynomial Q(x) if there exists a representation P(x) = B(x)Q(x), where B(x) is also some polynomial.\n\nSome moves have been made already and now you wonder, is it true that human can guarantee the victory if he plays optimally?\n\n\n-----Input-----\n\nThe first line of the input contains two integers n and k (1 ≤ n ≤ 100 000, |k| ≤ 10 000) — the size of the polynomial and the integer k.\n\nThe i-th of the following n + 1 lines contain character '?' if the coefficient near x^{i} - 1 is yet undefined or the integer value a_{i}, if the coefficient is already known ( - 10 000 ≤ a_{i} ≤ 10 000). Each of integers a_{i} (and even a_{n}) may be equal to 0.\n\nPlease note, that it's not guaranteed that you are given the position of the game where it's computer's turn to move.\n\n\n-----Output-----\n\nPrint \"Yes\" (without quotes) if the human has winning strategy, or \"No\" (without quotes) otherwise.\n\n\n-----Examples-----\nInput\n1 2\n-1\n?\n\nOutput\nYes\n\nInput\n2 100\n-10000\n0\n1\n\nOutput\nYes\nInput\n4 5\n?\n1\n?\n1\n?\n\nOutput\nNo\n\n\n-----Note-----\n\nIn the first sample, computer set a_0 to - 1 on the first move, so if human can set coefficient a_1 to 0.5 and win.\n\nIn the second sample, all coefficients are already set and the resulting polynomial is divisible by x - 100, so the human has won.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACb8N2gC/+1bUXPbuBH+KzjNtJETSUMABEl4RpPpdW46eUnTuXvpWKnDSLDMMwUqImVbzWWmr33vD+hDf0l/yv2S7i4ICZLtNHGZm0xPzkk0QWB3sft9iwXhe9+b5U1em6Z32nu1KhbmhW1MWZpp0xv0LtZ22hSVPbf5wkAHaCrszNz2TpWKBr1qVcwLm5fny1W1WKKE76vy2rDm0rCLqiyrm8LO2bSa4QX6vC3Ngq1rvMMu0DJf5YsF3pe5na/zOTRumsvKnk7sxPIoYhuTr2p2mYPUZV7XZsZg+NSpKPO6YdfFtKlWG1ZdUNsit+zarOp1DXoXy3VjVqyw7A/ViP1gppe2Kqt5YWroNzMsZ5drUFk3Zgn2rm7y1YzldsbA0qpBAfbd2qxAJ0r+Ll81l9+wF82T",
"part_2": "mjXgJxzhZoougO/5ZcPemubGGAty0ZCtLOiXN+ymKEs2M9Ni1rooL5pLb/gSPGCaEc77hz33zcH17CYHcy6rGkTv1ILC+hRmVzRFXpYbbF0ZVtQwr2VVbmy1gHb2qn97wsYsP39vP9z+Bb7YM3fDhoy7BvgFGkejET3it3SJBgwsBgM3pmFriDrME1wxrczFRTEtjAUP4QTRlgIwMwdPX43YqzLfgP9ZXoLrbd7QVAsweb2y9Yj9rmEmn17S7QANpe5sWUyvWF0tUBTgi/04YPUau6HfApVo+Y8fXHPd5BtmAR8MZgGNMHELrp4ZULwgW9FyNBHQXbMColDB7YZd5+XasL43Gvy5Mnk5AKfV4EpAGrRYM8/x9wGLyKNlDWMxJGZ2MmK/99BaVNcApotiVTcAMPCECzxF",
"part_3": "+q3BYJe5BxBE0yIaL8imykLEChf7lanXZUMk2cVtK6O4LuoCqMPebtifXDBvIWRXhJVXB4EGW+u8mOFUD8cGskmMUw6IMbdFjcEEO5ZgCrg5R9J75HwLFxwwYDfU/dtWD/mEYraTTDZ9j23OM0Tct8gIR7gSPD3bkANsdcM21ZrdVBDx1QAlYohWa+PC6zw5hQ8khlUOwXKs8YQH8x1tNjWrlsBI5MBz1D+xQ/x5YSFG9NuWVBgnVgI2POsK7INEb/LCAq9vKo9lABOZecX6nP3893/BLX5jTooi4MZPVz+1DXh/8u9//vy3f5DIuvjrVnzg8rtU8VYVw10W2NHeAgk52Vp7+yADgCOmiLsnz5948ITs8GwoHKfBpfvkbVOHt8ERAShVfBjcJ46C7CJ2BeGyrI9iacI0",
"part_4": "dxoZemEEWXJKk9l60fXp4/TNNeCAUs8JwGGDADXv1uAbAGvk0FwaWIqQxkA8QkGB6RZpvQXBzD1A6AC12LxAqc7ZSF/AbetLlzhdTkQpfj3A/A3ZB7UiSEcBZP64bkLMwHoIXpj0/mzqSY/1MRtWAJd3a7Cv9gRqgXoJGRoZjrGrmxUkvvlmgA6f9F5W942ukHw3Rb1nwHe3+WJZmro1gSAMCyET8JxPLMHbGTmxaJXd9hEITewFcYAr/MfvdG67xkyRKB5873qCtTt7XoKtW3e8sO3CgyyqydDBbpWtMdmeR+hWAl8V9kZHQ0qviLVbYuOQ/eTOHRYU0QXcOQr01gZ4MNsqBrofLEarXYKp28z/YHYFaO8lx1tCdkQ2HgS1sjuqUrrwmbluoLAhNQjGGqJbzqCoQcxA",
"part_5": "A3ikKtcESJgT9K3Qu/jvJWS+elso+bqIigXjkEk8nJkR1FsrcwEIhpIHqqvlmEdxpjI5se/aX/XELqrZbLx8+u4pfCbWDq7GzRo81F/kS1zjBmR0/2RUL8sCricnE5uPz6LXE3tj7GVejQEr87zAC9YWBdZLQLW56dtn/AQqMQY/i3Erxt1CGBcgYjyGRNT2wJ98lC+Xxs760Hyya3Z6no25azJlbe4bBMb2FyfBOLCKBk0s6Lsaj6PTrfZ+fsadenIc9PwtH4/5CTLOPYoCFRSU/hMggTfrwIa2w8sKnwfPQJMz/ps9edBsSV/Qdr+ee3Td0XdPn8U4PwPvv961WItNQcNhrAbRYLgN11bOAMb1rX129XRx8htEyiA/K4ahYAzlvrceOxNAK2EMkAoJsLBw34L7uDM4",
"part_6": "7gyOO4PjzuC4MzjuDI47g+PO4Lgz6GBn4IXUvdOz3ps3b1x9NLHHXcJxl/AV7xIwUIDW3utBD7JdA+jtnb2f9JrN0kx6p5AUiTznLS16A2ghULmHmPAo42FuAlH0vHIJijpgOsN2WLc+XapLkdsciUkS099D8j9POCZVZy0/uN6VjgvCZwlPMjbUWmk0XiZJQlcVoQbNE2xWqYhRZ5xm+DCJJfWJJI1RSqZ4jYVW5IBMkYwkFeiDJBP02HXWKqJrGkXYmeuYgqF4SjJjlaAmITUOjZMoJkmRJsU6i0mUTqOMemU4OI0F2pqlHNXqlOMznTljYrAOr2AE3sdpin25kiQw45KmqTlZEUtJ+mQakeBIuglFNB8unBUJJ+O4JLVSUtfE2a+kxL6Kx/hsKERGs+VpTEMll05R",
"part_7": "rEiRkAonJJIEu4OJpEhr54TMxYSLlGYt3K2IU5KhhRDkBO68rRMyNs04d1NTzmcpzY2Tu4c6aTFKD7UgRcNUOicJpVQ3mFLABvRD7DihPTU46pOCbCFXdMUQxYbkBq9RpHSNSSFXLhrJgwo/e4JQk/ItzT/l0xFZ9Weo7TC7xcwL3eY3f73T0JFKxWQ7h/s+nc0r/mQFjyDB/wLJx3CASCcjyiUuHSEJXZA6VJQ4t0W/8k9HqUQStzBKHvBcPiT5kcR9fi9f1ZfKEXvzeN5lSvCTgUWRoC3jT6HtZyvizDup43yzE+w/XfBx39wOc3B6x9x7efBg4v98Lggqzv9PmA15UhzzZHcll6+5+NGpX92niwCz6L/tbB+xLQ+r4S4zedZWW1hsYVn3Ed8k7fr+S5Ak3ZmVfEQd",
"part_8": "lof6l6xv+BdZqAULQ8u7XKijj78kelRZ0QaHtx+PGxHUTRi0rP09bfvptk0EeOsKLwDjxJdqHhh+1+DeHPC2hepF4fu6Z94SGT7q0jwWdV/cRYLRax+KrnvBFEyBWodx6wr6ZbjtLYOIUWPa9hO+b+x3XLH/km1f9xKnDeewfaVEb0e8dG9G+9DLJyTKgJg7w70tQ3U4FdJEw4deuQpgN8z8DPxiOlR+gDclvTMd6b/4VsPWEyoUFoc30Z4LXcfkcF5+AkQQp020dgyTAJdRywXqwgMLO0CbSBw/PdfSez5R+8zzVAXJlAe1ieeQOuDsF0iwSu6nFRWkEI833Zos2mdpYCYPUov3qGzHeFlhmtJBGFQQAXmQ0nQwVh/o0oHO6EC2l5F256Isdi7SQaTUQYYNpyYCV4Qu",
"part_9": "U4F5yUEfEfA8CWQlQXUgW1k6CFFYOcSBjkP77kOQCFaNNMjFPLBRB2HKAlkewclBeNNg9Qnt1IHctFsEx0F41AGvfXsahIEHbtJBxtJB1ZMcuCYLMpoIxnrXhK6XAeHFQfh44EbV3SL8KUVbFKDul9twubeW9EJRRXQGEacxeTfV5Eh3/sJjehkTy4wAm9LJhs40xZKwzOk4RUsiAdd0oWMJJemYKYszp4ROMuKMBMWxUykEOj3TdKakRNqe/NBdktGAhJZTkdDZS5LRKY3I6BWrkHQqlKj2XIlMVe71kU7pSEpqeiUr3ZlTlkpXFkUEfS3dORjZCdZSJHhCGY+7Ix83r1jTYZHmNJWMzqlS7t7DZu7NrNIEU3dEpFRMfIrovC3VnNgZtWdVFMyMlIos3oY/+rVtDLXj",
"part_10": "R1AXJfvlhPJ1VLSteuRe+bStltzDZL8t89I6Zo3mdDSqktjhQDi0U2PM6QxScWKWjCnyqdTuEJOwn3BCn9QEFcCnO5PNCGiOQKkmbqnje6avFr27PWrHf3IgHdAcwCgDU3agzJNQTlZ0/JwROnTmTsmpLKDz7SRxh8+EI+ovSIJ2KY/qnoT2CfSthMMklXR0jO4AmaWJy8WU1qkwpAwn6IyZU6bmdISthEMuGZh19HZh64SMDpSloqRJOTNu/yKAqqmIaEYrRUYJ2/mD3OcSLE2P1ijXmbol0s2FygFirDu+FiQpyWivEO38SN8x/YVETP7Vzvu0fLnlxzns4UOex26Ru3z9AUnsmFK+vk9Xi1TiSZOE7xV48mlF5Gv8n7jr87Ut3q1N7xT/rPrDfwCgD9J1BT4AAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/71TwW7DIAz9FcS5lQIBA730D3afRrXLqnXSlExJOExV/308J5BtmtqeFsnGmOfHM5CzfB361L08T0OaTnInz1G+dR9pGqPciaconVBN/mLsrlnBRLkRUbZa6BsF/2GqCjKi5Npse6yVYAaokNvMsy3BqZ+RrS4sLFsH15aIU6Y6V8vXnC9s835WlP3/skWTnzUBSTdapaXd+46jbfhS89wS1CnD9R7CSQNnPVr1FtcYPDLeAUkNMkRAaoIyx3jNDAGJEADxhI4Ve8sQUoiNY3o1U6LIGcZzqz5gW2251mn2jhnAbBQL9OsJ1be5ntwBC32avj3hh36Gl/HxOFaKa7nfa4eL3Mhx+nw/5v9kSHm4fAEEdFLqPwMAAA=="
}
}
|
codegen__primeintellect___2016
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAlice and Bob begin their day with a quick game. They first choose a starting number X_0 ≥ 3 and try to reach one million by the process described below. \n\nAlice goes first and then they take alternating turns. In the i-th turn, the player whose turn it is selects a prime number smaller than the current number, and announces the smallest multiple of this prime number that is not smaller than the current number.\n\nFormally, he or she selects a prime p < X_{i} - 1 and then finds the minimum X_{i} ≥ X_{i} - 1 such that p divides X_{i}. Note that if the selected prime p already divides X_{i} - 1, then the number does not change.\n\nEve has witnessed the state of the game after two turns. Given X_2, help her determine what is the smallest possible starting number X_0. Note that the players don't necessarily play optimally. You should consider all possible game evolutions.\n\n\n-----Input-----\n\nThe input contains a single integer X_2 (4 ≤ X_2 ≤ 10^6). It is guaranteed that the integer X_2 is composite, that is, is not prime.\n\n\n-----Output-----\n\nOutput a single integer — the minimum possible X_0.\n\n\n-----Examples-----\nInput\n14\n\nOutput\n6\n\nInput\n20\n\nOutput\n15\n\nInput\n8192\n\nOutput\n8191\n\n\n\n-----Note-----\n\nIn the first test, the smallest possible starting number is X_0 = 6. One possible course of the game is as follows: Alice picks prime 5 and announces X_1 = 10 Bob picks prime 7 and announces X_2 = 14. \n\nIn the second case, let X_0 = 15. Alice picks prime 2 and announces X_1 = 16 Bob picks prime 5 and announces X_2 = 20.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACb8N2gC/+1azW4juRF+FUKDSSS7JTfZ/8J6gATYDeayGyRzmMBSPG2Jsgi1SE0325YwMZBr7nmAHJIXyaPsk6SKbFmy3Y2sCd9WtiGpyeJXf19ViYC/9ea5ziuue+PeH0ux5h+l5kXBZ7rn9Ra1nGmh5LXM1xwEYEnIOd/2xlFEvZ4qxa2QeXG9KdV6gwh/VsUdJ3rJyUIVhboX8pbM1BzfQOam4GtSV/iEIrByW+brNT4Xubyt81tY3OmlkuOJnMjfFWLGSS7n5P",
"part_2": "fqhtxw0IXnREnm+Y7cC70kOflai9mK3IJ9I/JpyXdkIcpKk9lSqQoOk0rnpUYNsl7f8JJ8vvbJz//4DwkMsC53RCtS8ny2JEpyshZFAQ6Tm93exBmvKjLn1awUN3wOZoBbI3Kw71bxqlFqEJfcWAnn8xUYUGheytxYoOtSViPy0ewTMQT7ccmzmop8B+bdL9FsXCZCE1GRimMuKvBkg9nZu1Gtc0hSCUdzCzery5JL3ex7xpZcSgUZBPtQwh4BM9d1ocWm4EQtYAN0PEEG",
"part_3": "RKNYKv3/tIwwCj+oEqV2HoF9BZahqmdGb8h3EPhv4oEMCT2EaQFksrYBB8S6XjdCmJ+DeFVDboxVGzIXdwJyYXdH5EeleWPwwvpoFEOa9nrzAnI73z09iLDeY6b2js8xkej1DLy95ca574HNy7xCskngAZ9bLTrXTfS4oR7JFxrDdK/2Sf6DuAP0z9cMw1Js4AUUcBACTzlk2cb4SVo2qqoElEgbZY9dPbAFeKnkbyEbHEmal6LYmR2iNlqYpIzIX1QNKVF1MYdClBUEoY",
"part_4": "SgFAdtxn5+p4oaK70ybk/kEH8+yk2tzSdc+oSkxRUE0rmQmF8s5gLXNb81pjLSDyGB/zYf8Z36f40HwHrjMNR4mYOsCWTjy/FZEJlBK1GV0NzbU9Hb09Ek9djAn2p9bKF9fGHVf//189//+YRmj85jaI/wvt/mayiMqkE0/k8kDQ/gExnjQ7PD/OMdGh1tpTRjx5vwTK2mRhcm9NHypifYNqKBDd4v5IaoTEe7JPGI/ATMehScqbqsnpIUZIHKtjFXY0KIbWAbaKD7HhA9",
"part_5": "6xufrylgU5+YFnwsmbyQZCgZ2tbY+FNxoAoQD+aLRwquG1tpNGrVztq1xy+1R63amU3mgaj30M2hY0PUYASZI7tDOQASdDJYgJ7VsB9nAcgqTBj+/qjuca8ZafsJhjglNz3a9EQ15yOYjCVfcGiOMxyUCxiIZJ1DhxfA5lKTRaEUdOXqawnQzdqNgPgYTc0CHrCK53xByvvltfG2Yn05gIkIMSPvyFLrTTW+uAAmzFbqjpcLHEhQNRdfa6AK1vAF8+M0SNjFIq+QTMP7fD",
"part_6": "fUalgI+AyMGlrYoZllQzkUcmjH7kXgBxFN03fNu9U56eEvMcQm8sNl7JE/GfexASAmssxCepDD7y5Nv5fNOYsxUzA4zHcJyFNfvo8/0IHdwYVv/lh6dCyH1GNjeR56AbwGXgivzIvglT5cwZmpPVEJDhm5JFefyppPyRngXVwEg6PNK38K+z/kRcXt6gIGkwBSkBJbex8S35dnZ/4oGsDJc7qPLsE5YhHE9HGNkNVlcCbO6d/oYclK2c/9/upshUgD+zwes7PV9PLKGDA9",
"part_7": "66N98bARiocUXlfne/8PYChwHp6thnD6rC9+QweI2Q32QvY5dEPSK+YFU3JOrhonnkeDehi/4SFFg+MwTC0jVxBQDJsprP5ggGs257BxTNWV2cqxcEHClOVEPmq0Ulfj8ZDuAwy6Vu8Fubwk/lHIzUlxeL6BOb5C5O0WFRrDV8MNO4dJbj1+Zwq6j4Tsb7doISBv2AcW7nE32E4aC2zxjezbdcEXur+nMKJgKY5mXBQABWy6YIPBoKGfVbOhRimHpDToucRQrI5U0QP5th",
"part_8": "S9326PPOyKyUGiiY4gHy4BYPx0w1aVhGFQ85ZDoPA9eRHVx+jSp9F9FuX9o3UJpmYfPnmAOWzcPo4EbA2g/VWbQuAVQJfw1QCem255uhScLgWnS8HpUnC6FJwuBb/CS8EepOqNr3pfvnyxkwy+EJ0uCKcLwumCcLog/EouCBMJza839XrYbqAZ9q6+TXp6t+GT3hj6gOnF102X7XmwYmhkN2HUAqBZVXZwmuXYrD545JcjwWhuQ4IZ/WooM8rbwMxMfzUc9c1PK2KWpXGS",
"part_9": "vB4zi7LUj1shWZBlUepgZhi1e02Z75CP9sQGrweK3woobQVyCf5bAdF2UoQOSOyt6qgpmBfUd0Bqzxx1KSHqp2l7sKIoDH0X4+Kgq2WAsiRz6ECMJnE3ZOpgJUsS1tE5aJDGvgNkELA47IA8xOR1pZ6lWYfjqC1wiKXJakd10CjJHOgYxxHr4BA64NIyITlJB4mi0I8CB8iI+lFHW2BRxEIXyMSHv3bIFGLCHGKZ+fDXHsvYD6PIbaLR9E0nGkIm3ZCJG2Tms7eFTMI0TN",
"part_10": "qrh4VZFLpBRlknpKOVWUA7IV2aW5pGYdoOGYaMJQ68hD6U+lkHZJKFLrH0U9YFGQXQMB0gg8hPOyDjxI9Dx07UkR5oG079Emu8AzJkqYuVpnqCdseTLPGZIy9ZB6Tvx75bejqbW5BFDpDQuFna3onMVuII2U4imoRJnDpCdlwqYkapi+MBDUPa4XicBIkjJOuyMsxcreyYkDHMztDlDtl+SXD4Rp5lj+Pv5VcCuFimLpflsB2QZs3ceJjiPwRW17UUX2veG+uy5g//A/wRkNxRKAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02QwQqDQAxEf0Vy9hCzyZr4K13ppaUtFC26eyjiv3eL4G4u4TEzYcgGj2VO0+0alxSfMMAW4DV9UlwDDM0lgLiOGUOYArRNABMzpBO9F9JKRSW0ohp66woWXx7RE1WF9fCNf55TrBqQlx75NJMz60uWTetTLM670s8xqS9ZV64IIlYxJuqP2LhDC2v8vu/5G0vKa/8BFFA1NyUBAAA="
}
}
|
codegen__primeintellect___2017
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAlice is the leader of the State Refactoring Party, and she is about to become the prime minister. \n\nThe elections have just taken place. There are $n$ parties, numbered from $1$ to $n$. The $i$-th party has received $a_i$ seats in the parliament.\n\nAlice's party has number $1$. In order to become the prime minister, she needs to build a coalition, consisting of her party and possibly some other parties. There are two conditions she needs to fulfil: The total number of seats of all parties in the coalition must be a strict majority of all the seats, i.e. it must have strictly more than half of the seats. For example, if the parliament has $200$ (or $201$) seats, then the majority is $101$ or more seats. Alice's party must have at least $2$ times more seats than any other party in the coalition. For example, to invite a party with $50$ seats, Alice's party must have at least $100$ seats. \n\nFor example, if $n=4$ and $a=[51, 25, 99, 25]$ (note that Alice'a party has $51$ seats), then the following set $[a_1=51, a_2=25, a_4=25]$ can create a coalition since both conditions will be satisfied. However, the following sets will not create a coalition:\n\n $[a_2=25, a_3=99, a_4=25]$ since Alice's party is not there; $[a_1=51, a_2=25]$ since coalition should have a strict majority; $[a_1=51, a_2=25, a_3=99]$ since Alice's party should have at least $2$ times more seats than any other party in the coalition. \n\nAlice does not have to minimise the number of parties in a coalition. If she wants, she can invite as many parties as she wants (as long as the conditions are satisfied). If Alice's party has enough people to create a coalition on her own, she can invite no parties.\n\nNote that Alice can either invite a party as a whole or not at all. It is not possible to invite only some of the deputies (seats) from another party. In other words, if Alice invites a party, she invites all its deputies.\n\nFind and print any suitable coalition.\n\n\n-----Input-----\n\nThe first line contains a single integer $n$ ($2 \\leq n \\leq 100$) — the number of parties.\n\nThe second line contains $n$ space separated integers $a_1, a_2, \\dots, a_n$ ($1 \\leq a_i \\leq 100$) — the number of seats the $i$-th party has.\n\n\n-----Output-----\n\nIf no coalition satisfying both conditions is possible, output a single line with an integer $0$.\n\nOtherwise, suppose there are $k$ ($1 \\leq k \\leq n$) parties in the coalition (Alice does not have to minimise the number of parties in a coalition), and their indices are $c_1, c_2, \\dots, c_k$ ($1 \\leq c_i \\leq n$). Output two lines, first containing the integer $k$, and the second the space-separated indices $c_1, c_2, \\dots, c_k$. \n\nYou may print the parties in any order. Alice's party (number $1$) must be on that list. If there are multiple solutions, you may print any of them.\n\n\n-----Examples-----\nInput\n3\n100 50 50\n\nOutput\n2\n1 2\n\nInput\n3\n80 60 60\n\nOutput\n0\n\nInput\n2\n6 5\n\nOutput\n1\n1\n\nInput\n4\n51 25 99 25\n\nOutput\n3\n1 2 4\n\n\n\n-----Note-----\n\nIn the first example, Alice picks the second party. Note that she can also pick the third party or both of them. However, she cannot become prime minister without any of them, because $100$ is not a strict majority out of $200$.\n\nIn the second example, there is no way of building a majority, as both other parties are too large to become a coalition partner.\n\nIn the third example, Alice already has the majority. \n\nThe fourth example is described in the problem statement.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "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",
"part_2": "5oqmrVQW5br1dUcjzKdS2HnfHHpmNR8R87lo8YthMvPrRdV1+vn6gT7W0ff+Vzj93RP7aiZlWr+57teLNd39Tr90TwRt/25TqegrfT0/OHcr2OmqMzBhvpXkJxzXtR12/qZU/35Z844mxkWCniUDWj+oIjVfe6BoHUNXyI+1ZsvSsbvr6+iTDCugv6Tbuh6qfy/mFdsZKbvXDA+dN0Pp/SGQvyp2R6HrdkUbV4MIuRN01YhAOku4ZN6HlEdzaWvYCbv01Thg8HsButU5vL5mkUgacXXto7Aru+bj7XvXhNFzzWjMOpm0+j3T9vTDKP0pom+06aNpd2CqRMy8sPLplR6mZUFPLvR3ZV0/bweB/2KkdQnrok6D4fuXBHGUxHNP1QXiWXore8Si9Fd3llL6F7yS5ZbqoSB9xBhYmF+eKaHTVG5GPNIGEAdWVfdzd1tbqg37aP1WfJjxe7BnG2/cAGICWCYdEgcykHHgxTC577lvEg6iR61X/Qi2MNq0bnuGu3nKkaj33YH1ARDTli",
"part_3": "wDN1p8DajptXbaWng3KGnVDPfd0pG+1SfZTd5VjT9zcgjMeyEUzKRwltxC7bJsbExWW3E6Yz/rZuOWhlF8wbAi6sNAT7HJu8JNOqabe3TM1Vy3gWyw/giV/ihvaxeWFb0w5cKN743XOsQ7Kq4cS9ROStS3q8a3lTzidxHS9iGmMz+wiVwLzVKI/bZiBipadV9bCFV840jbQAlc0oclol8P2Ri0WHrA01FVq7aJUeb7jICVCzi+MWOOFvuO5rWeBq2wMk3bbuSzFzF1CRXDTfyf++b3g1PsUae1NvGHjrukG0+rKWWAlib9eyeV/dSnXj6no2TWmxWFd/pib8K1x0/v//9/e//e9hYF3EPbpKgLC3iejsHriM88+8gMO8ivt1Uok1kWa816oVHJZXMCIJm3Op/jkzYvq8LPljl/yw7cc+YVw27TjtgdknYaJ9DmNgRFDMqIWanetwWBA88Bn8OJ9i6x8k/o+ckRzj7QMrqZSJtJX5ND7np+h0rm5Hy/HZKRL/XPs0Fq0lQVasUd",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/21SQW7DMAz7CuFzD7EtO0m/Mhe7bNgGDO3QJoeh6N9Hal3SFUUch6ApibJyDm/Hw7x/eZ6O8/QetuHcwsf+a55OLWzx1IK1ti9IyMhELWzQQiKKXQe+C1eJEuL1WbXZtSjoF6rcSO0Bm1AW9reEihWuHrmgVlhFjaj01GlPI2yAJdRBTDGRJcHIExQt6xRCkAcUJ5mHOTN3ZuskyAYrwspckf/ym3mJXkd5RGItVnczjOWRwCB71a5Apd0zc3Kv7GlUCMnkJmlYvXghyQY3Fr3HrEZoL7thkYOqqKNeejZCG7l3b73EupxRZF0v1JabR4zO7kQf5ulmvD5KpCWo+zeP6IO3m3nc621VPchxj3aXsAmn6fvzlX/acebn8gMdnTb8gQIAAA=="
}
}
|
codegen__primeintellect___2022
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nWhen new students come to the Specialized Educational and Scientific Centre (SESC) they need to start many things from the beginning. Sometimes the teachers say (not always unfairly) that we cannot even count. So our teachers decided to teach us arithmetics from the start. And what is the best way to teach students add and subtract? — That's right, using counting sticks! An here's our new task: \n\nAn expression of counting sticks is an expression of type:[ A sticks][sign +][B sticks][sign =][C sticks] (1 ≤ A, B, C). \n\nSign + consists of two crossed sticks: one vertical and one horizontal. Sign = consists of two horizontal sticks. The expression is arithmetically correct if A + B = C.\n\nWe've got an expression that looks like A + B = C given by counting sticks. Our task is to shift at most one stick (or we can shift nothing) so that the expression became arithmetically correct. Note that we cannot remove the sticks from the expression, also we cannot shift the sticks from the signs + and =.\n\nWe really aren't fabulous at arithmetics. Can you help us?\n\n\n-----Input-----\n\nThe single line contains the initial expression. It is guaranteed that the expression looks like A + B = C, where 1 ≤ A, B, C ≤ 100.\n\n\n-----Output-----\n\nIf there isn't a way to shift the stick so the expression becomes correct, print on a single line \"Impossible\" (without the quotes). If there is a way, print the resulting expression. Follow the format of the output from the test samples. Don't print extra space characters.\n\nIf there are multiple correct answers, print any of them. For clarifications, you are recommended to see the test samples.\n\n\n-----Examples-----\nInput\n||+|=|||||\n\nOutput\n|||+|=||||\n\nInput\n|||||+||=||\n\nOutput\nImpossible\n\nInput\n|+|=||||||\n\nOutput\nImpossible\n\nInput\n||||+||=||||||\n\nOutput\n||||+||=||||||\n\n\n\n-----Note-----\n\nIn the first sample we can shift stick from the third group of sticks to the first one.\n\nIn the second sample we cannot shift vertical stick from + sign to the second group of sticks. So we cannot make a - sign.\n\nThere is no answer in the third sample because we cannot remove sticks from the expression.\n\nIn the forth sample the initial expression is already arithmetically correct and that is why we don't have to shift sticks.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+1bzW7bRhB+lQkvsktZiAMUAQQQQeKmgC9JARfoQTKcNbWSFqZ2Fe7SihIG6LX3PkKfLE/Sb5aURMtWHMtWTAvaHELOzs7/fDsCky9BTzhhpQvawR+pGslj7WSSyNgFzaCf6dgpo8+0GEkwgKR0T34K2r++fNkMTKoGSovkbJya0ZglnJjkUpIbSuqbJDETpQcUmx7/BZ7zRI4os/zGLKAMUjEa8Xsi",
"part_2": "9CATAxCnbmh0u6u7+q+h1KTlhKzLelI7C1EjSDf+9MlYxkok6rPs0dteFgs2VCQkdI9OYgV+1VcxHeEhlbR38vbkaJ8PTiESRyDFOpE6Ggk9BR1GWOrDDy/8XMIxDVqLTqDTIS7Wbzgp4qFMLVkxpT1tHIlkIqaWMt0XKk2mrEM4mkiKheZ9eQkvYpNpx7LIZOlCSA8u9ApjPA3BIZEqN2SVccUeb2qLXsO3CYtXtjTT",
"part_3": "QhUsmQuYh0r0ej4UNjt3qYjdK/r297/0Jw43LCFvQ9csU+Ft4wcLnRf2GbQQrJPgY2M5ASiQizZxTrAnP41TaS2iTaa/fJotE8s8bjqW7Q69LnlOO1YNNIWnnTdXKdFp52hGob1D+vbPf/S6SW+adLTfIq//xJ+EVm2VhZssfWIoTo21CGRxuE1GS7qUKd7KimDCEPX62WgnEmTC67smZ8FSimohZLLqjqpmSCTJFDLS",
"part_4": "FO1Cqg8PQ3oDsUctX7+ygWYYcI1ciYgvkMQYRCtRF3JxigaKi+V8uhzVFr3nskEWfOZRukPVh1hUr0EFsHOekfZMWpZeyYIK5NLeJ2sKve6qO+cyRmuvcKlF74yTywWdypEpm7zM+bxMF4Kb6AuoXJwqzLnpEKfeIgScpqgMHJR4Q0QqdcNRX5xnieHmcNX+aNERHJ2aDPWajFHOr/h0Vx/wOtbjzPknJv3pFelBIhFz",
"part_5": "hCvmJCtdtJHSygFKKua36Ng3GTApFQBE7tEbondTEpvoUHQPXSlf/3z4/HmrYuD7zFUtPO6zdBxUll0Ws75eClyRyOUcGsanMmtNAKvSXBUQUvW5GxyPxugTBRzuBrQ3QSBNVsj+mCHTFl1WMaOwYSaOuaAxS3xdVkP1u4f6EvXTEcJkvBDAB3u4yLRjuLJiNE4kcvebYT8L4fITQIrsWMRIzVAwYAEfW1figlqgEavH",
"part_6": "8XnTCW0n4JwZyVheKB+xXSnFCeoF94C/HcDGxcKCUo7ZSOoSfa2U1y2s5Ortp4JWZsvXVlfneZhHOS9mLPLJ1BnZmz9j9WSmV3krCanwzqT+AOtc6g1WLO3MneGmXpSdLhKn0rnnVxGkqLpFDocq7dEgNdmYI102c3knF1IAR62KaItQ80VUlb1AhDlKV/SEHhNmQsvzSyr9ZboQNhLoQUEH/mSr7PiiirUpqwR9XnGh",
"part_7": "tIcBMLPyOr6txraqcyh4N5zJuhlLfCclALTedNXVwdDnynt9MpyyMT3fHUNxKRcgUHo+wzPFNUATlSTwApsYs7wkrnGLzk56ZVdM+R63Jsmcv3548ukZLhL+8w6ta+dj22xKYzmpdFlauIkZTrYw/aWyj6jqmIdBB7TzJuztd/UFXlyrj+lwrxE1QODb9QX9QhfISSL1ngMNNyTIoGO8Iyy8u87hKT2LqBE22sQSQWjT",
"part_8": "KUqgkTcKLplYOdtre3mHvO86FxVGmcyEH7womEH2XG06ODydM0DV83J/0VA47wMFI+GjHSeKZ1kgktJ4L0Oym2530+1uut1Nt7vpdjfd7qbb3XS7m263brqdCbFBuxN8+PChmNa6eisn3a6Gh8FpM2BUgMdB50s34FmmG2AYCnzAz8pQBk1QfASKzQo0IMh+t0DD2fYcI3j7a5PuInoBJTfJrgDF3WUvoOfBRV8FpBVR",
"part_9": "WWa5e2TKFVaeo/zGtREXr67wOmmFMY9k4C0rXLkT1djqNVZ4l7ysvVZW/VZ4l6+JNzUtmPCOdV/Dhgh/3Mjop9R6zbyO8u3x+k7Zrm/XPZyLa68axCZcx+onc4HV1LufUfLhFqe1pt7VMq11QeCwHnb/BFyPHquNtsO3vI4DQfiIad0O3/L1ujVaWevRmj8DNyAyyh9YZL6xn6vhk70OntaEUlv/8premo+a3u3xL3/C",
"part_10": "P6ejzWT3AT5TbOzzxwq0qWitwfVWSc732mf9rylhnn/vDr1HMPLV6ZtpvUdQoltCEt0HcDcQkLnLDx+Q64PkZqaX/Ja+uU/Qt+VnxGN+/qn3LRdev2e+E6rr3PeZnaIfmkCi+3kYLgPxjf8eYNmatdREtyqJ7he0KM83qyLawK+2rR6Tt8e/tSvm0b+91f2L1mMV53L4T/k/yNqzTKuPmQzaLs3k1/8B7gFr8GE7AAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/6tWSi/KL81LiS8pKi3JULJSqo5RyswrKC0pjlGyUoiOUarRrrGtiYnJi1HSUQDyaoD8GqAIECALgoVt0cWIAdpEq4TYSk2A5FqYr1CFbDHU0BzY0sMShKeg/gYLxIJE8ktLkGLfM7cgv7g4MyknFUtYIZmDRR02rVjSjjZ6uA+fUMbhy9haJR2l4pLKnFRgdisqBVK1ADOqrsqGAwAA"
}
}
|
codegen__primeintellect___2030
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given a set of points on a straight line. Each point has a color assigned to it. For point a, its neighbors are the points which don't have any other points between them and a. Each point has at most two neighbors - one from the left and one from the right.\n\nYou perform a sequence of operations on this set of points. In one operation, you delete all points which have a neighbor point of a different color than the point itself. Points are deleted simultaneously, i.e. first you decide which points have to be deleted and then delete them. After that you can perform the next operation etc. If an operation would not delete any points, you can't perform it.\n\nHow many operations will you need to perform until the next operation does not have any points to delete?\n\n\n-----Input-----\n\nInput contains a single string of lowercase English letters 'a'-'z'. The letters give the points' colors in the order in which they are arranged on the line: the first letter gives the color of the leftmost point, the second gives the color of the second point from the left etc.\n\nThe number of the points is between 1 and 10^6.\n\n\n-----Output-----\n\nOutput one line containing an integer - the number of operations which can be performed on the given set of points until there are no more points to delete.\n\n\n-----Examples-----\nInput\naabb\n\nOutput\n2\n\nInput\naabcaa\n\nOutput\n1\n\n\n\n-----Note-----\n\nIn the first test case, the first operation will delete two middle points and leave points \"ab\", which will be deleted with the second operation. There will be no points left to apply the third operation to.\n\nIn the second test case, the first operation will delete the four points in the middle, leaving points \"aa\". None of them have neighbors of other colors, so the second operation can't be applied.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIACb8N2gC/+1bW3PbxhX+Kzvwg8SIYiTVcRO2TqcP7tQvbmbal47IynujiBG4YIBFZDWT/95z2QUWJGhLLPzQKVexBezl7NnvfOey8OTXzEgva+uzefZTlW/se+dtUVjts2m2apz2eenunNxYmABduTP2UzZ/c/V6mpVVfp87Wdxtq3KzRQl/L4tfrPBrK1ZlUZSPubsXujT4C+aowm5EU+MbToGe+0puNvheSHffyHvofPLr0s0XbuH+WTZCVlbc579YJ6QAJUW5Etsyd74WJXX5Sub3ay+K3NmZeCf1msfFWtYwrsuirISs6/zeWSN8KXI/E3+BPp4lp9B",
"part_2": "RC2dBiCqrmvYj3XiTx3UOEk3pzlAiHE26J1HChCrOUNY/WlAP+jYwaoTcV8OLTVl74R/LZKdLOAHABMjRhoVdeVrf663wcLMIxtZWq7LaEBQ/N9Zpi3iU0C3RSoSJX+d1H6mZeO9IajtxKp5AmrGF9XCiouifls/ZahoOAuKkMPlqZSsLrwysX0vXwYVQ2mI1Ez+xOMSSNzGizjdN4aWzZVMXT4D6DMy1yiuAhXXRubFBgaAN6QEWU50UxAe2c1F3BH0m/rzylnRhWRp0ikihbs5+8t3ZhfUaEIHTuKTzsWwKI1zpW1TAzqzHNAoFCkSxOdvkr+Wj2BAjOhM85o",
"part_3": "AnrnCWCRfXNM7nxZBCprQ1bd0SLAAAi1mbP+FmC3eJ7b3bNp6esIvewBjOy9wh4dG5Cot+gV4FRgMntJUGBxfvYCSv18A0D3jV4kyeXZ79+2wm/kH04070tcQBztjQtcjZzmVlAGp4YUtB1xOZWVYVOLA1zEBL7jjnOEA2ZvEkvaZu5g/oF7lPHkKbTqmvtnAqc2hFGGXa9X0I7YvQ4Klcs1G2XRRgzTunvSZGXV/9680sgfhvjU8x5lfyIDxWRBvxBQ6BSHsPe1yyadsNU0oQVkhLoHKgQwcVR7d+bGu5QtCC2BIiSGX3iJFq/e6T3GwLWwe9iRkLJ6VS3SEW7",
"part_4": "qZlDY1pKdPRa5YXJH4ovU2YlpjTW/gLSTVNOhNvQh+ILgpBb5MbU7TaI+SFRa6HjkUm1SKbBpxoceLzj7lfpzZvtyHiAihxAYAUBBIPACS53RZPtBaiYpUshcFZcqgg+SWnogzXtFkguAcfdErHo5zXHlAuspn4QFF4xbmCvL1LB0gZyivscFNRl4OnDpEIzouny61pyZ5TLIho1B6yLmGNwaheU4DbVugvT6h4XRZNgALnlmh+/PkAMa1us3hM2iinsr6pXPBFY2dQDFSW0oHG2qAWb1mF8wnK0U11VwCx3woglYRft0voXMsqPIITiBxxo8Bxfo2gufN6MoHU",
"part_5": "L6DlK1Hf5kvx9i3+vrxezkUUeUEycZItahvmC0i8gIh15jzMm8QB3DWOsaxuKNWSu0DbfUF9Eawpy4HpDo9+tXDA38LSMeRE/Ciug2YonTvDyZyz1R1UPbjrVWg8tAeKu7yetAckUCSC8sdOyLwnD0e76fz0AP0wei5vr5ZTmAEyl9PzbtWFuJ58++1N0O4VceQcKDsX6JRQIS2yP5AQfH0I01QwIx3QPt4llh04iNs5RI5mvRI0CZ5Ao2Q8PeiP4mFnhDaPpsA5lw+T/RlRpdaS8Axzk5k96uxuevPNF7eFgA+zXrT1q1c4zviqsBLJA3x+aEmPTFEpfYimCO3",
"part_6": "V8hvXdcE2Ke7xGWYlBNAlZBImZ8eHAftcTXnbPttIwi3JWKKSqkeuoG+7Mftq93pBLgu5MneN7S8bwL7T9iLxxR6qu8D2tpr0+NUOhWPd9HULGF8KUrF3wojD8rNMeXVI1Reo2UP3wNYYN/XtnCZdpAPB7Ml2t/PlQExkEYoGF46pB5SbQOyuIXvglQ1vUA7eQ6g/XeJOl7jTJe50iTtd4k6XuNMl7v/hEheF1Nn8Nvv48SMn74U7XehOF7rThe50oTtd6P4HLnRpjFg4iOLZcpphLoSont3+usj809YuMgwBlFTuQrrIMBpQlOdBKjVABPWXXFHQwA31/jYVL5",
"part_7": "KFpcmQtOsjpCmltVZqPIFdGxR59V+IVNjoQe42lcygOWqoyYNt+PjHmEfp0aAcDUA1lkqj8kQdcIrfHXPC7mdcDZk1Y+k5yEpldlqPmTq0PQrvk5onDp//GGMrCy0Kxq1s27DX7LXuPP2Z2LqXOM2ChEFlvz+KADKGBsXP8akd6Q/RS/y7+4t/M7o82C77uiQYIsJw089ow9nmzRHKajSrkRYwsFKDBS2AoaUGMmgDfRqeNWhuDYxig90xRSnsVBJXapiJxsYRjVKA4gbtjzKk0aNFgb7H6J4zwd77TgUa74PfdzhmPQ3gw6Cu371cV9wgIIX64G8EUiPXCCd8w",
"part_8": "kHSm6YipPAfzsW1OFHRSgKbWMuH1GHZoK6vjyXsAMt64WegK6Zs/dm1NGdQ198fy4H+Vjs9YUqq4u4KvX+oBIJBXY/wLdIh/AlMQF2UDgbWwchEi9bOGv/iNyZM0I8HNQkjXZE+alwOHBuOnteGM9fr47IBBXLGRbZRnIN6GJZdNRnmy9CRFpFxsUzyiFLjAZum+zZoteGGEmcSxyBedbGI21CJm0QunDBelo3ZMeIRAFQxX/Y9X+78BORVV7LHxy4pj3VP+gzPWqwP3RPQfQ5dHtL3YV2PiFqaoeEEyemV3Jme0I9xgIM8hVNJPg4uzhpxiNDRDpwqeC3lDUoN",
"part_9": "YwEbSr1+qowJV+vd7Kn2alvbJlRzKOcO6vrDkdmgs17/btgOte975j7EjpQK41UEFM9VMD2FcS4JQnmKBpaU8SWP0h/N1YIOAY8YxD9KdmfT7Hpj6SoT0Ydu1dHTkkl7BcBOZdGTNVZFgGUo0M1iwQkUxQrVYjkLVFQWIbZ4laHrCMVSqG+R3jBTY7jFmhficFBTUiFs8GBY1wJvod61ZrSPOypUfmR7jog6ZC0dSynZdsccxyWBlIEXiCQ/cnBQOgYFlD6WroevMck9cb89/5vMqAH2C00O3rlHKF+O0PUAVLF3MMiG4fYKniR/vqp34uRBXX8YlQRDN4G0a3j",
"part_10": "CbpQe9dvci9vnqdx93PjSh8Tvjkd2j5bDVN2BUesuSyWXoD63D3wqO/4T7UDO73E5/G7v3n0Mk6Upg6lgGDV3yedQdo+qX6oD0q6xQoGhOs5QPjeaPsVgyNcm1HsY6A0MKZiInRj8IT4o/DLDC7SBCfAfdPEnGRyWsdTE3DDeP0wcip0pkj0Cx5zaLxnCP0kMJYjRQoHFhGi4hjLWhK+cmOxpa3qCNK8MlgrkS5o+fOE3LrqoQ0VgqHBg/8IPWVYR6hLtAJWB/frfC5+ZRQ8ltqT+HibB919H2f1Pni9Q+uB3guBeS/zf6eq7xuU/Nzab+6qxv/0HUHPcPY83AAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/41T2W7CMBD8FeRnnhA9xK/UVbW7oBapClWwHyrEv+Mdrx0nJIjJtd5r7LFzcd/9KXb7r9DH8ON27uLdsfuL4ezdbvXhHQEywsRjKWTghGlFDeYRGyzofefdeqVkqbQEaR6lW5M0YmKedFdXU1/JZBktES9A7jzN+su4kvEyDg+wQDGPQUbNK0ISLi7SIoAwWT+4qKY1ypbyUmRR3I2MrFIlPUg1SZIlm6CdkQtKRW1E8UDdnEXYKyoXN4dA8mSHlYmdNG2EdlhFyhO7dbPxBZ3kOekrj0DJdkpyUNAMc9Dp8zN79tyGjA/tgP0AkH0q2ymG5rd7rbN4q9Zm1txW62XGt3nPDFe3dufw/3tIv3gf0+d6A/j5btL6AwAA"
}
}
|
codegen__primeintellect___2047
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nArpa is taking a geometry exam. Here is the last problem of the exam.\n\nYou are given three points a, b, c.\n\nFind a point and an angle such that if we rotate the page around the point by the angle, the new position of a is the same as the old position of b, and the new position of b is the same as the old position of c.\n\nArpa is doubting if the problem has a solution or not (i.e. if there exists a point and an angle satisfying the condition). Help Arpa determine if the question has a solution or not.\n\n\n-----Input-----\n\nThe only line contains six integers a_{x}, a_{y}, b_{x}, b_{y}, c_{x}, c_{y} (|a_{x}|, |a_{y}|, |b_{x}|, |b_{y}|, |c_{x}|, |c_{y}| ≤ 10^9). It's guaranteed that the points are distinct.\n\n\n-----Output-----\n\nPrint \"Yes\" if the problem has a solution, \"No\" otherwise.\n\nYou can print each letter in any case (upper or lower).\n\n\n-----Examples-----\nInput\n0 1 1 1 1 0\n\nOutput\nYes\n\nInput\n1 1 0 0 1000 1000\n\nOutput\nNo\n\n\n\n-----Note-----\n\nIn the first sample test, rotate the page around (0.5, 0.5) by $90^{\\circ}$.\n\nIn the second sample test, you can't find any solution.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACb8N2gC/+1a3W7bRhZ+lSlRwFIrGfM/HAO56MUuNjfZAt2bwHIdShrLRGlS4U8dIckD9D32yfok/c5QUmjXbb1eJuiFRcPknDlzfr7znRnK8PtknbVZE9rkLPm+zm/Cy7INRRFWbTJLrrpy1eZVeVlmNwEKEOXlOrxLzqyws6Sq801eZsXltq5utmThh6r4ObD2OrCrqiiq27zcsFW1pht0lkW4YV1DI1",
"part_2": "KBZFNnNzc0LrJy02UbCHftdVWeLcpF+V29zVjesDb7iVQytgnVTWjrHQvvsptT9q9QhzgPW0XWtEcX1VWURS0y9LrqWAbdTf5zKDFVB/ip8rJtWDZjyxlbRbV/Ijd4iTMso+cSP5sisKZbXWNd1rL8it0GVldt1vZ5binorK466MdxXL3cxUFcPYuPZbjFXJMTnBRgdoi8AbQs65+rYn1HCaFle7v31y8fs77P",
"part_3": "64DjuuqWLSGZXx3wj3BdY3XGmqro+nU1K6uWTfLTcLpXrQnMvCG8HoQna/Pmaneo66oq1zGEKdWo2LIYwDq0oUatw8H92y400eGD/mPki3JOn5fltmvjE4n+Q4mWxY4VZAzO2iwvG9bk7xgiC5tQw9zl+3cfZ3Tb4bbsR8t+tOpHKxqxyYeo+mHGPkRlelgeJMuDZHWQxEUf2K+//JcJ/qNHgi/bk4aBunUG32",
"part_4": "Hds+RIhCbybg3ocnTSMKd/d+0wKbQeUF0kr0OzSP68QDOovaqgVVFlbvMmHEm+Qkm20VLIwNgitMAcqKBOO0w2gU267RYiYIzuDPV0GNI/0C/bIjT7oCLqi5Izsb84afZxwx0CLY9KcRqX4Lz/NVRFsOXAzauqDce8X5b9bpHX6N8m+mcteDH7ox6b8FMzY/g1pSb72vMf3y8Wq7xeffz6dGCwCcTCuxZ3PUIn",
"part_5": "LdxF+u6OmJ4eiJVTPuw2Lwq2hJV2HcFbx7XNddVRg0WAIag/cbatSLeibOl6Vd3S3H4rPJSR7NSh7epy3ybrcIodtQ5XaLByRRvsOlxBJVtfEncmU9oG2/2Sc4gm+RQbKypKNY2hTqanzbbIcb8gx6uqqtcNezE0sij3mxzE55Ne4zy/gGD/yL5l4mJgGFTehAmfgT/lXn86Y5I8UHyQbtrry+ZtPSHDd4KcZO",
"part_6": "f8gs3ZErcp++YbJmEcQtELxV5Ioea/t8S+ejGUUcy99Qj55ORVdYJsQoGlk9UdR2yy7H1k0ceLF6QwdEoKvFfAgoeMNmEoBb1PpihOBBeFaWtsMhjva/l81D0fdc9H3fNR93zU/U9H3cFIk5ydJ2/evOl3wP5YeT72/i7H3qJEaZKLWUJcQqmS8/eLpN1twyI5Q0NGplzuOZBQi8aS9JPDFoLdOF31zRHnqZdI",
"part_7": "jl3p8UZ/33IPmUbvPcEyR604U2w8m4rpGK1majwI5pR2/xmAcRCM50d7YWS0T1cqvBwT7LkAKhqIz9VoVuewJhkZxm28YE2sIJn8A3ifFCssKkpf0F2PZ1eRPQPLeBgx3AHHhs/36OcPny/t+NPjiEgaZ5SQUjCVCiOkEZ7NnRVCydQbEEJqrVOZortlio9zJFTOemnseBWVVguvhAdh4C511iAip6xNtZaWza",
"part_8": "1SnlthgQ/iMN5JAVpp5xG/Gi8MBGEcciTKSsOlQShMWESmuRMs9akRQIt5C4HmxjMpsEabEStiuVNGKeQ/t5Lb1KXIWuqUSw8MmHYQaAXXTqbSGBkLYjUuLt14BQG/UQgLJKxOPU9TnjIFjjjtUs9SLaTzmviaGq6IJZgGYlYZM15HauANxmHvEFZqbj2ytk7ih0knkbGgCLxwKUpgcG567zx36Yh7gtdOeZVK",
"part_9": "7DTaG+u0VgJVF0YZ6oo52IJnSyQ1UjqLwlEHOayw1poReZHCu3KeeI9qgProT8+9UwqYo32NNxxNBOfcoGJK4uQx1gAYbkfcMKTl8MU1M2AC+hA9q71VXHHHnFCpVVQUjJ3rNzRjELo0csT934EK2AE0sHAGuCiOZOfoVgMxF7SJKA12pjjTTepAIoFzSGFeI7AvsG8/uGsPdUZ8W3zQ1d2A5o8/RZ72unY8E5",
"part_10": "9+cP7f74mDIL7Aif0nBf88db7n416JP5Mf/ig/T0Gw/+Yk6R1uNJufCHAvhYdpMiZmh3T45zAqR/xOssd8RNSPXylHfMMX+8zFqHFSlHiRZSNWHidtirNHeGvxgiQt3gePIz46G4YbwOMp/VSwJNP0tdCPnEXPFzEq//A2Qn+GGDdQGb8T81FJjcZDqOYzNPRf/FXkgv6ZobnsyvxtF5Kztu7Cx98APP6DMA0hAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/4VRwWrDMAz9FaFzDbIsO0o/ovcxl11WtsFIRmIfRum/T9lo4sDYZIyk5ydZz77iyzTW4fmpTLW84hGvGd+Gj1rmjEd4zEjg6W7ggWy5Dcl5yHiAjFF7ZQHfp0QKnNjLmlnNylvq2bY0mOso9exZGFwXNaZA1spF1WgweXAiQYRICTRqF33nA3CwcwkUdr13wzaJ6++20lvqFu7k7eJfVH9fYnoYtimcqWBDZXE/1POCj7U0z/pwmdeKNj6N/4R/k883POBcPt8v9pVTNXf7Au5Nb9/iAQAA"
}
}
|
codegen__primeintellect___2055
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nRecently Max has got himself into popular CCG \"BrainStone\". As \"BrainStone\" is a pretty intellectual game, Max has to solve numerous hard problems during the gameplay. Here is one of them:\n\nMax owns n creatures, i-th of them can be described with two numbers — its health hp_{i} and its damage dmg_{i}. Max also has two types of spells in stock: Doubles health of the creature (hp_{i} := hp_{i}·2); Assigns value of health of the creature to its damage (dmg_{i} := hp_{i}). \n\nSpell of first type can be used no more than a times in total, of the second type — no more than b times in total. Spell can be used on a certain creature multiple times. Spells can be used in arbitrary order. It isn't necessary to use all the spells.\n\nMax is really busy preparing for his final exams, so he asks you to determine what is the maximal total damage of all creatures he can achieve if he uses spells in most optimal way.\n\n\n-----Input-----\n\nThe first line contains three integers n, a, b (1 ≤ n ≤ 2·10^5, 0 ≤ a ≤ 20, 0 ≤ b ≤ 2·10^5) — the number of creatures, spells of the first type and spells of the second type, respectively.\n\nThe i-th of the next n lines contain two number hp_{i} and dmg_{i} (1 ≤ hp_{i}, dmg_{i} ≤ 10^9) — description of the i-th creature.\n\n\n-----Output-----\n\nPrint single integer — maximum total damage creatures can deal.\n\n\n-----Examples-----\nInput\n2 1 1\n10 15\n6 1\n\nOutput\n27\n\nInput\n3 0 3\n10 8\n7 11\n5 2\n\nOutput\n26\n\n\n\n-----Note-----\n\nIn the first example Max should use the spell of the first type on the second creature, then the spell of the second type on the same creature. Then total damage will be equal to 15 + 6·2 = 27.\n\nIn the second example Max should use the spell of the second type on the first creature, then the spell of the second type on the third creature. Total damage will be equal to 10 + 11 + 5 = 26.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACb8N2gC/+1azY7byBF+lYJyiISVhf5jk63sBEg2QeJDNkG8t9HEpqSeEWGK1PLHMwNjgVxzzyPkHfa+j7JPkqpqisOxpbVNe28zC0his7uqvqqvftrYt5Nt2qS1bybLyT+qbO+fF43Pc79pJvPJdVtsmqwsXhbp3uMGXMqKrb+bLK1M5pOyym6yIs1fHqpyfyAJL8r8jYdm5+G6zPPyNituYFNu6Qv3rHO/h7amJ9qCKzdVut/Tc54WN216g4v3za4slqtiVfzTb3zR5Pfwt/QOdmkNN2UDu2xf+/wasqIp4VAe2jyt4Jtv/gKryR+rNCteNGXhV5M",
"part_2": "F/KF+ZwmyGlJU6pvmno4HlG2aww2im/daUG7NMIp276uyrXG12h7tr2HbVkcEdPCQp/cL+KuvPClATVBe08s9YyCh5W1RQwGbyqdNW/l6DtmzZnfcBpu0gLWHra83Vbb2W7jN8G1zW5IBa1/V8PO//wtZg3b4NMdXu8PLt9kPkBZbXt2me3Lcdn9DywvGkeZ1GcCgmOb+4GtSVx8Qc43YoW7KzeslwJ/KFkH1koNJvaUw7VQtLzqlP/2oZr8D9G2d3SCoN2neMt4z59GVAwunnYkP4mYLICe9ILvo8HVW1Q3be/RKW6NDihL2JYnb4WIKDbKUUTRlk+bzo9",
"part_3": "bab0p0CZ8mjz06tX7n1AKC0qGakoRvfNUgZx4w7Nu8yQ65DwK6c/Wjg7g9rdZZU6XVPZTV1lcLeN4gHYrfNlAgi+ua3qA3cDvGJg/2sqDFkSVIHlSZI93XbX1PPD2kTLTrskLW1+gcTDXwd+keGUThRVH16xruy5ZEb33jK8wlD7e7lJSzkn16l+3xGIM+BgIdRkb0hCRRhCfd7DKPxM8ooGRrPaDMvsTQlIeGxd0i58nwVfGM/p4Xh7bhX7T0HaU/RzInczAq5FGyp/KeM++GWF3MIZ1jYKYSfv7P/zBB6FP99KMU/4rmIPgxDYvi+LwebppxmAllSBTCN",
"part_4": "UiyzvSOHQNqUeI8fjmgzhyjgC+x7L3xeQBJeAYZixG9w7AyuPqIbpCvw/w8Mr7DGN7M+2VaQyQuIAkV4EAF96iK1R4xDT3+97YZuhwrd9EAVda89zDL5Pi3+8fxfwg8RX2LrBuK/jMyDPled8I5tqtCgQS5KqQAGa0KS79XRbACX8b01O3UGCvNO5NVEYPEnRGoR9ttUNcp/LZsfI/keTEIlw+mcEmrd2WbbzmD+uw5EdyyGEb0iHROi8X7B4c143gSa/qDy+E7Pjf03m2G5zH1/fctJxY6BL4Ci6URLkDFiwGKTvzHwjhhTUA2Akazy6rtEMcvQxAIQUr8",
"part_5": "iAiEfeA9xbTfXzdbqnWoiopOB+XA3MOFivpmy/SlHtpsSwo2/fdtedv11K7v8yRAcrAbt1WwGOcEv8AJo/LX2EyLDQ0cv+nmAeTTNc4YUN9jLdofyqoJtnTLm5J7OWruX9PEsm1adHswYeuvqb5uKWuns2WvmHZM9+lhiiDmAe50tqgPeYbfs1k4fCxVFwMRq2JHAC7g8h0Z9PpBAJdvroPcdtHmxVFGPZ1dkXQstwVONmscGAD/2J/Tut1Pj9G7lFcspu9JKIqUk3k+r313kJYWNYKfvvb3F3m6X29ToGFpyZ+X4gqehV/yioHRobVHfl2ACE9kCvy+N4X",
"part_6": "+cnxLki8LPL2+Grwo+SRWmCnW5zyIz4Ps455TVl8ui2frq4GGgRkkjH7O4QE8yv36a0hnKH3okGdsQI/jpKZgG6qbLYcKP04ZvT6uz3o9ITofF54hxK+AjnTOGqp7hGr2YRzvSCUAsxmmDTMOU6ahkRefuyx7GsqfhvKnofxpKH8ayp+G8qeh/GkoHzmUH4XUk+Xl5NWrV2EiWBVPA/rTgP40oH94QCfrMG0mV/NJgwuYRpPLt6sJFYfVZIlDMTPvZZefkzmuMNXDy1Dnj4U+VHqUyNvKUL/DvpiXsZl9vOzQGbrW0PWG0BxOarCfrkGiBrHibnVSphwnUg",
"part_7": "n6I8vP2frpcmMsteRD5UCRoxMDiryiDWhDqgzE5IEkAodfRkBE252DJDlpg460HmOGZTOw+MccbwmOPYguZDMExswGOw0ptg4igist6JN22FiJMXYkbEeSgCK8WoDp3EBBSzQ4Mi/WAT5SyKjOe/Z0SFRiRtghFcRsSJyATBx7BCMTkxEukRBJEqpxjyX9idDYPG3Yr63jHxhaMj22KCKiJaXxlwxp1b1U+CMmCQYDHLnTrpRauEiNAqHQQcweBU6T5yJ0YcKRcRhC6Zh70oGT5M/IYADYoxbHGWnJnlggFWPap5XF4HPUSQrzLEHCOsc6EgtRwg4SSJJIn",
"part_8": "MYipBXom3hE4UAuas48JRKLvreJsmyEdughcqQRJjqdFUoJp7WK4s9MfXOuppgxAcKs+7BkZbtU/5yCZdSvY/VZydaM6Qx916F8SYAzCs6EdFQVl9wYqK19uc4QZGowp108xg8qNDDJ2COQ/ef78kclUtR3d04nUOJMEOVnWB+S1XCDiM54x40qA30Qf2k2kSMmh4juQCL4RHb9L7Sh7isKTfh0s5FmDH0exfp9odEYD+nQtlXCQrUCE5+uLcnINFWdj0TPTBWFCeYEQ+U4CPpXQ4CN8aPGWyPH0VM9YpDSX6xCosExSw+1MQrOCZMKf2qeqe2wjBre6nhr",
"part_9": "DO7MiKHdGCIkrMh2hZqHnDM0ljgjjcJruHIEpEkftVBfZLg/hPThuZE/w6wcCCTPddUxyWoQcBBqB3YY9rk7U+EUjlyfronGzjDysirLKmQXaNUnnRSdXzRboM8MEAg2FqOo3DVkxnauQikR6VHCHSMJZsdn7lQmlknk3KhSriGExwTqBJrw7WqQGCcmi3iMtuTYlOI+I+wg57oXJ7SZMdqoZwd2C1aRPLTzoPXs3VfgVSNOovF9N2JsCSRfrAfGWOyDzbbP3pDw5thh4h6lDkunkI0rMI5RWSWkTAxeivDCI21iBV+IVCJckjhsR0aaSGruZTKSkaCtxrh",
"part_10": "EJzFfUZ0VuBjhcBArhZwVgjsw0lfHGm8r2hjcIPnC4oxwRqNGMBKvdspKnnejyDqrsJyjRhspbk0S31mVWIwq3nlcFAu+Yhmt0Sq8iRoToX7N1y0rBd7FpEPDYo1H0LbTI4WKdJQkowoTkUx2hVf3ZS+UBhn+YafvPqEihxywfRlxZ3oQlhFlRvbb/hJlwn1E4iPyRJyp/cKMSjq6UPcETboaIvumJ8+khFaxG9lsZO+v4EHFHrTnUkDpsR5kFE7FKjIxpoBRTiDDeFU7vMxbJ0GLWEeYGWcaPLFemNh2pLqi/3e3ftkW2fetnyybqvU//B9WhkyU/CsAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/1VRy47DIAz8lZHPPfAMpr+yVHvZanelVbJK4FBF/fcSIwXKwdgzHtuYnb7Xpcxfn3kt+YeutCf6nf9L3hJd8ZHIg6FSmrVCqNeESayvNiB2ItEFiTQmGHWcCjkDfTIWCrals2j1wXmYM6NmaxFoOLF+ELMwrXvrawY+wEpkhPfCe0EctJIgiPBobRt0No0yQ5Tpwts8VjDDUskauPbQ28EuJQ9bsq7LJuYh6K7ytu+J1RAMvguafYxdxa3y7UkX2vLj717/aC31er4AWoHmRrsBAAA="
}
}
|
codegen__primeintellect___2057
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nOn one quiet day all of sudden Mister B decided to draw angle a on his field. Aliens have already visited his field and left many different geometric figures on it. One of the figures is regular convex n-gon (regular convex polygon with n sides).\n\nThat's why Mister B decided to use this polygon. Now Mister B must find three distinct vertices v_1, v_2, v_3 such that the angle $\\angle v_{1} v_{2} v_{3}$ (where v_2 is the vertex of the angle, and v_1 and v_3 lie on its sides) is as close as possible to a. In other words, the value $|\\angle v_{1} v_{2} v_{3} - a|$ should be minimum possible.\n\nIf there are many optimal solutions, Mister B should be satisfied with any of them.\n\n\n-----Input-----\n\nFirst and only line contains two space-separated integers n and a (3 ≤ n ≤ 10^5, 1 ≤ a ≤ 180) — the number of vertices in the polygon and the needed angle, in degrees.\n\n\n-----Output-----\n\nPrint three space-separated integers: the vertices v_1, v_2, v_3, which form $\\angle v_{1} v_{2} v_{3}$. If there are multiple optimal solutions, print any of them. The vertices are numbered from 1 to n in clockwise order.\n\n\n-----Examples-----\nInput\n3 15\n\nOutput\n1 2 3\n\nInput\n4 67\n\nOutput\n2 1 3\n\nInput\n4 68\n\nOutput\n4 1 2\n\n\n\n-----Note-----\n\nIn first sample test vertices of regular triangle can create only angle of 60 degrees, that's why every possible angle is correct.\n\nVertices of square can create 45 or 90 degrees angles only. That's why in second sample test the angle of 45 degrees was chosen, since |45 - 67| < |90 - 67|. Other correct answers are: \"3 1 2\", \"3 2 4\", \"4 2 3\", \"4 3 1\", \"1 3 4\", \"1 4 2\", \"2 4 1\", \"4 1 3\", \"3 1 4\", \"3 4 2\", \"2 4 3\", \"2 3 1\", \"1 3 2\", \"1 2 4\", \"4 2 1\".\n\nIn third sample test, on the contrary, the angle of 90 degrees was chosen, since |90 - 68| < |45 - 68|. Other correct answers are: \"2 1 4\", \"3 2 1\", \"1 2 3\", \"4 3 2\", \"2 3 4\", \"1 4 3\", \"3 4 1\".\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACb8N2gC/+1a224bNxD9lcEiQOVWVrU3XYy2QAu0QB6aFGjQlyh1aC0lEV1xFZJrRYgN9LXv/YA+9Ev6KfmSnuGuZCmNlGa96ENhB15RXPJw5syZ4QTwmyATTljpgovgB6OW8rF2Ms/l1AXdYFbqqVOFvtRiKbEAU0pn8nVwMYjCblAYNVda5JcrUyxXjPBjkV9LcgtJsyLPi7XSc5oWGX",
"part_2": "9gzVUul1Ra/sZLMDM3Yrnk77nQ81LMMblxi0JfTPREP9VUaEmvSiUdZWJDIs+pmJEts0xq+l5ZJw19Q5mcqkxm5ArKjFgToHJJAptpoSzNlMyzHn2dK6ktLQQMFLmRItvQtbLKYeduGfZmlMuZo6XQG8rUbCaN1I7mslhKZ9QU6+alkZbRlevRU1gIm7zL9RuAGTkvc2Hgu76Wr0mfz7G8887s",
"part_3": "qsg3PL9WbkGaLJywZz32/NlCuE8srReb93pZWuYYx9QIPXpSrO9WLkvrYAw8cQsjJbywTiGQdC2NU1NYeH0ZdvGI+BGDz+kCS4XzXlTsPZpMqsH15Zvwlp+Rf8a3j6izXoAU3s+u8h4GhkM1D35j11OJg+rPmMB/RZqtXeXdwtI0L+CPYG+sVdAIuyh69BjhB5yhdWEy260OEnkJ426OWkfnJG",
"part_4": "4ekV0UJaJ5JQnqUstyuQP3/D72hsIHgV8f6WLl1FLkZIu8ZMXjvB2fd2BWOGUhlKyKmd/ooZYedqLP+eexXpXOj3jqO2UQDiah0PkGLEAwEIATCmp064LsSkzluZUrYQSLUSEB59JYSIJ3CerE9Pa3P/GVn2H/57RLoR+LambUP/vrj7e//u4Z0uXyClbDrF20la7SrZab8MLASilZT3W0sCiT",
"part_5": "c8jF7rvytHT7vqBAaFer6pjZFztF/FNqXUhaQWyzwixPSQzBP4hQmTu1wsr3RGnlTdqPBD3bP5/3V5zAxhnqFLiDvjQ7DOVNf1krqA8Kk2bf8W9fiyVOtLXrPqQTHVOY+srkaZnokCKKvaCq9wkNhvvvIxz2zvvR/vsE76Pq1PrcJ4WTO7qRATOvHuuNISftXhLD321BQWGqqJwKeIXa5mSltm",
"part_6": "oWKwf9bXi7PtXr6iKBtrlLvGo50nJaGIMrwDPy096B9lXJhO4dk6Qgj8Y7+ArD+uM5FLujwLeVEH524M1dxQE6sLYoay4MCxQG3UW10FNJN3h7Dn5v6Au6wXl+jPrrS0RtL6DsmlMHRl7QJIg9v0HXDyNKqmHio1YPsaQaIlLbBSEl223YtF2Q+GDWYOF2bXy4Nt4OD3Cj7fDABizo1WFGNTcH",
"part_7": "xHS5VDI5XCqMMJvuIVV7hL+Hqoqekaeqom30IaqifZeiO+MPqIruvNujKr5jYusSp6BizaNQ4tLm0unQBfjasynKbUmtkhcTZpfSnJxYW3B68D++2eyuq9g2EYxjpCvNlqRM9tCcGOmv6yn3Kj7vMslJIrJLnGM7Z9xWuHrfc0x11BnXIlKsTm9v56xnV7nC5wveD0oFfbkPwbN8yX8JXzHc7T",
"part_8": "YIjeygzGnQHVYnqRmJK9sRmOEtn3Kpps9Jn9FXuxdqb9pvYgMZXjG8J4hRUUR5+jOKzuCnNxE+QhlK43tNy0MD9tCAPTRgDw3YQwP20IA9NGAPDdh/34Dt6kJw8Tx4+fJl1Uwgb/+vzdhEw8vgRTdgzcDr4PmbSeA2KzkJOKie9MuaTh8k71j10hczAPv5oqpIwVYKsX9z26V/j+eLX7t4o6N4",
"part_9": "ycfjcUa2aF7MoWoTMOzzzwkj03TUHPWErdWSxtBJdBQ5iuM4bW5zFB9FHowaIaftaiCleNAuXpq0jJe2mUIpDfvt4o3G7eKNW7ZvfCIdG8kvbBswGrQNOGwZMGnb5UHUMuCJ4tgAcEDJoE0VDiiOW71oYmq1ykS4ClstqyHupPB4YRg3cjkMhyduwAaQIwqHx3kMG9zVo7Q/pjA+7vkgHTaJz3",
"part_10": "g47NPwuCbDKB1GDRJnHIYpJScai3jrzMfpfZSkYxodb/7iOBmGTegNfVdxgt/+eNy8EQqPZ+kwipLGuPHxOzwcJ3WtadS5HWciupfFwxPl4F4WD0+0C/FoHDaPXf/EJTUIw3v08/1TertXT5+cENy9aA6T48k3iu6jjPBEGUKZGvWb/D8x/GAT/oL/dMRellq9KmVw4Uwpb/8GOlD7QHsiAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/32QwQrCMAyGXyXkvEP/tSl0r2LEi6KCdLK1Bxl7920KdvVgLsn/JfkJmfg69DmeT2nI6cYdT8r3+MxpVO7ooCwEB9Wo3JCypVLDbEEwBUkAhJwpgODbsgECwq4p7tfNypscN9TntDukJZB8xzdlKyUeqAksbKhnKhX+uCE45z+nzNzwmF6Py/qdIa9pXgCOCsokNQEAAA=="
}
}
|
codegen__primeintellect___2058
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLet's call a list of positive integers $a_0, a_1, ..., a_{n-1}$ a power sequence if there is a positive integer $c$, so that for every $0 \\le i \\le n-1$ then $a_i = c^i$.\n\nGiven a list of $n$ positive integers $a_0, a_1, ..., a_{n-1}$, you are allowed to: Reorder the list (i.e. pick a permutation $p$ of $\\{0,1,...,n - 1\\}$ and change $a_i$ to $a_{p_i}$), then Do the following operation any number of times: pick an index $i$ and change $a_i$ to $a_i - 1$ or $a_i + 1$ (i.e. increment or decrement $a_i$ by $1$) with a cost of $1$. \n\nFind the minimum cost to transform $a_0, a_1, ..., a_{n-1}$ into a power sequence.\n\n\n-----Input-----\n\nThe first line contains an integer $n$ ($3 \\le n \\le 10^5$).\n\nThe second line contains $n$ integers $a_0, a_1, ..., a_{n-1}$ ($1 \\le a_i \\le 10^9$).\n\n\n-----Output-----\n\nPrint the minimum cost to transform $a_0, a_1, ..., a_{n-1}$ into a power sequence.\n\n\n-----Examples-----\nInput\n3\n1 3 2\n\nOutput\n1\n\nInput\n3\n1000000000 1000000000 1000000000\n\nOutput\n1999982505\n\n\n\n-----Note-----\n\nIn the first example, we first reorder $\\{1, 3, 2\\}$ into $\\{1, 2, 3\\}$, then increment $a_2$ to $4$ with cost $1$ to get a power sequence $\\{1, 2, 4\\}$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIACb8N2gC/+1abW/cxhH+K4vDAT05J2HfXwSon/oCA0VapP3mc2T6RMlM78gLyYsiGP7veZ7lne04vKpiE6AtpAtMcnc5MzvzzDOzRN7Pboq+6Mp+djn7W1tty5d1X2425bqfLWe3+3rdV019XRfbEgswVNU35Y+zS2/Ccta01V1VF5vrXdtsd5Tw92bzQyn6d6W4bTab5r6q78S6ueEFa95uyq3Yd3ziEozctcV2y+dNUd/tizsMPvTvmvpyVa/qv5T97zqxLjYbUYhN1fWiuRW7pqv6Ckoq2HlXtp2YF9dyKYprtRQXFxe8e1+fqw9zvLRr7stWdOX3+7Je45Vb6m",
"part_2": "1x0+XJn0sS8/V8KboGa4oe9rei/KFsH8RcitVqg2XDBbLnFFNTcSWuxPrban5Be/8MYfVnps7r+RPMXYqHZi8KWFfQc+WN6JtLIb4pm/YGxtFhWfCiuigvxK5a/5N7KNvtvi8YIzHfzbPW1eq9XKolhdfiXKjVir6ob8T6HZxcZrOxg4Y373fX1Yf52XLYkPhD80XsGigYpBf1g6j327cwBUp6AKW7PFhRiwwKMa9O6qloCMxrh4ev+DBspKrXbbkt656TN+XxYXj5Lbyv5mfivurfYbfr5uBYNb8Q9PifoDhbDAxV2/12WAGVfVvUHUK4PY0OBKT5BURyHFf1Of9e1rt9",
"part_3": "n+849A/6pWohflPVJRTVfVHV3bD7A34Q78XcHGAyXJT81s3PLo4SuhIv3nwhgu89jubFXA0i6cCj7HSQfTD5r/v+c5uRz3Dlb+WfP/5YbHebsjuoy+5a1WZVK2GE5rLBHAzw4bN5efwTo7c/ezXhL2on3aD5oPvrpi8/bvNlPaA2R6ccrFqK++NIe8ggJgZ2aZYwbnXc4GFQY5yDh0T4BEq4Rw8gtvMBhtmFc5UH78r+lyzzSaSlyI+xr+gAyACdvQUSerBiThemffeu2W9uwIgMGAYgrtnsc+JBDdY2dAZ/Xzf3nDuw7JFUKact+307uAKUW16ArNvyFnQHo0DN9RVkL7",
"part_4": "IRi7OzVV1ckU4W22KHwX55mLjodpuKC/KKrmn78mZRnFFzdbuof+/dGbm5z5Yuuv0Wk+c15ssN56+uFPMYV/35uuKVfH2u8qquzOOA35WSL17oHO1VT7qt4CLRkjsWaumIhEHGqq+b+ys13PbFlRzu+Mp3fKU4rOLkV1fF226B9effnR1H8fTiqhqeqBfJsMB12Q/7+mhk3Z3BZ9kB8BdSpKrxfHDxc3F7Lm7Pxe25uD0Xt/+W4nYU0s0uX83evHkzkOsg6LnY/RvFjs/w2+z1ctaXXQ8/zl69X836h125ml2K1SyH8foQoNkSI9lxwyQgdUgGyMmTzQDrPKvy6IeleKLA",
"part_5": "x7JnVNenNHqyUk2RTmmvhFIxBGGgz8hkfNBaRCuCi8r6iJ06bbwX2girrVDeJG2UFTpoH0Q0WljhvI7B2GCFMcIpn3wIBoJdTDJZCeFa2egwBEHBhdHdROwjuOT9RA+KpLSJwerIFB1RYJ1W8unCKcyJ/BuPgpomUwktUrRKB3iUxkcj4aZRHZgNMXo/IdAuqzp4R1qdRNJJq4SQPIqvaBJeQWCfrlZlmcQJICOSscJ63CVBXATYozGkgC7jhOYVMFLCOULP5UUCgdS89xYmY5WVAghLEGkjRrlSwXGApREYcDHLx3tQ4rHeU6ZPDkMW7ytowosBcMSqKIBewB9S8KTwSq",
"part_6": "AUOAViYCxwbDhASEtB4HOYZilYy61kMT7SBm6Td8IhkioO8yIHVYREPcIbXCTUUzQmnfA24AlxFTFCU4xMRCwdD0UwbiK1mABrJJPXjIo2Jk4XbKSJ3iX43sCZ2vtx/GLSWQB9qiL4WjodEiJhxrFqldPTpMPqJEFfRFcw0IEoaaQHNhXieDZqqbDMTNwOUiohAx1AA7qTznniRskEhI7q8ypKb2ScGKcEYgnOAWguJUdCBtMbwNjEqMY3aKRLVk1RSPZWoH0UERWix79QqiQgCM0iISexaTMOcqNdSH4K19CrIBgiXSP9QaUhaGaUhAVIM4s6hTxEAUie5Qo5bZmhydoU",
"part_7": "ThSLlAvfBGsYRNTVBDJDRsPlyHILZyBFEHOa5BP5B0yBKFhDTpIiqgCLrIJFGGTJjIC0yx5UQVo4U0RpKMcqcqgbB6dj7QW+JoIzucQ8EN75cSIyU7NY25SpVY/bbcI0sKFkorzAS0jgGEHJQJg5YbuekrIZ0SwjxlpUElQWYMwwKogqCMmjHFl7YlcKPZCLU+p2IjWpXPnAEcIF1EiJ4uaQvKg1AVi38gTbBienKYS5KIBIQ+tEQJbkUg1IeAIX8GV9VUpLlryofR48sW+PznRK30BqcKi3oGJs2gmmj0OBRNOCkixRtpEbQFJk84mGIY2nr/dmonIwl01oEjSQGnJvop",
"part_8": "CuESHXUoKvLfMZPAo6Y1p7JqaSaG4jS7xBOxHMKa8Ej5pi3RTTMtaTQT8Bn8APiAKuKIwITUgABrp2tlRsjJLL/YhDnDRcqEg14ykR0pTqn41B6CPJNdncc2HbbHmAWOQKDGVrh+6fvQ/PBbkT1FqiI/MB0Bg/AiTpQXFx4nGG5caS8NGOkH0d8pUtoYdvNIseO0o7kFDAEMBt0FRanoE0GjOLMb6KpWhpxi0MU9qwbJ3WwVo2o2iFwOFJ8VAFWEmJWsVKwRYVxQGhhd1aekXGVHQdK5pjdVTMCdAbAh3R4+qgWGdhe5AQ5NiRompppxJBoalB4h28Cd3jmIw48PmIc9PU",
"part_9": "Hh9NhLABDTQ8jvMblWF3qCCJbowZgRbNvzWASMzGIBLoeXjIBFsbzS5fO0CbkrA1tCuIG2DFFgm+MPQC4oL4+AjUo5vgYUBxNXWjlmpGHDZAD9BmkScs9JYmYQjZiqIJjcREQn5QECzhEgjALVsHnhdgRSTrQo3NXSfokBoDI4CEwirFAkkChsE8JviBo0GcPvL4wtMLJGGZA9pDIO4IflAVGBsrHA9jTAx2BLCdZIaoWySLs/l8EAJdOAhmq6AIas3jiyLpIY0QV4O6AGyr8f4Fpk46MKjDydTyHIT+Hp6y2VTNNpVnHcndSEIYbIi2hUcebxBMo0FvcIQDBYEcJFPMoz",
"part_10": "yj4dJ26MZsdGQJmQJ6G/rIohHDlnC2ldSHjWtqBZaspe6AM1PMdcYiXQPt8NEaZ2kN6mCQKdv0L8+xKCVoZvUEhOdG9X/YHY+e8LXGf0CdngqVR75bPd8+/XY0Ujodp6dktRw+Aj3791cPC6ssmgYVJrdR/wdewHkV5xx+ojT/Acfycx0KKVpKfkp7yvNj5h0SR9qpX2r5JfDEp6008UT5qaioE6dVP1Xyx5/8tSw+egFdy4mP4HqqULZ+qKjjYuV0U9EmjXdGfuLRWHzxc/pE3JwKUyn6mWl/S66OR66e8l1CjWEgn+bGYaDd4aPPa/7Po931vq6+35ezy77dlx9+AscABql9KgAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/1VSy27CQAz8FWvPPfj94Fca1EurtlIFFSSHCvHvNSAFuCSbsceenclpfB72y+79bT4s89fYjNM0vne/y3ycxgZepyHTtJMIKDSOQmDBRqbxArcagQCvSPXJCYoNHA0suowEbAjiCREOirq204XJDFoYwMDZTyKgokzuuYjlqNZoWZ+BlcIjHQhNKCWARAtChJ5EJWoVk2lv7glmDtbfWCS2NupVvXULENsTX+KyApRVVpzxqjVUu79Jmi2b3Ft1e4IRDETZNUFnBNJuQifWyjaBWianCbcl0b6wuCikeLtK7QBxQGAPMqgeYcxGpRDFlw3YnGb27ts9txdB+2V+yEnJ7jE8uBF2z6vNy0i1+6WcEl0wc0Ue0pU7mh7smXGLbnseL+M4//189A9zWPp1/gfUK0DASAIAAA=="
}
}
|
codegen__primeintellect___2066
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nMakoto has a big blackboard with a positive integer $n$ written on it. He will perform the following action exactly $k$ times:\n\nSuppose the number currently written on the blackboard is $v$. He will randomly pick one of the divisors of $v$ (possibly $1$ and $v$) and replace $v$ with this divisor. As Makoto uses his famous random number generator (RNG) and as he always uses $58$ as his generator seed, each divisor is guaranteed to be chosen with equal probability.\n\nHe now wonders what is the expected value of the number written on the blackboard after $k$ steps.\n\nIt can be shown that this value can be represented as $\\frac{P}{Q}$ where $P$ and $Q$ are coprime integers and $Q \\not\\equiv 0 \\pmod{10^9+7}$. Print the value of $P \\cdot Q^{-1}$ modulo $10^9+7$.\n\n\n-----Input-----\n\nThe only line of the input contains two integers $n$ and $k$ ($1 \\leq n \\leq 10^{15}$, $1 \\leq k \\leq 10^4$).\n\n\n-----Output-----\n\nPrint a single integer — the expected value of the number on the blackboard after $k$ steps as $P \\cdot Q^{-1} \\pmod{10^9+7}$ for $P$, $Q$ defined above.\n\n\n-----Examples-----\nInput\n6 1\n\nOutput\n3\n\nInput\n6 2\n\nOutput\n875000008\n\nInput\n60 5\n\nOutput\n237178099\n\n\n\n-----Note-----\n\nIn the first example, after one step, the number written on the blackboard is $1$, $2$, $3$ or $6$ — each occurring with equal probability. Hence, the answer is $\\frac{1+2+3+6}{4}=3$.\n\nIn the second example, the answer is equal to $1 \\cdot \\frac{9}{16}+2 \\cdot \\frac{3}{16}+3 \\cdot \\frac{3}{16}+6 \\cdot \\frac{1}{16}=\\frac{15}{8}$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.4375
|
{
"part_1": "H4sIACb8N2gC/+1c23LbRhL9lVmG2QIlSsbgDpXlqn1Y7/ohWsXJQ1KiIoPkUIIFAjAAUmKpWLUfsV+4X7KnB6BwEUBbcN6WSFkEZnq6e7pPX4CpytNg7mVeKrLB2eAy8ZfiQ5iJIBCzbDAeLFbhLPOj8Cb0lgIEGPLDuXgcnFmGMx5EiX/rh15wEyfRMiYOv0TBWrDsTrBFFATRgx/eslk0px/QTAOxZKuUnogEI7eJt1zSc+CFtyvvFoOb7C4KzybhJPzJu4+yiN15KfPY1L9l08Cb3U8jL5mzBz+7w2gcpX7mQ6QPrW9FwobhkD0kfpaJkEUh87NT9k8B6iBgsUgWUbJsaOfJDTLxiJtgw4b3Q5bBCqnU4JdVDAn5hsLVcgoBs1WSiJBIK2JovqKcn7LhelhKTrxwHi2xJPZ",
"part_2": "n96AXLFrINXN/7adRktIzVjAF0lJ/SnrwIcMqGh3Jm0TEECAkmdx8dgcxBYNT9reUFeZapSJlNLfwltEqLYTv1L8VoUi8LEqY8vHiHzlr2Be6eMGDt0nz5UPTGcphsClXpELMx0x4s7udXNop3AYRGeYYpE8Fm93BZGGupPiy8gLpem/qB362OSWzwi5h9MAeImAJm3+48zLiRBYRjzGgB15rL1g926lQvtvi3iIj58N5aSbiVEr5kLGZF5JG6V30QEsgRlot511MwrCJgMIkFFseTiaLxJs9XW6fft7C1HcigdEvC2/8jF88z6KYQmWHurSYZJNJGGWTCXbtr5mKx3gZzZ+4+od7bG8BCARYmEndn7c3vATZbB5l7Oc/nk44RGLJKoiAALlsKPcyCU/o+hDGq0ze0dCv4BOFAE",
"part_3": "vgl5DyiQQKhpnnh7DpQ1RqScEhNYWdlCGH4EB8YWHxC3lP3NwOx+x56r6cMoajqib/WmVVVfKNeYxiOyij8b///s/XvfpVb0q3NMzUtC0iOiE3jaWP5mIBk4DRNFqLqtp/f/SWcSDSQnFpz0loMU4U+Z4moS7Rs5vSqlOObap0OVUSlZlVGk23ue2orpvLLSRfRJl4NteHfMsLP0kzSj2k07jYNqUH2vb425BPuYbTtjX6ow8Z2cEaStPLUI1mlLIo1XVEJNJUOBO5OC9MH4QM610c8GPtWD+2tk/G9lzPwVhonwqgbF6qX1+fy8miHEzScwVHd/vEre2x1hjW82G9fdhqDHM5fL57MrdPzjbX7tfnIJC5l8I/QwGSwN9EK0oGq2AOCxBiMYC8FgUrWQSgLWgjciL9d4EclT4Xt",
"part_4": "F39ypNxtkpyK6C6iVPUxUQskClgSFRBwI/JBPEeRSVKlIsRqgnD5bNzwhPdggUenrb5U4j7i/x2mbwPbvGoFksWmHzL1IJDsfTqhF+DhpeDxOEkrKw5P3+xSK2sebjzKVCPjjT29pyFFcr7UnhJGLIfSfs6z1zumzfnzK8P3rPjmnI7BXxS4L4ch6KSqdZgSnbSyyERpOIFxfGzKaucuMqlh0L27pwpGranjhpLyTtID/PcOR/votI/1euHHCLKZPD+/fvJYMwuRi+JiNftbK54YzZtY1KoNm2zXMM4BCivnaJl/y2LSY8psgg8Ne1QdaE8jtmsS9GCj6I8sqMjpo3YMWjB7eIleSqW5KOri+uXc5SJZwhB6jxuhcLHjPMukY/nWvvEpmtifs7bJ3KcziUI9hjrEWoXZugm2kii",
"part_5": "hbIhsv2kEJgjYJoqjyebUTtOChzM2V8Q53u0Ixinsg3/6aMyH+2hrDhs3k0lghrHizdvvpUpke7juxeRO4icenEswjl2Mgk7QRT4aabgBUSh59GoMxJZTtDCB0zwEtE1TXj0CY9X2lgfm2P7+mwfgn5NVvu2Rlmb0kJ6dKTwN/7oWD01R3sdmh0dydSUfs1g4JztJ6k5M/2aJyveTL/LldNEePdtHmzk6W82JPaRdhWUFu39Di6NGlC96qN7FaoZNdyTHK/CRs2t18HOqcJ8rzD8rgfoYPiZ0lOtgoUdEGzU8pc2obr++WtuyGv8526CtnrfNN7nRu2vmD/cl7Qb1qt0OO9qa5oOAkluxne1vVEZnPuz7Aavr5nyW9Pdv5/vWrJq+nik9EELxFz57fRebFJl1AaU368eSYPf8PO",
"part_6": "i+SEg/15TF5SlJngePXeGRIsfCjnSt4BnpY9csAtq2xr7p2XvPcCqxihdLZV6N3oqX8NoD9LwDTHVKCiboJ8+Ug+0w9nOadrZTgoFV32O06tIyP6KG4mvhoY5MZVPJWQnjI/Yu3f15nRerq34D2SFzjvveEVyZ/qYmWNmU8OBf3jidO9W8700evlIhT6OHqh/y/LdNRvfjEq2VDB/g6DHyq2caSCBmCobdsQ21D010mbG3r6t6F8YbFOXkrXtvO6PEO9C0quTwagVaxUglKvqKyquK8MrxwKll1bQNV8qiMEJL19vLqoebGTcMtMqfjN8XqZ6v0gquUK7T2WlPvGCnFcDdvXV6opflxCJCSLxoq76TZyINShlpNXj8qoSv8/9Q97Pxour+Pr4RUdLVImkKhi3pAdM7TqiBPBQYu",
"part_7": "qzn1ueXbjmaSbPB/nel4+E0SV6+zETFXeIZt6sv0ZIih+Z1gRStoypY6oyffNGG71gA4okmhMJVsg/BU2jcr2eXwtnrKvut5iuvlcVnsFb7NFSmvumdMpyVHG2Xx0/qzvyc8fcbv5+z3z5FkvFDOD06Pb+Gq6c4geD++h/PGeXXQl++bgudrtu7JY2+20726d58e5dU3mNn1aq/YqWzP9sf/jARbviee/gh2vlMwKvTvFS03yUtF3PatoSBX0DQeQtTzi93soc8Vz+wN9rkBe14fIE1eVylNP+wOR3PFZ+/KSmQz06csHRpoFwLBsv+WKz9GIFuXecf5NSRqdpHPj4paj/QXaNFt3c51+GJuGLrBZKwjyBxwupgxemeZ/zMrUtaTVlKOhSZOX1ei3Dc11EXh6l0pPQE/+kmZ5LX",
"part_8": "1a2jPuclxGaFPAmyByxIpUh3VxWaUoslb4i7Y+eX3XoKafKt4jn0WA8kFYanA2yxPNDPBdf3w5HTIcjpsMR0+GI6XDEdDhi+r87YtoxSQdnV4NPnz7ldSxvXg7HTYfjpsNx0+G46XDcdDhuOhw3HY6bDsdNh+Omw3HT4bjpcNx0OG46HDcdjpsOx02H46bDcVP7cVNu50+fPg2ux4NMpFk6OBtcPU0G2SZG9Tpjk4H8vndTfLlDYzIZSPvmk/RtFxzkcJR/oZXjuhzdjtlrWGmtrMqPwq9nSd+O23iWH5FfzVNjRitL09KknubrWXKN6a08bds0LM211dfzNM2OrduOq5Kq9ut5urrJ3Famluk4Gv71UJQjoHG1suV9bKl2QDJHkapZPZiq9WuPyho3TW5wsweyLJurpsNdQwU6",
"part_9": "TZs5lt0OC811LN2BzXu4EHpzhwBg6mDDDEftCGDDNHRN1/p4VHNcW7d0i6saNzRmmlq7DNflpmYZfbZRu3TmcK3dVI7lqNgp74F2zVId01F1ruq6BZ+7lmu1g9/VNI07mtEjShHdhuuauqFxHWnAte32AHOxDdu2emxDN21X103VsKCiozFuGe0iOITrqmH3iA8TZnYM29G56+IPQ3bpcIejW8i7Tp8k6diObWsckDEMBy43XLsrEUOCbfTYh2NZ0hFAL7f2hrkDj2tOHxk2EqVtqC5wpToEK9d1O6KccKtqPcKDoILIg61sw8hlOO3QRbrhptWnaFmIagOOtk2nENHuDguQNl1L7dERuJaOfXB3J6Aj/CxkTM4NvU+RdGzKUYZk314vEftoQBy9R3RzG7UbYCTm7U2Da+iICLe",
"part_10": "Hi214jfi2x5nBNZtrZh98UgEF3/ZejFu2ZVoWd3vV+T+rxluIHtNFEKlcNVy0oLrejj0NAFJ1Ve/T68CCQLdLFdnSYRLHtjrCFBXfVt0e+LA4Mrquu0hYumvYzMbV7k4H0l2V95BB3Z5qGBzp0pGQ4bwj/TumiYa4V6+pGRp6P9QOMHE15uBqz5omQgIRbX5nxXdc5nSlNN1FpdCRXb+3q3C7uwoDuVtH1e/hDhgAmEQx11TLdJmh6e0iTF1XOSq38x3dqr2/E1aN7+LdniGKlzXV+k7z22q3i10d+ZRbpt2v/yXt8h++r3E0dRO9ab/mFPVI1zQV7bO9z8cGMguKVz+oqtTY2rARZO0Ja/T6tmoaal9bAajytUnvToEm5xo6p6Ln217T/yolvVmF/peVGJxlyUps/wdPfISqa0UAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/01Qy07DMBD8FcvnHvb96K9gxAUESChFaXJAVf8dp5Xi+LLyzuzMzt7q53xZp/e3ZV6Xr3qut1a/p991ubZ6Li+tYni4E6KSSHAJSW9tavVUWvUgdYFkBAiAkv3toGrR/UMGoQGdyGwb09IG091QNg8XecrEDiZrGaLolE7x4MjeNUfQwBRg7yIlzPkBvm7oZV0OgdT6eLgMe0omdKA45EowUhhJLYkIgw6e3Q/VYGQ0jX6PCBi7CwfbIQxlGEcnPre711O9Ln8/H/3w89rL/R93zuNkkAEAAA=="
}
}
|
codegen__primeintellect___2071
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVasya had three strings $a$, $b$ and $s$, which consist of lowercase English letters. The lengths of strings $a$ and $b$ are equal to $n$, the length of the string $s$ is equal to $m$. \n\nVasya decided to choose a substring of the string $a$, then choose a substring of the string $b$ and concatenate them. Formally, he chooses a segment $[l_1, r_1]$ ($1 \\leq l_1 \\leq r_1 \\leq n$) and a segment $[l_2, r_2]$ ($1 \\leq l_2 \\leq r_2 \\leq n$), and after concatenation he obtains a string $a[l_1, r_1] + b[l_2, r_2] = a_{l_1} a_{l_1 + 1} \\ldots a_{r_1} b_{l_2} b_{l_2 + 1} \\ldots b_{r_2}$.\n\nNow, Vasya is interested in counting number of ways to choose those segments adhering to the following conditions:\n\n segments $[l_1, r_1]$ and $[l_2, r_2]$ have non-empty intersection, i.e. there exists at least one integer $x$, such that $l_1 \\leq x \\leq r_1$ and $l_2 \\leq x \\leq r_2$; the string $a[l_1, r_1] + b[l_2, r_2]$ is equal to the string $s$. \n\n\n-----Input-----\n\nThe first line contains integers $n$ and $m$ ($1 \\leq n \\leq 500\\,000, 2 \\leq m \\leq 2 \\cdot n$) — the length of strings $a$ and $b$ and the length of the string $s$.\n\nThe next three lines contain strings $a$, $b$ and $s$, respectively. The length of the strings $a$ and $b$ is $n$, while the length of the string $s$ is $m$.\n\nAll strings consist of lowercase English letters.\n\n\n-----Output-----\n\nPrint one integer — the number of ways to choose a pair of segments, which satisfy Vasya's conditions.\n\n\n-----Examples-----\nInput\n6 5\naabbaa\nbaaaab\naaaaa\n\nOutput\n4\n\nInput\n5 4\nazaza\nzazaz\nazaz\n\nOutput\n11\n\nInput\n9 12\nabcabcabc\nxyzxyzxyz\nabcabcayzxyz\n\nOutput\n2\n\n\n\n-----Note-----\n\nLet's list all the pairs of segments that Vasya could choose in the first example:\n\n $[2, 2]$ and $[2, 5]$; $[1, 2]$ and $[2, 4]$; $[5, 5]$ and $[2, 5]$; $[5, 6]$ and $[3, 5]$;\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIACb8N2gC/+0c7Y7jtvFVCNfoeRvfwvZ+JLftBSiKBggQpEVS9MetFxtKor5FSiJlfQQB+hB9gD5LH6VP0hnqw5It74fPXRSBZYnkDIczw+GQHHIP9/PEoopKpiZ3k7+mXsS+5YqFITPVZD6xM24qT/BHTiMGBIDyuMWKyd3t7WI+EanneJyGj3Eqohg5/CjCDSPKZcQWYShyjzvEFBZmQGOELCKZRAhJAOOkNIoQDil3MuoAslSu4HdrvuZ/p7KkxKUWUKeMEalSIJVkSqdzMjWmhHKLTCUAueuZLgji0pOKCJuAaJaa0C3yZ+6EnnRJyJRiqbwkfwPJIeOOciVS9pjW/JBvyghLMhoSJciUgwDVNcI2CNXtUDzxZI86ml6SrfIWMz2LWVhjukKAPpTIzGga77CitSD+AtKm89BjkyrG4cPq6JJ8I9KIhmE5J0Bd85",
"part_2": "HIiDkR44pM78PH5Zykj8uHKZlNl2S9DllCANmU0q7EpxdaxrDxChuvdhqvusarbeN53doGq/f0BGdCzYShqMe1Zm3nt5qRL4ixFUU+Evr4M1T+0uRQDWWQYwklEZdinYF1qzYf0hhIs/pleokD873I56QeHRg4D7w9ZVLBGHlgeJFxherwLDJAb7B6TkvZGz5wTkgbi4B0y2Vaf6DY9XpuedhdqX2ZbNsMxkC7XN+uLoUJxAV/z2BGlbV+kulZOCfeJbtEOeifBbg6KKDALyk6PWea2AG1pwV4ksxgSigXCKbb4S22w9zI3o7etm41/T0ZeuahwRk6/3Be1PNgzd/j8y2PM6VLiMI5aHspqB16oDfYqnaHpgMSJ12tXtT3NN7kN4vFej1fLBZz0iofNTnCJgw6euC///Wff/xzZ+qOTnduPTnBL1uVOStUsxah3rJV/ImV",
"part_3": "CXwrxtHbsLDsrz1DKUN9PFkvOrCqhezZpQdXHFTwj2HYcXvRStgbnb9kqj88sA/wgUdtLXlwYlASU09XtI7eLssSZr20y3rOvZO9mdFX4c8FjeKQyUYJ7S9rfktu1pxSw6B0zSGBIsIUwTWv1V7zawSaFjcEIFrBb80xrWqoT75c9ug/kOUKSAyzfte8KKv67bANtGWwqvVuNP9eKNaZ7jumoIshGh+W4XqbA7vIvmHqWVkvQbDihFZrQ/Ak1c0MVhukWT2m9zDjVt2CAcDNA87S6f1yB3/d4G80yT494G87/FWNbx3cQ5uQ3APNDfQz2Lg1YSkyIl2taqx9AxApkSLM9IIOXgC0Ak3TrLBY1wQC7b6PfFKmsrTuJEQF7BLiiZTZsJxxE8MLL4pFqogswXdC4UBs4ax5U7g0qPTMPwlue84sZDCfPrY1337/zV8utoSWJy",
"part_4": "lInO1UryFwsYmReaE1+3FO+MUd2pWQT7DB3C9g5U6JhyOQQiTCZlfkd7DcfEGuLh5qst+07Dxui9mPFzWWQ2OYnB38HcCLuvjDtvjpfoHbGK+hHUnLni74ePbMI1+TH/q4ljXy9IZovUjMfiB/IPVQ/Xj/A8j6iDl5T7572GVTq/bFR7Ic4j/dew9aAjQa1gBqQM1CyXaYBqjXfkvoyqf74AF0Q7Yebspj6jSikXRYOSKptYS3jz7GEoes8bRFdq3SuPWn1smyGGJqtpzBjl3MyYaGrehaxYL84aN2roE1DE8t74sHVAZabPEFYgryW/K+aPk7TNXM2/YU9s7O21ohX5NFnz/SAKdGTJ//+y3/Xm+Aftif1av7s3p5f1af0Z/Va/sDS5LJpESR0ZzYFD6jZZ2u0Lu4mi0vRnTBuRsuh5N3t+O1vsAHrAJnG5QSYtAagSOt",
"part_5": "Lna9sOcrSGAb9+kKgyzg3GowJF2NkTbl91DxxV47UGXo4Y3pWjeyIbzTgd3yAla9DmpHpVe9ZbGvdkMzJ+/36VZjdAgvO1zTRm8vM1CwW7EjCLBmrdU0GzArjWdAN8et4lJvU5cpoxYGZbOLSxmHnppdtOMH9GNkda3xZK18shY50/u7GW4A9AJ7024WyNVoaoxBjebY1MhBjY3s6u0JRodQ3BbqmsDY1tzf3b1vgnBd2lLZxnYjC7Yeiu656mQMt55orv1lsP3AaHutH+Hyh/DDYHcaUnwNo7Hr07s89Ej3RBj3WizuCVgdGHsiBhSjInZ49EQMNmpQZXk3q+do62NDAmOfYHR9QH/ExXM0XIATyWJxjWbG9egZktqvHx+loimeNh9jgU7fdlGlZa+znfsBUxGD17zTQdqlKtS7OXmXvrvYo4VArCMWOmRtqfOWmhUmi1",
"part_6": "VPTEylrKF6vq35vn4QrempBZGaSoEK4Ca4O9/8nG9+zjc/55uf883P+ebnfPNzvvl50c1Py0RO7u4nP/30U73/r/n5Fuh8C3S+BTrfAp1vgc63QOdboPMt0PkW6P/qFmjNIVabPMwnCg7PELtN7n9eT1QZs/XkjqwnWsvHJiiczAGjNa0rMajvovourG/jerCJblBrW7e41thf5uTlQvAc0B4E2pNAcxQYkwBngleL0EeH/tmhf3jYOT2MyVy9XuSSYCPVfmq8L6/nu1qQ6wXqP/K8Dn2A9FRarr6EZtHI8zr0tnZfsZvbxXGqQat05HkKPe4Xx8lfLto5pJ+oLaD5bbr/DKgPWOK4QbrCZrGEX5s0OaCxINukyXvUXashyah6V0fMH5izV9oe8GuTOkdzYKlN6rylbbGnUgT9BZtVHvzapMkBjQUPk7jJIelRN3lLdcL5",
"part_7": "tcT5FcRCeEWXwpujDIBUr0YXcOgaVNdiVJ0j5xTuFNVG7L2ozgj+AHVbN2Kl1e3xq6Wz2f+9Dn2A9FSjeYXmM8vNJpHDFCfiCB7Qe6SjjU81vmh8K3H0W9aFBFONVm2Nfu0WjdC4ja6OH8oyTnJOPaHCsEqloMmGZuhM/obRDbMKL6mqTDK5YfwA9QHS027Plh+aMaNelPpZ4HqVoChDGIGZVIGZborCNtJNJUyhqdM96gOkJ5uvuAkWsoBXSp03ZY0eYHRJBxG7tFg+VRiISxpOgjynOaU5fnUKGa74GkLYhc/U5X3q8WG8Pn6XtkxlKktZZp0CqCyM53RxWIkTuMZAesKR+gpaZWnKrQzeFF6AuMUtjeYWVrQ5EmC0si2ebGhwLoRRZId2GIWQRXZdxrCtBiClGoUUmrrDjw/LEeZYLsBzF3pg3uD5dYl5o66cZBnFcV",
"part_8": "7qcX6L51cnZmQMvry9vjlyIPRB9g2etxRzYEU6eknqjo5xmvqQuennPSxN8z4cjp5QNTY4yCR5pVDz+YPw2O56fcwGi2a7wjAwy7IwK52sfkSW5ZBFDQhVWbbBQmVrWGYHHtgEeV1yWxRrGEWZFsMG9NU4j/4jtmwymvmwy2rYOaRCXvfm6Wd8Tz7S7z6g4aMAfm0yChxJ0UPiURNLbTIKHEnRQzZiXqbVMeJOGogsr/BQZGbctfHdKbwQ/yIyEFOXuro+0UvwLyLrxJxE8c9S6GTXsLg6X+vLBuo6EX67pZfXPEfZiWnTceh4mk7MIS1GzfbhqyNuzD9A/KUv/7mbJl1yAHqGiD7dFqRs8clecRdBn6hLDjNq+nJED17Gv4841emvDoOhHbNMuzycOk/WQpo/xwFSDE+fp/qM1NIp3tN2yAM3fYvPOTEUxv/+96sTMxKT",
"part_9": "3Ky+vD12Y8TATtrW//zFo/MbyEGffQs5z72jA3W7+HL1OTcpIjHK3HOMMIscVm5CJoUZWynbFE7pO76fV35o5X7ChKXc2N+UDlUskaHrWWbl5iGltthYvrSiyi5tLxHCl6WsEt9Iq5AnhmBKXyoGRVgYkVVtlBOHVWyymOogPMr9KLVVCrWc5gZjvkedMi+k9FTgFZZv+Xau3NBSYhPYlenRzKFuwgpQioPSETA0YpoXhnyj3rxRV052k1KPsyFKP/UFE1WeOAUrXDPzRBmZEQ82pjIiHsnSFGHlCmGrHP/bkETlhlJZnttK0aKMEul7nutIy6cSYNMRFfc9kVa2l1MjcqWj/3CfFpVIqIiMwLbCRJi+k9mVq4TDgsBOEhVwyy8t5mVh6G+yfKM2YOA05Buwn2GHZemGScqV6yWRI2SQupUdqNwsrMqzjFIkir9Rb57uSn",
"part_10": "WqrpwsVNDLrpmYSWLiV6c13Ob98lP1T9PXYo5t/bw2DYyB4XNsDvwbkSNXxK8+4MblxhS/El7p4heXHQ4/OYbTxDvglm4XhxOlQYzx0UQvZtYx2NML/+h7qBNjFa/p8Sk9F82e8cz3dZr5vCt0YIfcx3TE+5gdbhjjHs9jVKl4hCGI6ZqPn2SP+APoTRvgMt8yNnFgw3KXRV7muyoOueJWaQdB5iebwPFiIzVKM8ormpssxKEqRWQ6FTONKthQVsGCZAQi4DbdZGlp+VkcSZtL5W4sR4igsK3iKElHiTnJRteZxwwZV5FkluumFrXLtAocXmVOueGmcP0gDbiMQl9yNytNH3Z93LVMN6iiOHWDIEw9v5C4BZtOIYQhI9vKSmkaBWwpnBqpZQWpp+yjJB0Www+LOc0s09f4fvv5T5n9Af/fMPmYcS/J2OROpRn75b/DDzeseEwAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/6VT7W6DIBR9FcPv/hBcTdpXGU2D0A+TTY3iVtv03XcQuGq6bksG5NxzD8cL3uiNndq6r8zetr09sy27SVZWTW87ybbJq2QiTUQmZXUtMSOECNmR0kETImDmDjG6sCPZKhmr8hSZ0VZbY432iNQayJ4uNyFrrwCp0CbhAokqtF/gl+Hq16THlA4Xa3fJj/phQa6/0Z+44x7VzTiypsOMECJkR7oIIc7c9NTSQtXzxN1ZqaJQCgQIPipqFJaNVTTeI7lAPqrHsXBTIZ6GSgejj8NzPP24C/z8rQIQx/zB9Q80I7oGkDi+6c69at3b2QfPqQXp1NWpLSInnhF7IbbO+czrK+zubMU6O7wd8H+1PcL9Cxi1kf93AwAA"
}
}
|
codegen__primeintellect___2078
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nServal soon said goodbye to Japari kindergarten, and began his life in Japari Primary School.\n\nIn his favorite math class, the teacher taught him the following interesting definitions.\n\nA parenthesis sequence is a string, containing only characters \"(\" and \")\".\n\nA correct parenthesis sequence is a parenthesis sequence that can be transformed into a correct arithmetic expression by inserting characters \"1\" and \"+\" between the original characters of the sequence. For example, parenthesis sequences \"()()\", \"(())\" are correct (the resulting expressions are: \"(1+1)+(1+1)\", \"((1+1)+1)\"), while \")(\" and \")\" are not. Note that the empty string is a correct parenthesis sequence by definition.\n\nWe define that $|s|$ as the length of string $s$. A strict prefix $s[1\\dots l]$ $(1\\leq l< |s|)$ of a string $s = s_1s_2\\dots s_{|s|}$ is string $s_1s_2\\dots s_l$. Note that the empty string and the whole string are not strict prefixes of any string by the definition.\n\nHaving learned these definitions, he comes up with a new problem. He writes down a string $s$ containing only characters \"(\", \")\" and \"?\". And what he is going to do, is to replace each of the \"?\" in $s$ independently by one of \"(\" and \")\" to make all strict prefixes of the new sequence not a correct parenthesis sequence, while the new sequence should be a correct parenthesis sequence.\n\nAfter all, he is just a primary school student so this problem is too hard for him to solve. As his best friend, can you help him to replace the question marks? If there are many solutions, any of them is acceptable.\n\n\n-----Input-----\n\nThe first line contains a single integer $|s|$ ($1\\leq |s|\\leq 3 \\cdot 10^5$), the length of the string.\n\nThe second line contains a string $s$, containing only \"(\", \")\" and \"?\".\n\n\n-----Output-----\n\nA single line contains a string representing the answer.\n\nIf there are many solutions, any of them is acceptable.\n\nIf there is no answer, print a single line containing \":(\" (without the quotes).\n\n\n-----Examples-----\nInput\n6\n(?????\n\nOutput\n(()())\nInput\n10\n(???(???(?\n\nOutput\n:(\n\n\n\n-----Note-----\n\nIt can be proved that there is no solution for the second sample, so print \":(\".\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "H4sIACb8N2gC/+1a32/byBH+VxaCAM/Cis7OpW5hxCXy0MO5D3cFUqAPYeqspZXEM7Urc0krRi7/e2dml+SSkpxUZdE+iI5lcjk7P775ZnZXyJfRXJXK6XJ0Pfpbka31rSl1nutZOZqMFpWZlZk1d0atNQrgUGbm+vPo+uqPbyYjW2TLzKj8blPY9YY0vLf5kxblSouFzXO7zcxSzOyc/qDMfa7XonL0RCI4sizUek3PuTLLSi1x8LlcWXOdmtS818WTyoWz1ginsrlYWju/f0b9VvxVbVSRiQdyp1iqot",
"part_2": "RmIpSZi3u9VEasMifybKFFZmpRCk4Vz+L9bGVtPiUDt15woZ4wklKLtSpXYpYr5ybsYKnVbKULUapquSpRdt0LLUOsCu1Kup/rRWYyQsux8ncCzWqDExzacPqx0maGDjmhhCsLnDJBaEypcBZOtyZ/FrOVKtQMdTqRjiAdcUTpSKajoHJmiwJT84LqvW/KlSrFDHG5x/tCGbewxVrPyX+Lc2qtCFO5Wusymwn9eYOBOYxG3D+jnNMFR9nx8LLx8Bzv7nW51dowRDUzYnm74Fe1U1Pxky3Qjlpvcj3Z6zej",
"part_3": "IAHDn9AdSEkGC904DKQQ/axydq512pHYNU26PL+U5/xZa+ERepQTsV1luSaEO2CzDWPLqfjFlgE9sqSR5M8heR7tF/OBwLWk4AT+Q/uRoHP8u/t9LJRj5bk2S6QfohQMjN14Kt7xE1kocOJnHPxwmaZzWyK/P47FGPAp148ifytQmRzTfNVqEDfC3V26u9dhjrv7gmJfx+R9I9QVyMcvhk0g0eB2ZRG5etDj1fVVc8qVaaYiHjSzh8nP6okbgFaF0azbxTJYiitK+BrVVRuxRYZigEZv64YyFT+jN1S/Ts",
"part_4": "zt1sThj79ZYZM645z7BAtNvMPbLcW+4pJaWu5XFpVP6BnvCr3JFSaY2kNNa55M7YasUlfaaPwwJdrEuC2mHAV7RU261upBC5Xn+7AjvRRpwyjC+GXS1ZTemepWtsqpPX5DgW80C0SIvJoEEH6rHFnehB7quIeiyxWFiB0a7aFU3eIZJSsQ6jk2y8I3TotiuDggvo677j32TbEoMoRpwr3p2VZoLd/U4jXKFAr65ogNCFfx4BJxy+Ag64h5a+aYzavAF3r06LErajbTm1KhZxxbal7RdWs2Vcl3NPR3autZ",
"part_5": "gR7lVJ2BNdyqMfu55k6/REx8ycI4lB0++ZsfRZrOsILE5cU//zCWk15Jc+NjVk5rc06jlfmuvYa7u8vDAcZGUf1alXFY72r3D1hBiLFhYgrrJRmXhq0u/OJ4PMTNVHxlbFA6IfaYsoU09onsp6Nrqg6gErdVGfKOncjJOMS/+BXDhSA5j6m5Sg0kdJGcRwFHaPGQjczlhRfyv7EgGjaRCWp/DYa3zcqJ9H7iDuX7YhNfjQtzvWxT68LShuXhQ/cRNgzIyC3saFj890QP3CZxVqkQQrn6eThQtFaoksq5Jb",
"part_6": "/p5xe79ZVV76m4BElPocuq8Osx7sH0FHdv2FzQbyxz3KsZXBwe8RctALvCWD3gSJ65eGiGXQxHH6YzW6HsGZz5wSIelGHwMR5MaJBQyagz4sZjqcFI3NwJvLKFePiQfRQ3NwIFw2B4wSbfons//CBeczBs71ywhT/fhDfRJLq8OoEOdsdZ2/mNuNwZfhSvOsM6d/qAUrmrtPg+pSkuBBjSSs8eoA4exVDphX9Yt7cNWA+RG+ueHQQoY9jg7HrHek92T0Qk9KqvkB1CNxjsNWJvcBPHo2/FRU9BINZPCnX7",
"part_7": "N2GkVkK8ZOrC2dn0N1xA4UGyEY8BOyXOrpE1yEm3yTM6O+DGNDP4HCh8Ok2cThOn08TpNHE6TZxOE6fTxOk0cTpN/N+dJpoUjq4/jD59+uR3W6k5nSxOJ4v/+cmiq7j/lBrk6+jjZIQNoUT+jj58SUfl80ZjVWFlcfnchcLgJsmk9S+v0qY9oCJ+a33p82ugraXkV18n4vvVYkPpdJR9urHi/229b3CKlACDKbxihejjcCp97JAAqQ3g7cGVgIXjsZU8HQaGAr2GZLh0Xf4J52D+uz+HqCa7P/JYewkCjz",
"part_8": "mlH7o5mAJJOQCPopRH26NUAwSyw0ul1Gb9SHuvObz96o9xn9QNWpsvRH9MvExJGJSSV54hh1hxjEpPAs/twZT+eMGlQxT2pJL+lwf4goFtsR0ZPonK0i8MQI/D2mKwWLdk9f6SwfpL5QPgy5ULKFxHUav2I7QJ6ODMD/8VfOu42yy+vPpGUbfx+ttj/CBHZBti44UM//xf2OFayBIkMUKdSzaf0BvpiUvZ6mtoHXsi5R4bFHBbBLVPIFuzzNvmfUe7bA3LyHRPrp0qGzwGpEDggGzwhB4Feq4n/eRAiMAn",
"part_9": "qo4Cao9lD+FkJ1eyQRoiMSlb5su40UhuaFJGoMt9joVIZBKXsZQtkglAC3zj9S6LoBkmdIaHvulsEd3qXhfVvkx6Eh0ooQm4rSFu/QAtDaEtFdlNRHgrIwonMVV3agWSpJM2mexPbtKwu/cYasS7JyGJ89KJwgcmh11YaugbE7DrJhuGGM6Eul1fpqmV+l+He3US26pq81W/adoXRG+aSdDJXI+Z8Q00z5DEiYHeOtZxd59b3heIBb65DjRLYPdW7khIuU98R408LBErkGGr3C657Ue9n+1sbrtXfyK0j6",
"part_10": "2q7kRo1rquSuhp9Lv35vFokvbSlPRSvoeHUYJDAwiUqA8EsLPad5dViIkV2W8OzrBDmI5G6HgJXabubDGYorJf8V2WQ98xaBgfFej3kfQlQv0Hl+zrqfkQsQDqX9glDPTYtZeJvXewS+QDLI+9ieZCO3LkFyq0Wx3uXE7bwMG0vead9HCLBquTg+qTcmD/Bjw+vmF9MLDCIb8Z8t+6DRwyVcTAIR/+pkce6eOQm6E3/ivRoX2kFj7wdzgw7Nct/F3o4S/h6sA/0v/Id3eVyR4rPboui0p//RfbsIJh0i8AAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/41QzQrCMAx+lZFTAjvoFA+95EGM7KKoIJ107UHG3t2khW4ogpTm5/tpQie4hiH5cx9DijdwMAnc/TPFUcA1R4FOxDNrEGgbge1GS2Tmciu+14qQsAK7LFQV6SnyEqzLzaI9mJm+oCxfjTbVxyLIaD4q+MmIIcXV+rg4HP5fIuqb9IMxqo6coYUxvh4X/buQNM1vmmESA1MBAAA="
}
}
|
codegen__primeintellect___2088
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVK news recommendation system daily selects interesting publications of one of $n$ disjoint categories for each user. Each publication belongs to exactly one category. For each category $i$ batch algorithm selects $a_i$ publications.\n\nThe latest A/B test suggests that users are reading recommended publications more actively if each category has a different number of publications within daily recommendations. The targeted algorithm can find a single interesting publication of $i$-th category within $t_i$ seconds. \n\nWhat is the minimum total time necessary to add publications to the result of batch algorithm execution, so all categories have a different number of publications? You can't remove publications recommended by the batch algorithm.\n\n\n-----Input-----\n\nThe first line of input consists of single integer $n$ — the number of news categories ($1 \\le n \\le 200\\,000$).\n\nThe second line of input consists of $n$ integers $a_i$ — the number of publications of $i$-th category selected by the batch algorithm ($1 \\le a_i \\le 10^9$).\n\nThe third line of input consists of $n$ integers $t_i$ — time it takes for targeted algorithm to find one new publication of category $i$ ($1 \\le t_i \\le 10^5)$.\n\n\n-----Output-----\n\nPrint one integer — the minimal required time for the targeted algorithm to get rid of categories with the same size.\n\n\n-----Examples-----\nInput\n5\n3 7 9 7 8\n5 2 5 7 5\n\nOutput\n6\n\nInput\n5\n1 2 3 4 5\n1 1 1 1 1\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn the first example, it is possible to find three publications of the second type, which will take 6 seconds.\n\nIn the second example, all news categories contain a different number of publications.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACb8N2gC/+1a624cSRV+lWLWUjzaian7xcIgkHalCGlBAoGQxzhtu+zp0NM96e5ZjzeKxEPwADwLj8KT8J3qnou942QzNOKP7dhT13O+cz9l5cPoJmuzJraj09Hv63we35RtLIp43Y4mo9tled3mVXlZZvOIA1jKy5u4Gp1aLyejqs7v8jIrLhd1NV8QhT9UxfeRtbPIbquiqO7z8o5dVzf0gTNXRZyzZUMzOoKVuzqbz2leZOXdMrvD4kM7q8rTaTkt//RbVsb7htXxuprPYwmgwMKah6YFnZssLx5YEwlqw3KgrmPTJk7LqyK/TocbVt2yqoz0cVQesZu8eVfhLMN2vAP+",
"part_2": "2ABpzWJ2PQOyWJ+wb2i4Q4JdxaIq7xrWViyususWXIliT+HhhH27JrBeYkf5EbvKWixlBXFpZ/MN0qPsEru7GE9I2D9CIQXuNy379c9/w9KgWd7d4ROsZ1mb4DUsqyMUkiWVbhQTbx4LPa9wClDz7yPQ5rdP4M0y0IEubm+hMyijXM6vYk06ekTlHrjzslf0YyM0J4wAt1l9F1tw34p5nZXsFk4CBmToIj5nmmSS/Oh1uwOs53jUkooacCxvwInU82fSQN4kv4HD5PPlHAZps4K18Fn4yXVsmgwkYKXs5ok6sEb3AGJZtMT3qW3iKl4v6eyENbhfFLv+Mcvg0p9X16/YX6olif+q",
"part_3": "Bad5hUuPQOwa6+ohAXoCI/nBtHxNX2/KxbJNo7Vz3OY1XKLIO2fOaR+hVTY5OQhWdrR9B3Tw9n/9899//0ditEWcAmpHuOMjwaZT3Cu7D8n5dDrhnB+NN27ZGeITrCmyer69f+9j/TQsnxq/C5BntbOFCgbdQPC/hh2c8J36p8NstzDJg/IW3vy3Ph3s8Wv4UHJrCn0o8aknPwr9DdJ2B6kZH+0a+HfLdtfCSL3wLCLeI9xqMLk7HL2O75d5DVAJb4K5PwQBFUuszm92kJGxKbzSpQbpHA7zQ9xF9M0qmy+K2PSYkgdOSzMtFXMs4MdjxiQzGBq61YkwLS1NtscFziimWRr237vH",
"part_4": "ecez5/pd1caNFt6UXe1Irh47PBMyDSJ/UTVNfkVK7S3RzuoYf+RV7dZh24cFbt/PcrjRfY6gJgMzu0ksOxz7GxuWlAKehgpOtBmy0+dTwcYjOx9MvK/ApL2h6+DzgEzRzKplgUSVDI+FGqmnSEmIJMTZipRF399V97TXF9Z1HSU6dWyXdScBqmw8QX2uY4J2TeU6ny+quqWCOS1vUaLZLGaL96xfpsli2cwm3ahaEK+SnZEHHifkx+PxtMywUiCEjufZAsvthPV7J82iyOnMmC5eV0vIccY+fKQZeeeKkbRUyVtUoDRLh9LKtE3j89UF7myGXydPQf/RxB+fErtsGkgQb44TsLR2",
"part_5": "kqMpaDo0XyWldus9uKb9CVLMs9UlHQV9DI9pmK5vVPBDvjjOJixt9KrpgWSYgitF4MP69PmG3muIv1HJ+epcXGyn2cXF+AmLNSH4YafcHLsIm/fLuIwYnl/04zVa7PXFLY03GsjGa2O8I1Y1mqx4XMSyV804KXkFgTZGeHdBS/31Vyusv5qwFZFpEUhUX9gvGFHIxskDs/P8AuKcc1jojK16q+2A+/psc0ZcdLtrxztOxyZpf9xt5XQ+GXoLYi01gKRhOkpKXm1REaJuk/2S8YTs+B0h2goLIwgGTfRykq8l2D87Yw/jHjeCYIFUeraOiOMtww2e7swulkfyvj5j3Yldifur22P9",
"part_6": "vd5okHm71e08bBTxFdsn4iltfAIwbX4KFe0/w73swHa7Y6SUFCFIJ22N9Id5n4Fe2v2Xdv+l3X9p91/a/Zd2/6Xd/z+1+2sizej0fPT27duunqJjfGn9X1r/l9b/pfX/L1p/WkBKGV1MRtSfIsWMzj9MR5Rnp6NTNh2lDHfZ567RBCspsrpNM90tJbu1BHTT4aqrEOm0TasfJ+zLGGyLz2712ceAH8hAgroITHj8prnR1jGhvVPMWqk9Mz5YyQL3Wu6XjE59OXNNgMFYcgbWKv1zJB3gGFqlgYP4Ad+CJ4wW1U7IpHEcMDS2gK9pYOhDEC3c8TTspNJkGikNBLGQRluvYTP0hcyq",
"part_7": "oDlzQUnPrNYcptPa4ZLzWOACC14qjT0JRFAMCHqtQdlwhU3nuTMgZUAWd6A2rbSxoOgAVwXOQlBQY3AygCWHokAwGHB2nvjirBHKALALGlvaQQHWcDIFqDIvcBrXwdFJhXtCGNwEGizbIBVUJ620TIKM3m8cgR1rvtw85GSSE1EHmeRQLkdk6ccNTlFzL82QRFN02CEpkjY9eeGQRBX9iCEpSiIJz1OD2shppSwCjJQQhtWAR6zyYIkyYjrBH861+PprMxmKvExFg9AGJIIwJFnFEnHjFVKWCsO5MZHtcypysB+SrGM2OZ/TLHg+KGmP0uA7PQc5KGFUJEfYneMCKd4NakUUViNt",
"part_8": "QCExQgfp+3TM9KBqNwF1UKDoWJSKgDhSqTAbqk6OczMks200sT2BxT4RXztbX9zjaEZNjkqh5tE9oKajuor9atT60E7NpNYjJfrAJTUZIjmeCWhLrIaDoIVS+x1bGOWlO4yzTz0itUgUP0w56nyofeNDNoqJQ4CQPnWN6EQYWiZrkV+kR76Br6JtC04P2p6ir0OPRx0Tk5Qe0CwhiNF2aWjTD8nJU4+L3orETDXVIQYgnEIfimbYUSKVHM4jdRhWxOCFQv6wsBwG3mioGkEprQ+BwWOcQ4cZ0IYiNdLZ5GzA6tD4qefc+NBQ8U5y8KB+WwliCN0bFG5pFLpQh7Qg0ZVb6bXBzCdF",
"part_9": "hUCtuJNola1Gg4qGkVplZ4Mb9KmyL3l8dvg0u+z9+ETKOaRv4Cnp6JQPJOvfJukNh6eGF0zh1ZKSElwNJla0oPa3LXCEAwEIplNioLSkEgTKwME4RK7gyPX0BAkA4SUeU0prQ7+Nh3WFdniqeDx54GSoPEx5/4yS4AR44xwIsdNO/4TjaZKyS3oQ4kkEzQAInk3wc3q1YWV/6FnFD4ZA+gnJVC69HtMyBMYjEC0rRbyxnFB4uLkRwlIKMkAkueX0EKUzUgQKRyGfacWlMcbpQy2J4kWPTsqCWpLroO9AvlJ4BZLqwZleysmpkCthNZxFAXCI2MFqQEKCdyxyr0URped04ofqo8mR",
"part_10": "U4MF3zLwNeRMgmSAwaSntkdaAx7FUSksjuCq0aDkuLT0TLZ+v9oSjQOx2oCnliA4xnspLBxeAkGQeIMgXQkrhdakRI2njoUcKGlcCoIehEfDZWBXFHLk4gARnEPiMyAINzRIw0HIlLxJ7xK+4yklwyLQBgRD1TJqUNVrzq00lGSpCNDfCoDE8mA8V+jdgpPSOnRxEhVLpTQs0YAI5HPPaCkIhI9Cq+e8DIguoaXDLv2NA922MunZFJwnmQ24kKejJKIwOTIiXA9RAN/XikxmuTLpryZI9Frz4RK94AdnevY/LBDswBqCpLqtIRf034uby2WZv1/G0WlbL+PH/wC1wXiinywAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2091
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given two arrays $a_1, a_2, \\dots , a_n$ and $b_1, b_2, \\dots , b_m$. Array $b$ is sorted in ascending order ($b_i < b_{i + 1}$ for each $i$ from $1$ to $m - 1$).\n\nYou have to divide the array $a$ into $m$ consecutive subarrays so that, for each $i$ from $1$ to $m$, the minimum on the $i$-th subarray is equal to $b_i$. Note that each element belongs to exactly one subarray, and they are formed in such a way: the first several elements of $a$ compose the first subarray, the next several elements of $a$ compose the second subarray, and so on.\n\nFor example, if $a = [12, 10, 20, 20, 25, 30]$ and $b = [10, 20, 30]$ then there are two good partitions of array $a$: $[12, 10, 20], [20, 25], [30]$; $[12, 10], [20, 20, 25], [30]$. \n\nYou have to calculate the number of ways to divide the array $a$. Since the number can be pretty large print it modulo 998244353.\n\n\n-----Input-----\n\nThe first line contains two integers $n$ and $m$ ($1 \\le n, m \\le 2 \\cdot 10^5$) — the length of arrays $a$ and $b$ respectively.\n\nThe second line contains $n$ integers $a_1, a_2, \\dots , a_n$ ($1 \\le a_i \\le 10^9$) — the array $a$.\n\nThe third line contains $m$ integers $b_1, b_2, \\dots , b_m$ ($1 \\le b_i \\le 10^9; b_i < b_{i+1}$) — the array $b$.\n\n\n-----Output-----\n\nIn only line print one integer — the number of ways to divide the array $a$ modulo 998244353.\n\n\n-----Examples-----\nInput\n6 3\n12 10 20 20 25 30\n10 20 30\n\nOutput\n2\n\nInput\n4 2\n1 3 3 7\n3 7\n\nOutput\n0\n\nInput\n8 2\n1 2 2 2 2 2 2 2\n1 2\n\nOutput\n7\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACb8N2gC/+1aXW7jRhK+SoFgAHuHFtSkKErOcoB92ADzkgRIXgLT8bSkHrkNsqmQzfEIgwFyiD3AniVHyUlSVd3Uj39mHIPzsmvRErub1fX7VVUT8MdgJa1slQ3Ogx8bXak3xqqyVEsbRMG7ziytrs2VkZVCAlzSZqU+BOfTWRoFdaPX2sjyatPU1YY4/FSX7xXYawXv6rKsb7VZw7Je0Q1pFqWqoGtpRiS4sm5kVdG8lGbdyTUubu11b",
"part_2": "c4LU5hf6g5ko2Ct3ysD9rbGWSO3LYTySkQgr+IIimJV2xZoZkKQZgXhgh4ujh4urqpwBP+i3fg8BN1CWzdWrUAbkO1SGVaxblaqgRPkoOGfuOmjhlcgPoVoTANKLq8h1DhBYyEUIdgawgrOQISno17fa0n217DS7/XKeUI6sRLFGt4SoktMq5adRcOg7RberLZGemmjz4kLI+aJPtNVV0FteIp0Z/Z6x4rsU791suQ9aA0a/31tFbN3nBWGQh",
"part_3": "kLC1XWZt0Sofogl7bcIs+9UhG7FEVsORKoWOWc1nbIRMKt3J67cOumtdCq96pBsZ57C/U7NnyJ8KhbdUi5E0BrRn142mb0Wo0KHauHfqsNR+A7ctwHWW1KFYGm7ZDDhUAoiHEEcf9NI0jGlz1cmMQ/4mUUxG5tFBtNwFvX9Qo2srGa0oFV24X1HADCAyGXEVw4MTQijt/uCXYPjwhGcBc/S1kuu1JaZ7bpqgUiE6XeElAewdcIftJmebRjKQ2",
"part_4": "GGDNNWbvFJGsowxrEIWgLVb3qyhrm81k8mSRpwi4szBl93phNZ3lESz/v4lZqRAfGwEqNbiDXIDO1Vg1mZZ+ACPCTUGD2lahHBJUbxXhbYj6iE35Nw9M//vvn7/9hVUtl1gje3qUtB92FJoRGtRusRZgo5XbUq+JRcKwLid/r8liF2CkmMcd5gOrMD9XZu7MXZ691c09adSjtkZKzl7Y4lPYt7AvMKywv94UvwsNY/NDZw2C8MQh3zFNWyAWT",
"part_5": "UtZrAz2rp2HmsyD4t0ul1otmTBRmCklhRIymIIr5L8W8wSWe0KgwTuXCxE5hHk8AZwISvLLC8M+ecHxAOHOE8eHFC4cbsj46mjbBrS5LQnprV1TSER1bzKb2uu7KlXcSLjRYK8qOUpj8gbQ1saLr+/qWnvnm1fcq4oOp0zWuzGInUyPsgY16h8UBUw07nsbi1GDx2raFcarkNBmxIqNGyRXFqTAmqvJKbk5Qk4jpTk5H7abUeD8tjMxL3dqTx",
"part_6": "wiQYvFFCoxkvgtjYdCaXKBOuTnD201e0e32WiMI8dHrMRt38zofY6/FCoYlTpb54uLm0k3bfOwGTf6dLFvlJm6/xl28XV7oy9c57fRM6IN1tzmYMrNXpEo/U8juDgHuIV75XV79p8l/bjp1f7095KvP+hmyu8l3ljlCbJknbSROjxTVr4+ojgxHL/0jb3fjb3J0sJvdsCBG1Qk+OUVIcBwQDrbB8oBzj6CXI9HLkejlSPRyJHo5Er0cif6nj0",
"part_7": "Q9kzY4vwjevn3rehYeP16OR//3x6PCICCCyyiwqrUIkODiYxHY7UYVwTkUAUPhyiMvwHoRcPTcQ8qsh1LrILcQq7yrdmnA22Je/RTB0yVRLu6T0WXjQ6zHf5/1zLM+Tl+Xvw+JyP6+CDFDDxVUKEhMAhOY45XibIpXBjP8jXEFvZZ5XYgo9Q/nbvcg1goQHJ7+c3dyX4h4thD/HYRlyiwzclECQjDwkq/FPH6U+XM8PnbegHvXkP6JXSr6Xzc",
"part_8": "bCDBpH0sPyy/g5RkyMBs4p48hj5F4dHUQnyUc6Bh638VD2ZN6xs5j8S4wA2Zw/Ch4nsHyfh0XT6nj4+fANHZcqc6lwxXxhC2ICSnsbXcf0N+J9/lAXnDaDp6se0TPhkU0RozKwByTMMNkvNOZhm9TsZM3Q7YUVEolRCRLTn1BSHic+QOB8B0zGy6HUxcjJ+6wLQ9m5IQjjxWVGAs846A5gn8Em0fVbsKnBMpNrr1sNIWhx/lsWJynQ7a+ZO4N",
"part_9": "nJEBiI85kJGx8CWGcDMhw9DQifuJY/ojc4U3n6Pf7xBT9ggdpNgdxBCX0h4BD2qePMcZcV9kh0uibN9vPJRcGZgMh9mJRwW71Lsl3Y2HbRa7E7/wHSLbjb6yIL5DMphJ7u2CgjL1IZoOWDhdTBClQIkwYcSm/kxIGTAfzAwHsCmXTDphujcKfr3AwcwhgQsL1RgQbjUmIILLJGwcTJDwpoyL7ZT1TZgSN/iwDKd2JthF9Eo05dLGYubOijGbk",
"part_10": "XHFp9emhCv+jBXikpHyu5TgFsHU3qY5v8jNvH38ZMqcYuZG1jsT58x71mckVxZHNdkV/cG6SoacY06VmNHA8UlZC2ejfw0Uvs3NWOmElRXOLaRztuuHk32QY5/1Y/YIM2K2CcvK9iGfeNckTDT3Hsh63xEWxCOvoVyWuRdRGXb1OON6POccFc68QU/Rhx14MlxxEb4Wu2vydc/TX+k4/cDB/em1+JL+Yai96oz+rVPBuW069ekvMCt51XEkAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/6VSy07DMBD8lZXPPeB33F/BiAsIkFCKUudQVf13ZsdOU85Eij3ZmZ0dW7maj+W0zm+vbVnbpzmaazVf88/aztUc5bmabCXUOhcpkvBO4sQ+ATiJCixgBkwSgDywhyZiDUpH0UarTV2NRS203wEpDp1JdHJ0gw5UAi70Vpk6etT9UGkqy3oGquYg1QRQ+Eg9HcPBO9OLk5nZk8wUjDxqXbAmpvI8QA8QWU2jwsMn8Zxd9rkcq9l6mj+ZyHm0JiLsd87RyQ2/vnfGStTa/Yx6SduziyZU8TXJJiq8MMvE/dhu3MGDUxxk6d3bQLsNZO1Fi6e1PfwKu/g/aNjfzMGc2+X7Hf/csmK7/QLXfBBbiwIAAA=="
}
}
|
codegen__primeintellect___2093
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nFox Ciel has some flowers: r red flowers, g green flowers and b blue flowers. She wants to use these flowers to make several bouquets. There are 4 types of bouquets:\n\n To make a \"red bouquet\", it needs 3 red flowers. To make a \"green bouquet\", it needs 3 green flowers. To make a \"blue bouquet\", it needs 3 blue flowers. To make a \"mixing bouquet\", it needs 1 red, 1 green and 1 blue flower. \n\nHelp Fox Ciel to find the maximal number of bouquets she can make.\n\n\n-----Input-----\n\nThe first line contains three integers r, g and b (0 ≤ r, g, b ≤ 10^9) — the number of red, green and blue flowers.\n\n\n-----Output-----\n\nPrint the maximal number of bouquets Fox Ciel can make.\n\n\n-----Examples-----\nInput\n3 6 9\n\nOutput\n6\n\nInput\n4 4 4\n\nOutput\n4\n\nInput\n0 0 0\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn test case 1, we can make 1 red bouquet, 2 green bouquets and 3 blue bouquets.\n\nIn test case 2, we can make 1 red, 1 green, 1 blue and 1 mixing bouquet.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACb8N2gC/+1ZzW7bRhB+lSmBAg6iKvv/I0CnokVzSQskN8t1aHttE6VIh6Ri2UGAXnvvI/TJ8iT9lpRkqaHQitClgEkY3N2Znd9vZlfwp+QqbdI6NMkk+aXK5uF10YQ8D5dNMkquF8Vlk5XFeZHOAxiwlBVXYZlMjLejpKyym6xI8/O7qpzfRQlvy/xjoOY20HWZ",
"part_2": "5+V9VtzQZXkVP+C5yMOcFnWcRRas3FTpfB7neVrcLNIbLD40t2UxmRWz4sdySd9nIafbtKa6nEMoRIaqnlBFVbhaT0d0QzdVCMV6gdLiii7oIl9stozpLTTep0VTU1PCiNbKekOPi/P0t0B1+BiqNKeLcvFhERpsfHcbqkAp/hQ1D3ehpvJ6Q24NJXq32p3SLImWrciz",
"part_3": "ZERZQ0UIVzXJbZvHu3s68/t37bj2j32ti/3bdr3f2TXPljHmfft4NHKET6c1BpJvixpTdPinkN/RJj0I3TVg0eZ0ni6zOcJXLOYXodqOFNUgX6ZFa8Y4SpkV38XndXG3aNpRXHoXsZNVdUN5VmBDWTRpViA/tzCIMoDzJqariknv0nzC6Msff7UrI0zjmLNf/Qv68vuf",
"part_4": "rU1PtrS+PXm2E6Iti35eNNsmoSyK5t+820Sjz8Uflun8Lg/1SmTr8ayQZMhHnk7frDBxsiIqoE1tE9UWkRHebSLrlK3UvSmbsLH+dUFNQDgvUeTER3T/lIUu22sfRiRoB4ddHa2QtKmHr2SKHpkbBI3W8OmQtIu88TrhWXSL7rMcdYcSbNAw2g0P5QKwKRf5FZpFTAIW",
"part_5": "KrSCfBG7UgQeeMsYgPi+Ke8jbdWA1v0myqlCs6iKdhndKIzRx6pwjbIuLmNbq6etAScvxvVdnuE7K67LijLYRRUaUziRLyaxzInq0+wM3M1JHICvHtdl1e6Ib1rU0/qUnb16JellfcrXAxEHkWHZkr/F+GEa6XH0OI0McZRdnyynU9a5Pp0+TqeiHcc930zZ2gZoeTnl",
"part_6": "LfvDmn25w873sD9uSV8+sYs+9tabl1N055Pl6GH0CBfbHJxg+QUC2IYKwWsq1Cfmq3g/HwLPh8DzIfB8CPwvDoG1kDqZnCbv37/v+g66+vOBcOCB0LmLECZnoyTCAiFNTj/NktgsZ8kEDafN6PkqV2g3s6QNckfsygAyWkLZIbqlmHb184j+u7CubPqEqcOFdWXWJ4wN",
"part_7": "EQZHe4XJw4VZcntiZg8X5vYKc4cL4xp+et8vT0p/uEQpyAjyoh8iYoCJQiptrPPUM+rVsks9zHrSpI8FSGOMY8YaS9JprZj2nKS2Tjnh+rGlLGNGCz5AmWOMM6MMWWE5d1wYctw6x5SRvbq04sZ4q4boEt5ozjiUSSHgluWkrXDWe8n7cc659sYyfbgyoYTTynlDSgkl",
"part_8": "hReKuGPSa6v7PRPOacO5H1D2XHoP4HD4AxQxyclLDVVC9ANaGkQBrvPDVWktuRPWC9x/hFHMGoIiJaz0rl8X90YoqwfEUHtrPVNaAh1MSeskowhJHYPYnzCBEhKGD6gh5ZXnSkXYa+OdMBo40dYrYfYUrJbGcCnsgIR55oB2qRwZyzXC6ElwC1g70++YRCiUd3ZAGwcM",
"part_9": "rDAMKozwTqEELHkroEzK/lPMaY5q93rImWE1V0wwRiYiTDnFyQCRwL/sP+WMVYwDHwPOYQ1cOYZskRQQ47RX5Jk0sMDuwaL0RmoxJIrSInhKoYvjg6YYdXmBsd5TZGgbDJAdUmROok8hVYo0+hRmwhH0OIvW119lBg0TyBcDgI/+Z7nhAkeI5BwFZCUJWG6RQbMH+ChA",
"part_10": "gX41oC16vIwxTUJxwBGJI2NQ5SiG/raoGLPMobkNaIts/VDvsP8Y3iUPVejXz2bUn7hd6mGQXG+lr0f+2MoQN+LHu6ZuRYrtucWtnmGmHu1GzY97PRckjiVM4g6sj3XXh13HdHPfdVQMsQz55MfyE+VI9lg/Qwx+hjCy/Yfo+kA7i//Uqs8XRfZhEZJJUy3C578BKfBaUBUbAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/22ROW7DQAxFr0JM7YL74qtkDDcJkgCBHMhSYRi+exQXkrNU5CNe8T94ba/jaR6ej9M4T29t3669vQ+f83TubQ9PvZVxsCMWOFeqGwVUcIWKaO9DbzvoLREJXR2CgyiJHZIiE9Vlldw90cMDJM0UrQjEIjU5fbWMNRLNC4Q9NK0UCsVJMVaJWNQ8suCfbbUQBPyBCPAH0Z0O33iap4fSabSkKtuym5L7UnqrrIHoxrRdhKRcjOVvzM3ZAvzaDre2a+fp8vGyfGGcl3H7Ai3WUECdAQAA"
}
}
|
codegen__primeintellect___2100
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nSoon after the Chunga-Changa island was discovered, it started to acquire some forms of civilization and even market economy. A new currency arose, colloquially called \"chizhik\". One has to pay in chizhiks to buy a coconut now.\n\nSasha and Masha are about to buy some coconuts which are sold at price $z$ chizhiks per coconut. Sasha has $x$ chizhiks, Masha has $y$ chizhiks. Each girl will buy as many coconuts as she can using only her money. This way each girl will buy an integer non-negative number of coconuts.\n\nThe girls discussed their plans and found that the total number of coconuts they buy can increase (or decrease) if one of them gives several chizhiks to the other girl. The chizhiks can't be split in parts, so the girls can only exchange with integer number of chizhiks.\n\nConsider the following example. Suppose Sasha has $5$ chizhiks, Masha has $4$ chizhiks, and the price for one coconut be $3$ chizhiks. If the girls don't exchange with chizhiks, they will buy $1 + 1 = 2$ coconuts. However, if, for example, Masha gives Sasha one chizhik, then Sasha will have $6$ chizhiks, Masha will have $3$ chizhiks, and the girls will buy $2 + 1 = 3$ coconuts. \n\nIt is not that easy to live on the island now, so Sasha and Mash want to exchange with chizhiks in such a way that they will buy the maximum possible number of coconuts. Nobody wants to have a debt, so among all possible ways to buy the maximum possible number of coconuts find such a way that minimizes the number of chizhiks one girl gives to the other (it is not important who will be the person giving the chizhiks).\n\n\n-----Input-----\n\nThe first line contains three integers $x$, $y$ and $z$ ($0 \\le x, y \\le 10^{18}$, $1 \\le z \\le 10^{18}$) — the number of chizhics Sasha has, the number of chizhics Masha has and the price of a coconut. \n\n\n-----Output-----\n\nPrint two integers: the maximum possible number of coconuts the girls can buy and the minimum number of chizhiks one girl has to give to the other.\n\n\n-----Examples-----\nInput\n5 4 3\n\nOutput\n3 1\n\nInput\n6 8 2\n\nOutput\n7 0\n\n\n\n-----Note-----\n\nThe first example is described in the statement. In the second example the optimal solution is to dot exchange any chizhiks. The girls will buy $3 + 4 = 7$ coconuts.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+1aXW7jRhK+SoHQYmyMxiGb/8ZmgcUgwPphJwEyb1F2hqZaUiNkt0I2LcuGgT1EDpCz5Cg5Sb5uUpYckQOb631YrGjPDNldXfVV1VfV9TD3zjzTWc21c+l8V4mSX0nNi4Ln2pk6i0bmWij5SWYlhwCWhJzzW+cydpOpoyqxFDIrPq0rVa6Nhu9VccNJrzgtVFGojZBLytXc/AOZ64KX1NTmy4hgZVllZWm+i0wum2yJxa1eKXk5",
"part_2": "kzP5vVKSsoXmlRV/v2rkMnv3fgXRjESNI3PaZDXNRZ2rG17x+ZSEplpnleZz0oqy/OdGVJxqVRpEVVmTWlAubkQh7jLjGRkl/IZLKrPqJ66J50qqcntBfyfJN5Q3VcVlvqWsUjWfwhm4BaVZUWwpx98wNHPylbhbiZ9mzgV9KzmtAArW19mWhKRu0y5dN9AEJTDSaJJqc2EdzepVZpH8s30D5OxaQaI7YvF3p2rarES+skK1KuaUaURS5Jwmd5O9",
"part_3": "sTWi1p24oNaAgTW53ctMO3N2fbtfv6BvMhhYiqqgjSiKFnWNCMntHgUWamQlz2SXUiURkhXMlkpyBPDjSgArYsB7tElERvMlpKWS7yRfIhtgjmzKa6yZJHV2bIA+wpBR0Oa6qWuT3hUXFa3BgtqGbqEaaVYRDsMWrXRW9Ogzm1uLIbcg8oqD/XSmKprz9uOcxALecHMM0iVM33B4C5pU0HmYT2NJaeO0gWd85vt9GHij6RppWhfgJaiwBjMR9ro9",
"part_4": "2HpkYNjQ8dvcUJsjSnq1D8/eg116TETeK1mLeVcZ+1rjt1m5Ljgy3qzXIOxh5sOBzAeH65mNIe8YhZKxgdgRFr5M/EOiXC0OPJkr4+9TN/aabdwfCTDx6C159DWxyT7V9A+1MUFGGS+m1njnzw5vm4jWJ4ur1W6Vy27dmlhlINMkOvb4YNfv87v1ZA+TdTD9Q5gmAVdIaA3y6pZy4M3WEKIwLEZbMbq6FoUqtyl/WuWoDGnruz9ehi11Y8rcltCO",
"part_5": "1gcRNBbK7FaUTUlIdS3QXfvqhz6oazXfWnuWs9b7DGy/1hZXhnpdElrZXg1MPrarZ9qhBW6GI8jo7aIUd9yWXQ+XbRZta2hT+6SkzsRjjEW5VpU2EdusVBeD9p5Bn6sRbxzfXSs73ee2UGbynXmu5LrR9m3XTxaiqjXyZektdSakAVlxvis92yyntjOapJnuejZxaTaD/7dT2rZvnvuvey95MIJeu3L3dOP8t19///cvvf7n9b4+p0MS+0p9WpuQ",
"part_6": "yfYd/sDVbxt96CsudUO0jXr06/LZOX3apdrG3WKwicXpL6W0uwZNZp8k9jAv37QFXndwbZpmMqSAfCPT+jKTPnm26NrtiBJih9sxua3OTusHpXlPsrtuYkg153VeiWvcI6ItVkwNmpdcIpZX3YoZBeaPhyz8tRYlrgDcu42dHoT1cK4O2p69JB8b5MeenuKjpwToKfHk+JYTxsNHgtcao5ON+VY1uG5Vg/t+bROKhWqPAyAgq0wszM8HtTF73Si2",
"part_7": "m7yMnorrpmr9w1zGLzDRVXzBzYxjBjzD6ykY/DUKo9ZnZbY+g7FpC+vs/MLeZGfn5+czmUPolr76CtJvUQzmxZiubu36X8xXtcX7tn3HlYqtt4S1v9Id5jvCY105W7y5zx/IfQOlvKh5t9ce+BsOdAtPD5i+/ED3d/QOYg/mrNk/OD8svoU4/La+wGddofbx3YXpNMWeptjTFHuaYk9T7GmKPU2xpyn2NMX+T0yxOyW1c/mD8/nz53YCm8n/m4nW",
"part_8": "QIXfzo9TR/NaIw7OD/czR2/XfOZcYryzafjUBdiZYsXGoN1suQoddkO1jLQ7hrRm/WFKz1fXcrtPnSH5i9WFUexTmvhA6cf9KENKXq7XJbfz7s/63DEwoWxAnTdGnTeIbpw6nwUu+UEYDKXaC1OWjEk3VKet7gTKw17laRiH0SjcbuIHjJjrJ0FIEfNZf1BC8iLfHWGAxXGCH+ZCQxz5KQvj1KUg8RloF/Q744/xJAiiIHVhKojIA1TG3ICFbgRq",
"part_9": "eyxNggFjXpwQzuEs86IRxZOwgEUhKid0XS+mOEld5sOgm7jMjVFSKeqLuSzx3f6ahTAxL40TP3K9wAvSl4NI//zEdLSUDDDHP5LsessLaXT0HENIByojOnrGVWDgstRHI/MThpimHvNBbfymfuCR7yUuQu3hT3/rRCFQGvte5AUg0YgkUDwU4nFVTx7ahTugcUSO/IiY3zXy44vDG6UwBMp4oGGMaRYBRaZ6+2kyRiMwJgGxYKipjYkjbsPwCyrH",
"part_10": "RDImsO9VVYY2OzH5aa9ShhYxYvJgKKQUGRpIUUph9DrNo3et35MeyRFEQQUMXa7BmOIIMPMlA/NFMCZGGPq8oYFlTH8BrcLh/hL+99LY33+910pjOuTUqDCFx6jCZ7k5ACHsF3wZtV4V06gw4y43v/0EZ+MG0QHshx8D1BlzG6JtMM9juBNdzAV42hfmDhVtGr/CYJb2TUXPZ89/SmCKvkCRoWZ1TNYfzX9Vqj81UvzccOdSVw1/+ANCmOfm6yQAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/21RywqDMBD8lWHPHhLzUn+lkV5a2kLRosmhiP9eLcWspkMgu8PO7G4y0W3oY3c5hyGGOzU0eXp0rxhGTw1OnoxggN1lkmfC+85TAU9aHAGTUzKjkkN9hENGVTBbvTRYTzKwqFBumbIwCtJxotIodTLIh8k71lBfQbsq+hjYK0nov4sIpFjlfmxEto1jIrOLZRLYDL/KdqaCxvB+XpffHOJyzR9D7mj75QEAAA=="
}
}
|
codegen__primeintellect___2105
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nFriends are going to play console. They have two joysticks and only one charger for them. Initially first joystick is charged at a_1 percent and second one is charged at a_2 percent. You can connect charger to a joystick only at the beginning of each minute. In one minute joystick either discharges by 2 percent (if not connected to a charger) or charges by 1 percent (if connected to a charger).\n\nGame continues while both joysticks have a positive charge. Hence, if at the beginning of minute some joystick is charged by 1 percent, it has to be connected to a charger, otherwise the game stops. If some joystick completely discharges (its charge turns to 0), the game also stops.\n\nDetermine the maximum number of minutes that game can last. It is prohibited to pause the game, i. e. at each moment both joysticks should be enabled. It is allowed for joystick to be charged by more than 100 percent.\n\n\n-----Input-----\n\nThe first line of the input contains two positive integers a_1 and a_2 (1 ≤ a_1, a_2 ≤ 100), the initial charge level of first and second joystick respectively.\n\n\n-----Output-----\n\nOutput the only integer, the maximum number of minutes that the game can last. Game continues until some joystick is discharged.\n\n\n-----Examples-----\nInput\n3 5\n\nOutput\n6\n\nInput\n4 4\n\nOutput\n5\n\n\n\n-----Note-----\n\nIn the first sample game lasts for 6 minute by using the following algorithm: at the beginning of the first minute connect first joystick to the charger, by the end of this minute first joystick is at 4%, second is at 3%; continue the game without changing charger, by the end of the second minute the first joystick is at 5%, second is at 1%; at the beginning of the third minute connect second joystick to the charger, after this minute the first joystick is at 3%, the second one is at 2%; continue the game without changing charger, by the end of the fourth minute first joystick is at 1%, second one is at 3%; at the beginning of the fifth minute connect first joystick to the charger, after this minute the first joystick is at 2%, the second one is at 1%; at the beginning of the sixth minute connect second joystick to the charger, after this minute the first joystick is at 0%, the second one is at 2%. \n\nAfter that the first joystick is completely discharged and the game is stopped.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACb8N2gC/+1a627bNhR+lQMBBRxUNSzJri9dCgzYLX/aAeufoS5S2qJtbhSpiVQdo+gD7D32ZHuSnUPJkudKQcMF2IA5QZyIIr/zne9ceH7kY5Ayywy3wSL4sRAZv1GWS8nXNgiDTanWVmh1q1jGcQMuCZXyu2AxjaIw0IXYCsXkbV7oLCeEn7T8wMHuOGy",
"part_2": "0lHov1BbWOqVfuGcleQaloSfagivbgmUZPUumtiXb4uLB7rRaLNVSfVcIrlIDrOCw1e6UhlyyA0IqoyUfwpsdP8COkc29hl/0wVix/hWPqBS0kgf84LDesWLLC6RUkN1sCDdKWMEkvt+IwtjmIAhT706BWWC3EeS8WHNlHaLhaDh1mOcb4+PGIfysS1gzRSQVyt",
"part_3": "iYR/KsteTY4VESYsVRRkUO6g1wtt4BalJaTkSdteqxPcwFHisgFaYCN7A6QEMBBmIDStsjA+TobNdErgB1ODkX/e1cz5khBeR7zALaYJEOnt3vhETy2u5OlHfBYJBrgxJ/OIo/hB+4WvMQ0EKX07WDRme8MxinNBHEohlDBFe8h3AImiTaC1Ol45aoG6tzg6Juz",
"part_4": "gytMXslx7Q/nEo6EPZIAGxZKGdwdBW2eEwaXYOSPN8gRIGeVBYzdieyMgNVZiuMVeMkwuxQAgdAaSKZwaS5seQuVsROrETtTM7KE/bo9hBQSDxbpQi6gDE7k9/sdClT0oUrhvWWHqEZlSPiUhE0jtcKtiJnuiCLSCsajZqUJueW6hl93ai8tO4vWnpDhe4qSJLb",
"part_5": "6COxFbTH5QkTpBpWZpMOArsLhse42qKaotIZRPDn73/QUuie6QHt11KLqliPoZD8A5dkqjJ8UpeNWwU3OaYE2pOHU/KvS3vKvnp0Nlw11tzCLwlfkwNtCM+qo8Q/5OcZ3SRYesrs2ztGKWhqbk7lpUpg0vJcquf0UL8aw/j01aTCqtFeacsbL7GF2CZMxpmpmBN",
"part_6": "r4/Lh+bH+MAPa9tx2cCa32OrtLltAZ/W2+DXOsfWddVdMN9ralCiao2dOPZVQUJ4a4PO2jHbHT8JjqKuF5MkLaBRvQ7JHqrp0jVdt3Q3UZ5Af8WqzrSNnpifnpiMy3acFelKk51qcJ+m5GGxj6ZI4EaGXTfIkPCVf30f4Iv7ngmx0WdjdvXGIWjFa08l9gmzEps",
"part_7": "X8wuR4gB5xnx73RsmIu89JPWKURv1RGgJV5tc1Vk2wYxTpuJdS1/Ga0OIuuoDyup28adrvXkhJzd1YnL7cmQPOJfX1kBfY62ihwAYlSxrxyFPcq6mb0Pcrvad39TR3HN4Ip+B0G1ay6JQPcSgs+IYXdMHjCMjC1XXG8gFaCB2VwdXQ5FLg76ulYspcj5aqGh3Yy",
"part_8": "5FDXL0c4cAH+IXjATbeAWJcvYwW+NI8vY6aV+yrFa49vU6qFS4NX8CqeWbPruMXK/xYKufgAI9fITtnHZnZAu8jfK6duYyrl3H1Mq5extXLuHoZVy/j6mVcvYyr/5dx9QhigsXb4P3799UQh8Ppf2t0XSrkFrwLA2zjFrkGbz8uA3vI+TJYwDJwUt3WIgQhrjjO",
"part_9": "1UvqxaiLW9ZV13Xrz93qpxC+HIp6dxfU5OFQdEvjTydcNJ96APbCzWee9B4PrUe32MvNTqjRw6FmMOuWP3k41hTiTiyPQMZjiLozNvFI2WgOSXdajH2SbAJJt/7jsQdar6exB7fJDJKkE2029/I07omCRwFM5jDuRotGHkWQwLTb06lHFMaznpLyShDsGz26RbG",
"part_10": "Hp+MRjOfdQfUohtmkT7ho4tHD43mPcrFHikzHfcLN/ZrIZNqdIh7c4gSi7v6WePTKGObdIZ171Ol81tN5vVSD+fTRwJIRTLqvvVnkgRbDpKe7xX5oPdx8+nhPCCKfCESPB/VorCJIHmt+Sfpaxr86VcU9DiY+Dsb3Qb2jf5wwt6USv5U8WNii5J/+Ao/dvSZ5IQAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02PywqDQAxFfyVk7cJ5oeOvNKWbii3IKGOyKOK/V1uYzCrnwMy9yY5TXiQ9H5yFXzjgTvhOq/BGOMCN0IAjSoQNXGzaVi2ADcU6sIV76AtbiFG/eDChDnDmZ/dLF+GqV9OihjnFTmN0warK6gPv/yUHNrjxZx7PM7Oc4/gCeMNZp/4AAAA="
}
}
|
codegen__primeintellect___2106
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nEvery superhero has been given a power value by the Felicity Committee. The avengers crew wants to maximize the average power of the superheroes in their team by performing certain operations.\n\nInitially, there are $n$ superheroes in avengers team having powers $a_1, a_2, \\ldots, a_n$, respectively. In one operation, they can remove one superhero from their team (if there are at least two) or they can increase the power of a superhero by $1$. They can do at most $m$ operations. Also, on a particular superhero at most $k$ operations can be done.\n\nCan you help the avengers team to maximize the average power of their crew?\n\n\n-----Input-----\n\nThe first line contains three integers $n$, $k$ and $m$ ($1 \\le n \\le 10^{5}$, $1 \\le k \\le 10^{5}$, $1 \\le m \\le 10^{7}$) — the number of superheroes, the maximum number of times you can increase power of a particular superhero, and the total maximum number of operations.\n\nThe second line contains $n$ integers $a_1, a_2, \\ldots, a_n$ ($1 \\le a_i \\le 10^{6}$) — the initial powers of the superheroes in the cast of avengers.\n\n\n-----Output-----\n\nOutput a single number — the maximum final average power.\n\nYour answer is considered correct if its absolute or relative error does not exceed $10^{-6}$.\n\nFormally, let your answer be $a$, and the jury's answer be $b$. Your answer is accepted if and only if $\\frac{|a - b|}{\\max{(1, |b|)}} \\le 10^{-6}$.\n\n\n-----Examples-----\nInput\n2 4 6\n4 7\n\nOutput\n11.00000000000000000000\n\nInput\n4 2 6\n1 3 2 3\n\nOutput\n5.00000000000000000000\n\n\n\n-----Note-----\n\nIn the first example, the maximum average is obtained by deleting the first element and increasing the second element four times.\n\nIn the second sample, one of the ways to achieve maximum average is to delete the first and the third element and increase the second and the fourth elements by $2$ each.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+1a7W7byBV9lQtBQO2urJLzwRkaSItisQvkz7ZA+6eIUmcsjSw2/FBJyo7qGOhD9AH6LH2UPknPHVKWHEtB1sv+M4VY5HDmfpxz75kRkPvRwrWu8e3ocvTHOiv827L1ee7n7WgyWm7KeZtV5VXpCo8JGMrKhf80ujSxmIyqOrvJSpdfreuqWLOFP1X5rad25WlZ5Xl1l5U3NK8W/IU517kvaNPwE0/ByE3tioKfc1febNwNBrftqiovZ+Ws/OHW11tqNmtfr3xd0co",
"part_2": "1dO19STfZLf46Wld3vqZbl288XW+DzR99ns2zdkvfVzDctt5P6c8Yd1hx4+uG5rW/oztXtg21FRXuU1Zk/+hCxpw6hBDMVssw+OjeN5SVPJTV1HpXsEe8WlZ1SGDu69ZhQoUxx5g1U87hbZm1mcvz7YSX1nCCf+Ny/KXdx/iC6ZW7DZBxIA2N3VU8IXclJjSb5YuqbfipHE+o9s0aTAGOfDult/Be+n0EweWW5q7ExKICMfx6j+cSrB0mdJYtD4J0LeXeNS21d9U5VfXeWFYCRJRMR+",
"part_3": "IOLHdgGdCM43FAvluyqNheUcHcuBgfgkS/z5tqgsiYT1e32XyTu/rA1uO6j4frgtVrD8OlD0B/j+dttaGVz9c7Ng8Q/RaugQNXx+/Y3Ky84Ottud604Y6HuJCWWY1g8gxIzquSKYeHVe09YGl9cDhmajhcVy5CumfjmJnzVHZfcfTXe/3Ak/rxjyfGi/24eRif/+ff//3nv0L45aa47uI+qKPAd5fmpjiY0qKrmwDOE/YOmDsG/CSEzxbbqnX5EbtflDqj03iAsvgCHi73PTgninkPk",
"part_4": "rvK9mknT9LOum7aNcbJFkWiIIlT64tgesDpHzbtIandI5cvWi7fQbv3uct7yUr3tG6C1b9UmxpQNQxm1nDWTbZAEy1wW9foTkJbZZAbd91U+ab13Eu1zx23Lfm6xuOCQy+rlvynucfKMad+gdyDhx8hMZ2E5L5lHh/9oQHGbrxn6m+bevur5vDtNbrwiwjdfO7XLbwgLl5YlfmW78ez2bJ28/vPji7o+vPD/WyG3O/PQNfn68/nDw97Vh5D6yH94ZMr1rlvelBD18xKQYqSWanI7HGe",
"part_5": "lXE8jY5cnViGGYoEr4tJ4kYertUnlz6G8lPV+kdu33bV0PWs74J82iU7PoFLdc3lClygXgsPqHf7VL8cm5cv2wBZ30O7CX3V72YsGe/QdNODIPpJTR9EUOqufu/cNmxGbr7K/O3R2PA2hOQPAnpsz1VWL46F5w/97mZzcO1qN70JUi3G5OH8sYsz5oHusjznGmraBW9QWM8S0qyqTb7A3o2O7moxVDVUgIPE3IqJ4s9P1R2/688Du+2f7dS+3dR9o1YLP8WxovZL9Ew551NGOfk4Keg",
"part_6": "NVKRpzwq3PoOrSYjp7HzarPMM3+fns9Jl3zRp2lQ1HmYlCvINITB0OG6aTXHmMp4BiXpD0RR1xAbxdbfKWAgE/ZaiEHCBu4sYhxLCheVs6IzNfEfY/M+KCeb+mj6en9NvsKyb1pkFl2e4m/Ci88f1dPGGXPYue9+NZPTdG4r7t4Jf9g9Ffx/QZjvngCokB5jaGuWK5x7Z19PX6+nr9fT1evp6PX29nr5eT1+vp6+fc/raGWlGl+9GHz586I4BOCm9nsROnsQYZEA1ej8Ztb5pAd3o3f",
"part_7": "1s1G7Xfja6pNkoMHfVczKC4I4CKN3Lrju79oSl8Lrq+iy8P9WnPPdhQt/uqGvnfT8fc6YH8hWTTmOZUhynqdACBkxkrT2eoIwiYQZynFJwSInaOTRKG0vCqITSRKSabGItsEBoGLaJ1iSEjiQZvCBlUiWOh5lqrYYLU9CQwYXFg3GHD9fJUU9iMC+p1SlSUjZKuSyNTqQ66tJqlcrB3AqdWkNSJEpI7jhUSRqf6DxljR0uXxXHlFiUu2V/IlbpCbc6iQarswAvoXJ7eIUViivORpaMj",
"part_8": "owgbW0CQIxNI0KNxyi5JLEaocrIkIpkGh2PU8lkMHEyFPggJXZ8pJESCF9JbbkflCYAp2PCW4MOSRMTUSK1OcGdVkmSDNcRTBrJOOpZg6xFx+VaitTa4VQiFQIlG0eJTTUXq4gsVBWEQcMDYWkUpcDEasaHaZOpkBAXIWVErKwn8EEdyOGqLI4M6EAlGaVY12SksauZVCRk4wTlleoYuoYOwKaQKKsiMigei1S0MdA4lZxohkinWg1WZFIrIXiLUICM4xQaYKXMGVmVSMgw1AE9Yaxk",
"part_9": "vk0UQaJ0emJrllqkQwWnCa2XSDQisNOhA5SJJZBDW6ATQXMipZIA0cYnwFKJMMlw0oH2FyaO4pC+UHGKbd2alKXMJtCHCCUmtMU0KBtUJNGsq4AsRsUeFw3UrBlqC7HYM1FWvH1GQQZ0mhqEGME9dC/ByUpCJsjIhEPEgQQrIoPKxF4eHz8AxWB/sADBGA2ruYlJ0LXiSVzCKhGbl3SDoV8utKA/slMrDy8WyfiFJ4+vqyu/GU5dUStDaqq1UkRTEDyQpNKgShrWDSak3fH1l8knzx1",
"part_10": "OPSW9SDO1SdRwkmloOKkEhvi9oQeSSksDKaTGhhBNYxzUIAm7v1KlSfwS1kQIC/UcPvqoRzVVzzFIf743yT98mR54FSd+3CTPLqNe8lNbh1zYo/w//9Q2vYeYxP5zIjv57BLJS1hTYVvT1H9O5GefZfeSbUr1+cRfwVIOlBk0JPj6WlbPK0SLl3jaZXWarWFaXyKXruoTSo4fKgbypHr0RNfNJ3r5OVPKvpwpHBlYRE9IKMYHzk19NbfTvt7zf5hrrjZl9veNH1229cY//A9z322ocScAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/4VSy2oDMQz8FeFzCHpYtpRfqUMvLW2hbMpm91BC/r1ySJeFPtYHG0bj0YzsS3oZT/Pw9DiN8/SaDunS0tvwMU/nlg7w0JIAA7c20P1saQctEZCgEQghU/Zed8e6rsNvKKtbBeGSWTpuZk5L3YGdOViExVx7ndEcyEoNH+YIoYcO5qYKEqzYnYXBWAQDCTuLnIKSFgGpqFk77rmSgKuEB6whVESyQCYjX7n0TATFbhEDvif89pixAldC8p6AMzmBWvV+z0rcw3DCakELGbNStCdGBIpgeFM6dqnTPK0GzXvFn2vpK+xme/yP0oe9RaFsdYvDMUzc4OTCtWz10rIhEy9a+W/K8Zp26Tx9vj/HxxznOK5fjLV19LACAAA="
}
}
|
codegen__primeintellect___2107
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThe winter in Berland lasts n days. For each day we know the forecast for the average air temperature that day. \n\nVasya has a new set of winter tires which allows him to drive safely no more than k days at any average air temperature. After k days of using it (regardless of the temperature of these days) the set of winter tires wears down and cannot be used more. It is not necessary that these k days form a continuous segment of days.\n\nBefore the first winter day Vasya still uses summer tires. It is possible to drive safely on summer tires any number of days when the average air temperature is non-negative. It is impossible to drive on summer tires at days when the average air temperature is negative. \n\nVasya can change summer tires to winter tires and vice versa at the beginning of any day.\n\nFind the minimum number of times Vasya needs to change summer tires to winter tires and vice versa to drive safely during the winter. At the end of the winter the car can be with any set of tires.\n\n\n-----Input-----\n\nThe first line contains two positive integers n and k (1 ≤ n ≤ 2·10^5, 0 ≤ k ≤ n) — the number of winter days and the number of days winter tires can be used. It is allowed to drive on winter tires at any temperature, but no more than k days in total.\n\nThe second line contains a sequence of n integers t_1, t_2, ..., t_{n} ( - 20 ≤ t_{i} ≤ 20) — the average air temperature in the i-th winter day. \n\n\n-----Output-----\n\nPrint the minimum number of times Vasya has to change summer tires to winter tires and vice versa to drive safely during all winter. If it is impossible, print -1.\n\n\n-----Examples-----\nInput\n4 3\n-5 20 -3 0\n\nOutput\n2\n\nInput\n4 2\n-5 20 -3 0\n\nOutput\n4\n\nInput\n10 6\n2 -5 1 3 0 0 -4 -3 1 0\n\nOutput\n3\n\n\n\n-----Note-----\n\nIn the first example before the first winter day Vasya should change summer tires to winter tires, use it for three days, and then change winter tires to summer tires because he can drive safely with the winter tires for just three days. Thus, the total number of tires' changes equals two. \n\nIn the second example before the first winter day Vasya should change summer tires to winter tires, and then after the first winter day change winter tires to summer tires. After the second day it is necessary to change summer tires to winter tires again, and after the third day it is necessary to change winter tires to summer tires. Thus, the total number of tires' changes equals four.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACb8N2gC/+1by27jyBX9lduaRaSMpBb1loBuYGaQwRgIOgGmkY3VUdNSSWJMFjWsoj1Go4Fss88HZJF/yH4+Zb4k91GkSi/b7XCQjWy3RBZv3Xvq3FexgP5UW4Y2NMrWprU/Z1GirrRVcawWttasrXK9sFGq5zpMFArgUKSX6ufadNQPmrU0i9aRDuP5NkuTLWn4MY3vFNiNglUax+l9pNewSJf0hTI3sUogN3RHIjiyzsIkofs41Os8XOPgg92kejrTM/0eZVCDVRlEGr5VGQotUdJYAxqW4YNpw/dpBipcbOgW7hXc6vTe",
"part_2": "2c/UAkXpggfCO5WRgTDCe5Vs8c7mGYENLc1uA9n8S2geQtiEBkLQ6h6QGEhXBQwbZcrA/SZCgyGtz8AmSsCmsMwiXLgJVyp+AJ1CkopqDbeMFNBIqB/OoWjDNysy4ITRotAUWahnah1my1gZHqel+PBlyCie2ODHJzGrMDOwTO81EImLUOvUwo1CO2rJaNtwZSFCZnFcqwWaC7MHYUcMOGzIZ4LkLFJtI52nuUF760RptslOIR6/VSthAD0RZegGh4bcJBwbG8UxmUcFeZIUSAsY29SYCAPmiNxU78kzqzpPbnDAAUAHKf2oz3mZ",
"part_3": "uqWRWYuqC5tRcmz1yJz9Ahul/l1oIfOwwLjAGXt60eCew8hLd9FCAao3IYgX0GGYcJoiA9dKK6fAJeXfY16yBGZTlOSJR4nFpDaOdK3Ukm29AMKhI5Z5VmSyTMMgFpQKJ7pQLRTi5SLMePU3NGo3DN+Fqnie1jHTLfq50tvc8lVRCCSK4kgrDr0w0gj4PqU4iYhjIENrBAoS4bdQD+DXf/wbb+mz+8t/gs5fB03o8O2tPGr88q9f//5PRrfjaxepQsH+U3G+T5NbEyVSEUhcGzCv/Cjap1aqgRcvTbjJ7cnKgbXPpjaM2wUVRiED",
"part_4": "ywMuMKHUT7nSCy4JekeHnQdN/Og2od1u09Un/Rnq0IKuUIED0WfhqOPxcTasJeqjFnpwx5REuHPen3Lrew+7irbPiE0qupVGJnqhjMyrFdXSvRxvYgMiZK3Aj7w//BwmWyy2Dj4H4kz3oYfPB8RZqwcdkpZVznSXbkqx7jmxvicWdGCIEwElA0A5/G31aUawP6cnuByyd6lVJalX2qutSjBjFD5ZdDdpHi+fw3GTApo4k/6ZKekwzSIlyiq25xhUsqf0Bnsw6eH01/te4iLg1wieQeb+lhvr2WzD+02Olrn1USbsBRBO+p3DYgBT",
"part_5": "IIy5MEhEOppcxvw2PJWEhKui1B1pfQZXxRbAw0szJWq9hvzMDFljVRBsO1h2E2VPaX0c4pc6YpXmWVm3Iop+NIBpifXSWNwWMsCHNC8Il4zEgQxMGue092QQdplSQtDvO9zgmXKbWewqSU+msEKJw3HPqdq4W83USmVUFHFv+tWr17nJXt9E+rXSd26jiSm2VCtRWG/gthPwB4m7hTdYYI2tJ+G2jpiagr7eaJttHOF3oyGyVBvNc4RFXOicY62mSdcfZFRI90dlfJHTYGiQhTcQ7MZiRQMdGeAE5bpMUNwS6OcrobM+q/2A9GC7",
"part_6": "WM9q6LzGTiJa+SZ+j2reYi1CfXULb9CA7BU9EIii4Vnw8XxdIjy2/82SXgGw/8xqnnUVGzU9N+U9bjwpQu9f7c05Rk2YDrQcEN0Ot1vcktQd0gNtJ1AcuOTx+Tt/BMcPSue1dnci9egingR/APpRsKcCz7u7DqZ78SZrQYG6p7VU42CT0Fu49SC45GsFniRK1T1LDY6p4zlBIesbhFcUf7RO6YkMzxWXN8eavz5SUEyi98U5ytIoznyXalUC5Iy5bgUf4O0+soNJPl0ofdJRB2JTljvFPVcKk2ZWLffWUCLeJcF3bsG0bcftpElh",
"part_7": "FWZTymJHReNwxo9SrknhFEjwkKmjGX+kl2RTTmPt/vKPJnxXNnKqPCG+L25URrNucVN5GHYkwltYD8N0rwB5s8gL5rC8OApab2hvdabwmEeLyk2mwttjct0rauyt/97fpuBTXFUxS348sE2kdxPe0UbTcwiNukuuW7tc8CPKvWZTLD5Khj/pbKWkGr3E14Cig+O7Bc07Kpsek2WSugwsEHODpX44nxsbZviCv55vUzJTVH0x6tolr+9YFPsu9z3suTbDbQjeuzZ9OSG6nBBdToguJ0SXE6LLCdHlhOhyQnQ5IbqcEP2fT4gKJaY2",
"part_8": "va59/PhRdpczfTktupwWXU6LLqdFl9Oiy2nR5bToNzwtmmnsurUPzZpVxmIXrl1/mtXsw1bNahSTvAmYu/ZeI8K4W8pD2nTvbafRBMuksj9moS6Pfm7Cl+jtPq23/+V6eVt/dl9/ykjvJeD7T4MPXqI3eFpv6wWKZe2toFeZxq7TiERXqLXHBExQ5xBao8rUDmDAYAeoGJkldgMy0q/KcSPJEiIDEwY/R84KX1fnxg4ETPsEJKSRJVwUO6ELY7YeDKpaVK8DE5wlmruUSEEgS6NvNE1mx47KibvussQYiGe8oK8J4LcwXygQwPik",
"part_9": "NeZ0rcjNHXbDkNKHbE+AyEHf0MeA2KIHY5jwozH9dZnGgP4GJN3n8SH/TWhUVHWBRQJ+jJiDnjNAvyRSfLIz8HvI1FVU0TowYK+PCOyEwAyZ8Q6T2mNaEQ4+Hjma+/JvBBLzA8I8dh4aUWkUhw1YrEOPem6o5wjhgaFYGoq3xLUjN9BnUx1ncOxGg9K3YrQVyKDLCZo1ZL872zLD5WRfvijaSHGXb3kaeQAv8XMo6AUdXwb0xMHsOyjiJArcjqAZCBmcL9WnI5N2+q+yEkNkc2M7/D3dJTovsjCQ1TD0w4/TC3mJHcycEddjCWMO",
"part_10": "oAG48KGck2DpgYTqGIIyMIKgKj4nMJbiJpVNErhPpQr/uhVyGrjW68qd9IVOWSqLHB1WFigD6QGSXi4Lu17n60uOQtfdY3fkPJ1UhoC7+BlXvYRELLussUM5PQEpRrROkF4zorLMzaa6lu4WUV0kyN4uqA4fgaiOY1bXqVbdmdW+bL8p9EFQ1RuIc3BVKx5zhcRQ5YImRQxr2pnN8Yv2xqSKilV1Xgpg5HRyo+a3Je+6KqpHbv8N8isXVSkXXojwXlW8DOT9boe2aqznVP4vWJ3nHnXaB/rvRWae6+inXNWmNsvV5/8CmcAAlZ80AAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/21Ry4rDMAz8lUHnCiw7L/dX1stedmkLS7qk9qGU/vtKcYlzKMHS2CPNKPaDTsu1zN9feSn5TEd6JLrMfyXfEh3xkShAUpojWAbwqDDRAYmkgxghDuIRLbCH9BDIiMmCTNCgfLd1dfCKuYd34ADX5FbMEraT4BBN36sYa7nqiA4x6tI8mBurA0t8LcN+rZjM1YClaEPoztVGE/C1UpsmDJvhiH4dAfWrYGN7dI3lPRNgQ9uA9Xc+7fBa8u4OuVU31G5lR++gf4NeDk860C3ff3/0vZai6fkPuVpI3scBAAA="
}
}
|
codegen__primeintellect___2122
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLittle Petya likes arrays of integers a lot. Recently his mother has presented him one such array consisting of n elements. Petya is now wondering whether he can swap any two distinct integers in the array so that the array got unsorted. Please note that Petya can not swap equal integers even if they are in distinct positions in the array. Also note that Petya must swap some two integers even if the original array meets all requirements.\n\nArray a (the array elements are indexed from 1) consisting of n elements is called sorted if it meets at least one of the following two conditions: a_1 ≤ a_2 ≤ ... ≤ a_{n}; a_1 ≥ a_2 ≥ ... ≥ a_{n}. \n\nHelp Petya find the two required positions to swap or else say that they do not exist.\n\n\n-----Input-----\n\nThe first line contains a single integer n (1 ≤ n ≤ 10^5). The second line contains n non-negative space-separated integers a_1, a_2, ..., a_{n} — the elements of the array that Petya's mother presented him. All integers in the input do not exceed 10^9.\n\n\n-----Output-----\n\nIf there is a pair of positions that make the array unsorted if swapped, then print the numbers of these positions separated by a space. If there are several pairs of positions, print any of them. If such pair does not exist, print -1. The positions in the array are numbered with integers from 1 to n.\n\n\n-----Examples-----\nInput\n1\n1\n\nOutput\n-1\n\nInput\n2\n1 2\n\nOutput\n-1\n\nInput\n4\n1 2 3 4\n\nOutput\n1 2\n\nInput\n3\n1 1 1\n\nOutput\n-1\n\n\n\n-----Note-----\n\nIn the first two samples the required pairs obviously don't exist.\n\nIn the third sample you can swap the first two elements. After that the array will look like this: 2 1 3 4. This array is unsorted.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "H4sIACb8N2gC/+1a3W7bNhR+lTPdxMYUw/JfEm8Z0IsNKzB0xda7OEsZm46ZUKQqUnGMosBud79HWF+sT7JzSMpSEjttOmUbCttNZJFH53znO39m0LfRjFlmuI3G0ctcpPy5slxKPrVRHM0LNbVCqzPFUo4CuCTUjN9E44PBII50Li6EYvIsy3WakYZftbzmYBcc5lpKvRTqAqZ6RheUOZc8hcLQHYngykXO0pTu",
"part_2": "JVMXBbvAxZVdaDWeqIn6SVgrObzkdsVAiitugOU5WxnQcxAI84LnuARS2w78wqdcWbmChTCQatSfw4IZNMINbvAZbqSgFQdTTBdeEUJTRhhLAFClAo4AUdh0glFUpfQSlhqdzklqueBeM4cpU2CWLAOmVmCXGmZO09RW0IRyfnpbRuMNs7WVC22hUEbniA4tSo5hQHuWe0EPgczgmjfF3xRMVvr5NVcg5qRyhTo5",
"part_3": "GVyjyLQRFLvbMDrwTCKSu1bSwgQTRqfcubPJCpQRDx6knFuMgJSQIzSRB/YoeM+cAINW5W/JboCKeYRRmWPqQNLeGgqKwRQtoKhniqAIW5q2QLRZF1g9v5N55AbqnXkexgDsLIEPf/yF1567djqdcP9Wvfum3H8f9t+H/fd+vwPk149cZoG0OfrgLJKdQMCsxrvVnlKdozcYWoMclCmwgpmLAvAb9NoxNlH79Hqu",
"part_4": "ssK6T7T0ihwSOXooBbqI3lgmFGU9lZHkZZiQsZb3TbnfSfe3YbsD9LjhxMGd5ymp1L7iF8wKrFiTsSnfNzxjOXMcr6vrLImJjpi4iD0R8OH3P53f6xgF5n2Yq7TaW1firSqkHJT3qkSQ3xUrU47C6MVRnZufC1sn57kzS8lEhGRM5ISkFgBCkrIrXkNXFhylEUUn47OYthViREhOUhXpOSHzbmHkKpUVReeU3Y63",
"part_5": "DqyBUGYbLJgcS4TwmFuA4mCDOobXnbpnXUdy8GeamyotSvn9xEdyc0k7ox4ywloKu6i49dVFmajqPH5/w9JMchOYdCk3UYn7N1GeZRR1d2Gzh5vQ27o9cNvQh0FdJDwRZPq0gO/7StbAXmBfqsLrnfTpTzVmPGq3WtWbp/n8WujCSKortVcvq6DFLkQ+CxpgpYuqf9+2UY2AZ3OLmXunZy8Fpq7U+soNJNKKfaWH",
"part_6": "XqHnFCQRZhSl5Lq3l4XsU9ypOMc8sTgXMRdmDo5Z6ELOQsBxIcd2JwuKtusjdqaJLnq/wIlk1nO2HKukJ+e2yL27OHR5B8d1zueYFmpK01ukGeIBszKkZsbnXk2rjdMW8KViOIb8utX2t8zdylYS7ufYxwRlXo6zmrdwbLeSboydZB/7d6mjFLysCbKbloCvIQmy3TZ+qMvTC6uRnYhT+OoYr5end3YdHNyO3SZ4",
"part_7": "mdgt3RdEVVhBnvoWa29QRS9HdInrki7tzYKe1EfimeoCw3gM3Y3UecpqwG557zDdZaC05jehktvEwscZuOU9XXobvN/k+aNweBa+PqaSr2EL5OBytzuG85yzK7/vUe1TJHx+bvDCVWpcDrVjeJUXPHa/N1ItucJnt/H93Ta6fT84hh8YDu7bWzW8j7L17TZba1ceNhaKmzwNAQ4oqfLdN0Svx33VCKr8m5jMctuS",
"part_8": "7XGpxTO9t9e51FjGst32UlT8a5mUZS2Uin3barU7JpMCr6WsbKlK+ERiv21tfaTtuDqrlUAbc4VG8Mp0FvwGJ6ahVodJMewOjwbDwQDGbtN3yWPQGbI7iSzHtm5v7CRCGKF9YZtzdrDF2Ry/3eB96Iq7E8nuRLI7kexOJLsTye5EsjuR/D9OJKUSE41PotevX/vxil8GdqeT3elkdzrZnU6+sNPJRGGTi05jt4lN",
"part_9": "Lzp5i4KrjE+iMUwip+EsdNMoxhWHzm8mExqAyJLb0H5CuZ19v/wuhk/X1pv4+deUvsGkGrGbdJa2HqW0PylnclMw+wFmrzmQwxIkbOOzB8PHqx2tCe3TBG8O7wE+MoIhDLxibPyNqU66AfSdnwYtJDW2XSDDextBo8/PkaTR4hiOeqPk4HB0BEejJBkcdoddGB6NDpOjwyNcGyZJv39wMGqOqttGN5iqgDRrtPKv",
"part_10": "MlWZX0Nq2NP7Bh7haf8p6G2a1vvePILW/lPEsvtk2frQp0bLsuZgxer9Ut3S1/vN9YINn56sLB/yeYung39q9EGfvwB6N/b3T0zeBjzd9Olj9DYY00/1tIHs/RcT6T9uDg+m1NOXzJNmLz3i/jDV7LwKf+tqTmmJs7mTUnle6G092Hw2oeR702elfpNf30klnTr6D4I8pf9aaM4KJd4UPBrbvODv/gak4cXVmygAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/42R0QrCMAxFfyXkWWFp17TZr9jhi6KCbLK1DzL271aEreKmPvU0vZebpAOeujY2h33oYjhjhYPHS3OLofdYwc5j6X0jTFS6whRgWDFZx7JESelxAy9P9i7sSJwIiCHS2lqGYkU7Jy3Qm2epp5+eKT9zT919zkGJaLrZRAwGStCggP6YYW1H9dPUxpCtmUDNsSusQGf1mbf0VV6PuME+3K/H9L1dTMf4AHVXyFz2AQAA"
}
}
|
codegen__primeintellect___2124
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nNew Year is coming! Vasya has prepared a New Year's verse and wants to recite it in front of Santa Claus.\n\nVasya's verse contains $n$ parts. It takes $a_i$ seconds to recite the $i$-th part. Vasya can't change the order of parts in the verse: firstly he recites the part which takes $a_1$ seconds, secondly — the part which takes $a_2$ seconds, and so on. After reciting the verse, Vasya will get the number of presents equal to the number of parts he fully recited.\n\nVasya can skip at most one part of the verse while reciting it (if he skips more than one part, then Santa will definitely notice it).\n\nSanta will listen to Vasya's verse for no more than $s$ seconds. For example, if $s = 10$, $a = [100, 9, 1, 1]$, and Vasya skips the first part of verse, then he gets two presents.\n\nNote that it is possible to recite the whole verse (if there is enough time). \n\nDetermine which part Vasya needs to skip to obtain the maximum possible number of gifts. If Vasya shouldn't skip anything, print 0. If there are multiple answers, print any of them.\n\nYou have to process $t$ test cases.\n\n\n-----Input-----\n\nThe first line contains one integer $t$ ($1 \\le t \\le 100$) — the number of test cases.\n\nThe first line of each test case contains two integers $n$ and $s$ ($1 \\le n \\le 10^5, 1 \\le s \\le 10^9$) — the number of parts in the verse and the maximum number of seconds Santa will listen to Vasya, respectively.\n\nThe second line of each test case contains $n$ integers $a_1, a_2, \\dots, a_n$ ($1 \\le a_i \\le 10^9$) — the time it takes to recite each part of the verse.\n\nIt is guaranteed that the sum of $n$ over all test cases does not exceed $10^5$.\n\n\n-----Output-----\n\nFor each test case print one integer — the number of the part that Vasya needs to skip to obtain the maximum number of gifts. If Vasya shouldn't skip any parts, print 0.\n\n\n-----Example-----\nInput\n3\n7 11\n2 9 1 3 18 1 4\n4 35\n11 9 10 7\n1 8\n5\n\nOutput\n2\n1\n0\n\n\n\n-----Note-----\n\nIn the first test case if Vasya skips the second part then he gets three gifts.\n\nIn the second test case no matter what part of the verse Vasya skips.\n\nIn the third test case Vasya can recite the whole verse.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIACb8N2gC/+1a62ojyRV+lRMhWItoTFf13ewEQi4wfzaBDYFleuJpSyWrmVa1ty8jm2UhD5EnzJPkO1Utdeu2Y2lkE3Yl2VZ11alzvnOtU8I/DaZpnVaqHtwM/l5mC/VO1yrP1aQejAezRk/qrNC3Ol0oEGAq01P1OLgJvWg8KMrsPtNpfvtQFosH5vB9kX9WVM8VzYo8L5aZvqdJMeUP0NzlakFNxU9Mgpn7Ml0s+DlP9X2T3mPyqZ4X+ibRif5OLekHlZaUVWDCZL+jf6bVU0rztM",
"part_2": "Ju9ZCWakoprQi/qeizKitFqZ7SMtV1RXVBpZpktaKspkzTrCx0TcWMvsdySn/K06a6ZmGG8ZrBBFRppisa6iFBTF1d07ua6vSTwlx6mw2pUiCa9iWwTsNs+Kaemy3XLdhJqr+paTKHhpamKKeqZAyGMaPiWSP4hmZZWdX5E2HGsq2srUBKy3k2mXcgxBrEuB1g33///Z+DG2RvA5uoKqjQ1/THWQ08RtrKNQbMuFVgmeU53avarOhmcdeiL1Wl2MbqxybN2Q5b60Y7DoUmBzCrzbQzNhuG",
"part_3": "qk/ZA6U1LYoKbtEtbuxeo2AlctXBgx+vshnz5b0VdpZsVvBabR/zZt162ICfqlmmIR0wdFFnE46GkUHSI8qzqsY26LEZC7OixK6enGG1tuM1/RWr6jFdPOSwF3ANK3pLwhmOYXCM3gvHGVM8JoGfD0Nrd6u+hW9yhX2+1ry1vdEBizA8qJbF2t4G93eFCThYjuMa2VBUVYb82grH5bzIV3Zkq2EOWoBe6aK5R2gg4UfXxBz/rBAFSDLVRo2BY5FqpWygG2/hs7jj7DASFuljtmgWHYAuAO",
"part_4": "6zmcmb2UrhedHkU04G63WNVIdHx9AsQ1I6htQiRGLTosnrDGYFYbWEBis67GsDZGFM8UPRoCB8NqqjpExUhWCvh4TUQdqhtFmLJfoNv97ph6Y2I576x9r6OWu+TnsOJchS99CEeV0NBSUJm9d+wKvD0TrXOpW3ZG6xB4FKOSFXVJ1AdnAr0BYdjhMOtLVkvZL8Lx+hZB+q9Vy8F85ugTF8+37riFcF7XBKjBFa1QOOhuwzUmmtod34RRVZq05FlC8kw60cQ4VpUXNFutU9dVFj9yrHEcsx",
"part_5": "b4taF+1G6k7xMBjfmQzB8VJCM4SyzRumqWAAkDOyAvSUQufOhTQt8AcFAwk+4X1DNv6wH01/a+p+OJlisKm+jdl+PO2JmlW9NsCen3PHpJqNhS7Xekr8xZavVguTIIl2Ex2SEImWFCPcXBIRPrxEe+T6iRaCpx0KMaQo0T5zs9bAFkwm2rEiWiFcsNZ2eqd7da+zVTbbKY1tbLXW6VfEealUq3ePZUvf8eTKndZ8wC3ZuLvHS09inxFKU9nn0x1Z+8vrOhsytp9NnzvgqdH8mKR7Qpmybm",
"part_6": "l9gIkSR3DecIdlPF1PCzafre9LXmubqVXvxHxKVTelxYjOSl2jJyvVDEVTT7hFq3HogPuVgXE1GiWaz6+Mi0DJHchVPUJzRXhpdA18QjH148gcc49M1u68rh7yDJ8fLHX6bEqOXPB9I+wjnHqFPLtKRyP69i1VrXR+GTtcOSM7o3L0P93iFmw96q21fNP32Qf6gxG4tbjC8dbQ7K6ZLpYttcOzojeW77fk7GFqIdvtvycx2qW4K1X6aXMaPC0Q+MrYiv1UIpvx3Lr20jtfeudL73zpnS+9",
"part_7": "86V3vvTOl9750ju/Uu+8YlINbt4PPn78aHuoRF/66P/jPrqbZn/Da4MP4wHHG7w4eP9TMqifHlQyuKFkYILotg2PASrmwFjbLrpJm6k7qdrmaj9ZbbZyukKo4VTYnDWsJK8nnLm8+vOYno+Ct0ECzsX2xUIooJC83qQBsTWxZ7gXnH8aKAlxxjSiE/DrG+21mDjNYuGWF9fS4tWL/F/2X38oYy8OQhmHByPuBIjxJsQOWLwG2Yf7hVE3PqcZ/Q22PYt0kk/KgxPheCQ3YYiXlxl8vQlInN",
"part_8": "cIB0K7J7CbdH/RJieGbrQJYcMLe82ySqDgtHA5ESbjYoPt5emcOSPEq2ZCcLB47BkJfr+ydLEp/wWliz06R5vyzxlU3n7do41w/0I1Pq/ozQL0MqJNW2SNDe3cZ5S8V8xz78hydE7ZPkUotkEkXSM6jsLAcSNBQez6vuc7Ifme4/qRG5DnCeEI30Vb60agkVHw2laIXscDcn9KvojocEftzXQ4pkVwT4wB57fQnl9G5zvC5cv2/9GXzucjGO+ODhrh5EtGe7QwbGqbtrMlp/TNpUEeLgW/",
"part_9": "5uF5L4NHFfkXqPfe16I4/pwKjr3qHBLtP69rfYbR+r9HGjBsWzl7XPE7IB/tnGfeYstSpkpF5ts4k/U859o7kGmwQ/u13KZeO9rLs5fjjUoXG0c6KB74s/6xVw73ALbDXtpRB7r7dNQ177Sc9NqL6sqxq3rqHe9k/zeWJdtf2YpD18BzX1X6vyf4Kbj4ac/XBeHX+Mk78tuZZ7lWnt7a7HxR0ldZusbsnQM6gPKcNyTXIdd1IyeUkQkTTzi+9ENg8zzPiQIUaM8PJS6rmBKuK30/DMkToQ",
"part_10": "eYQUiREwnMk4udcRDE5EnPi0JXojRGDsbSicn3XSfwBVb9IBYehKGfA0v8BuQKP/ID4fosKXJ8P/YpwLXZ9aKI55xI+oI9H4aeLyN2VoBrc4QpGWFD4MJcQniBLz2+7wVxGAAm6JlLFFMAqA4IBQsIQieEfaVADEJPktIRoc8BiaXADTwICN0w9qU0/pG8meCNUEDR6Jwt04FGPCC5fu+25PKcCKR3EgTbLR9+n9dIG0nLT9FuATlcFg6ep8DC/+mXVbeNzn5s1OCmLhv18/8Aoqa9n2ozAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/+1VzW7CMAx+FctnDnHalIZXWdAumzYkVKaSHBDi3WeH0jQBBNO4MC1umq9u/F83e/zoN6F7e/V98J+4wL3DVfcV/NbhAl4cknOdUSCLBgJSw/hHfxFxlR3O4Fj2NvHlhR1GA3qkE0+NSGcq7GUVFuwFUXsLJZwZaUojExnSlQRox1ATouTqnBEx5/iVCzVgoII60jQ78iRylpPDG6InwqukTSBybdRGuVPnudYPr+IkOS3HKbEoaIFv40Wxkasrvk2UqWJLGQ7HbrLdcEsL3GEm1dRktf6RoUyPNqBPv67fu/hsMEtFfa0Xs+zmLbYU4U3wxYGQlJYo9VQtJiX1w6Rh1nfILw84w63frd/5ROoDL4dvbbXa06kGAAA="
}
}
|
codegen__primeintellect___2126
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given an array a consisting of n integers, and additionally an integer m. You have to choose some sequence of indices b_1, b_2, ..., b_{k} (1 ≤ b_1 < b_2 < ... < b_{k} ≤ n) in such a way that the value of $\\sum_{i = 1}^{k} a_{b_{i}} \\operatorname{mod} m$ is maximized. Chosen sequence can be empty.\n\nPrint the maximum possible value of $\\sum_{i = 1}^{k} a_{b_{i}} \\operatorname{mod} m$.\n\n\n-----Input-----\n\nThe first line contains two integers n and m (1 ≤ n ≤ 35, 1 ≤ m ≤ 10^9).\n\nThe second line contains n integers a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 10^9).\n\n\n-----Output-----\n\nPrint the maximum possible value of $\\sum_{i = 1}^{k} a_{b_{i}} \\operatorname{mod} m$.\n\n\n-----Examples-----\nInput\n4 4\n5 2 4 1\n\nOutput\n3\n\nInput\n3 20\n199 41 299\n\nOutput\n19\n\n\n\n-----Note-----\n\nIn the first example you can choose a sequence b = {1, 2}, so the sum $\\sum_{i = 1}^{k} a_{b_{i}}$ is equal to 7 (and that's 3 after taking it modulo 4).\n\nIn the second example you can choose a sequence b = {3}.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+2a225cyXWGX6XA2IiI4dB1PgiZ3AS5mBvbQHITkDKnJW5KDXfvpvswkizoAfIeebI8Sb6/9qZEGc1gxCF8YYhsNHfXYdU6/Otfq1r6cHK92C92w/7k+ckft8v18OO4H1ar4dX+5Ozk5jC+2i8349W4WA8sYGg5Xg/vTp6X5M9ONtvl6+W4WF3dbjfrW0n4j83q58Hs3wzmZrNabd4ux9fm1eZaf1jzcjWszWGnT1rCyOvtYr3W59VifH1YvGbw/f7NZnx+OV6O/7U5mMV2MK+XPw+jWfDabhfvzQKJ426522vf5saMZonKr4ft7oxF12Zxfb2U0ovV6r12zbNmfW4k8c1CGm7MqzebzW4wu82at+Evh2F8NUgcBi5fDTvz8sqd8ebPzPn5uZ4+/PmjeebM//73/2jO/IsmeWe2P2",
"part_2": "tac+MpIszu8OoNmr5F3/2bxb7b+/NidehH/ObycndYX31Ymh+M+/gn7VxcfUDE8uNHc3m5uR22i/1mK6d/WG+uP5r1b8xyZ9aLd8v18q/D9bn5tzfoPn7W+xV2vhzMQBTen8t3hHKcTu27Dmtzu9ntlkTgV6nRZV+O3+vnx/H2sO9PGvpPxXy53e3NajkOCtF+sRx3Zv928yk+ZuwBWt+5cezvIZ2Z6fO6vzv7p3Z6fidzNyDq+m+Efg45GhOmxacwYcD4KUwLmfI3Mmfl/3DY39f+7+Cuf3+3WN+uht18Zvfe5RhNvByT8SYap6WTXpdj0Id5TTDeXo6uNROd8a3dX+fadMR8yO83++GTUT+OUyb2qAzT8eY9KSC0zPBffMbQS+z6gDP9xzOyom/F3v/X7A5L9i9Wyqhinim8wvs/70wwi5s9abdf",
"part_3": "/FmJutwbnHJYbUycAjFrN8f3F6oXPn4CxlLOMW+Xq5WQv9tDMh1dkrB7szmsriEYRZWBLQatDiIF6cnajXyn399v3mpuJq07jpKc7bA/bCcdYbDhHO7bDjfDVsrAdMv17Wa7Ny+XGNBljWfg9wdzwZHP3p3Cf1vzTkzQ9Xx2er67XS35++JyXPyyZZfjPwH052Y8rF/ix05NE+g1s2YGh2rZm8Xq5mpE6Gh+9zvjNbRQUniGFhfPp+kXDFxMj8+78JElo5ashvHZwp2eTQ/+VJNbJreavGDfRV9/PdyY65ude7Y8Ey5OoWjDzxK1zA+c7eYB/Wzd+eL2dhivn2nlND6sdsO9JZOo79wk7Ni49n63cBfLF6e/XZ/eU8E/pIK/r4L/JSr4B1Tw91Xw91WQevbMnvZHPz/ed9gOWAycOii+9wJ8MS150Z",
"part_4": "25gMR+MFaPWoA9fc1ArMUiw7Otu7PuloUTys6nP1er4Wb/bAvjrb9/N6u9X99eTTK3/uL2e/fCfGfeffLO3ey/AuzdPQdMO+ZZ6dIThiTenYL2jkSQvt/CuXyek+Nblf9W5b9V+W9V/h+2yt8J2Z08vzj56aefJq66HL9V/G8V/x+44t8xzJe/4P/kxdnJftjtyYeTiw+XJ/v3t8PlyXNzedLT8WpOtJMzRjqmp0lx3mfSQ1ZfsJkYra8IfRQe+uVCO0l+wZLHBLv29ZIT1YNdsfDXmtjQO+Wj0h8p3Ep8qCE7U1LVObG5YBx/mqm+leOHufL1xzk7G1NNCKZlU4rJxaRGFTaOVzT1yWzrh3XjXHbRmhyabaY4zmytpcCZ2RcTbWuRiPlaTQkedMRYsgm5hHpclfYIZcJsufDBER75Jgbciy56oWzh",
"part_5": "oZgaTTIF/6BZMrXo5ZxezGc2TTioJlmD9o2Vnoenclr45LTqrOfc2gJ6xZiyaTbgxpKr3mu1lXMba4qrntkWsMZ5FG8hEs+QHE4uLjcSIiWWN3yKsqFgX2y2BJOt9cm05IMztRaHiS5jWbKN8RCjAyOBVab4JnzkFDm76+FZb1wPWSmxxicM1pxzNcvjuBgLlB1OAE3S3TRMDYoX795rTSWakErTOxSQWIzuGQ1JKxzQt9s5nAA+0qJkE58scJ9TOeQKSxRP4FwMZJnPSd60MbEoFLQIxTJbbdHK7HNV4LKpraF0LSkRRJukcV+emktCasSY0FJR1uRuVQtyShMic8awmL1X0G0yOdoC1BFcJSBzngugoNiE8a1V0s7ZACKIbfdexL1kHeyQawAjDaQ9dVjvftiOh3JwnjRzgNFbZwl2AH/QH3G2wQ",
"part_6": "JMlKwlOlTHA8X55IoFfdVaSCUrf22ssEmGQ1KuOTCDj0LOpbCBA5qtmadiXcW2ILCWBsU2k1LOrYlsfOPwRD4nzslkAL4lOL6mIC9XBmPhVJehKUe4cmI2FJyacLgn/6qCXAPxyIQvkDXsLBU1koik2gjHSSVXK2aJ24mS90pAT3JlS/RNijEzQphcSzazUniABAqwIjjQfk2WsBbWQQ6JHQDFA5KIGtUTxIciNv08Km6tEiYio8rsMchiGSCBkGJWGUmTr4KJtfiEgymS1UWXQCWoLsElOIzwR+Lm+1MrLbHFeFIEr+EODKmJSILcgAi24FQ95kaqFiRkHetLbJ7ok9meEWUJ7APBOQnhvcQEBkiWjGfk5gqQRY4p+BQAGkRI4L2j4lXnfHWJoxyey8SFsWZBpgMNpbUMFmWro4iVKPiQnryIfLY5",
"part_7": "eqdsbK6CNIAUMzYDZEBQUAdYQ0AW3OEqKkWEZx1Qg7jArivwGthMwZIIx6M2+90/ovx+GbUg9wITDIjVix9q9QBGaZUIHmwuom2eDLMeOsU/OXgYISuk1G7olikcqQYLVAeMhmqt9xHqoJujAhEgMTY5hydEsQkPQIEkJ+WFEKraUq3Itpweshj+LDPv/Cp+Sb1CEDxgJRiod2sKalYxEKFCp8CPzFGhxAzTO68WsTWrlfSNekyonCGCVcVY5V71JlL1sMuKurzWBYgAXvCqnhAETCJMk8I4OmoMr4GWJjahIjgBwznV5HDcEeQOIfjV2QopYVtz6nhQoUQvMAcdLFMtnsnCAFCF35qajG4ApGixFrZhZ1BVQiG248AEl1GY6OjgbNoJlRqwnVSkRU1O7SXEQIJIesVB+LDzmIqy6pxvvd+IghlU3x",
"part_8": "5och3kbNOvxn5pALWISp1XvwByoXd6UWxCXRzkxERA0gmnUKloP6n5A92Yn0Wz7Tix5kgRfhxYCy4uvUGWEuAruKhQhCSnk0JABNIjGb1au0yJUOMO1yqYFDWfvBaVnrsAnIxz1aobcMpiZpIgK46SAMTSviFHAc+2F0h8xAyEJ+9YZTIinAACTl3vS1RRqUupC2I9vst8UJWKXaiw3ETKkl374VHZQpg9YcaJx6Mr+3N9lO8CSQnDB91WqC+cA5UJfRgMwBw551VDuUpI0yAixqNBnRaUJSM8vAxGIausmpKtqK7Jw9bSNcEMpGrfLEn0vFU+Lsok0kCQL0XFL8j/Xr2xV9mmMqsDUa3K6v96405tZoi+juVJMSawQWmCp+U2GNFpkA8Uh9mEpjJGZehcQ6rl470YhSS7+Ur61RCk8/PcIpRjAZag",
"part_9": "d1bu91sIhnhRAh2KFaxyE4tRR20niKBFuCarnIUgpkTtIEpUK+X7BaRpjy0qCDhXoGQPayQYrDfZR/WRYFCvzKMpYCsgpoqLglLt7WH3EqiiqZWnS5dLx9Q9lOi4oOQC+fYcsl0JWpHSF4fULQ0h9tLfZs1JcnUJUUyGLlyU7FH/qjmubZ78+oJEo2Fdz/KQQaxqAQdbOj7be9cqZyi1s7o5aiRaqyWmvSWr6Q2zunb5BO4tCkKlu+Q+qGuBpcXHa6x1mb5ePmFRFK2pp1VKph4q20FWsg+63Kk2dT3IYStu6y2Ttqv/iroMo7bXYlzv1A7DnFYu7Z4Fk1HXQTDuOlXS7IFawgdfB7FqpRW2ghPdfABQxJIcjCH0jgF3JjUg6nqJrr7kgKHV+ocOEQiGPGM3XBdFv8f5Q5AUhz8qMv7+TYT+RY+6Of",
"part_10": "cxXZLyPFKnBxggT3MkwfxES1jnoTQJ0zU83w3ND9ylp1VQTpznnPdfyMKFbpqj4k6rQeo0QsM8H8xle9rGvWzeryakP+HuO/VgimljvFMPG+an1O5O1tcA81OYN+ieM2nj/N1cuxNLAGcnUZOmIwXASedWZ1ceK+Lt3uxXhWn6gjD29BUH0kYePeIRoulEJMsd77vdowTebz6/+PAkGhfTv76kxBj6Jn6LeUD5R5RU7nBS2tz9Hv8W8DFFxqQu2D+gbHwMKnrZVxtuBInjvWN4RFNGtyI2eOBr6fIYgR1l1RzXsT4qJTq8uJIIwg94tTzWdv+ApuVRmrb+5a9R7SZU7snQGvr3dk3f8Lkn+yeEyZfhAQe4xwjs/yYRny5GYf6XDdfLilUNO96y3JHtC/3HzN3VYVz+5TCcPN9vD8PH/wPseJws2SkAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2128
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nKolya is very absent-minded. Today his math teacher asked him to solve a simple problem with the equation $a + 1 = b$ with positive integers $a$ and $b$, but Kolya forgot the numbers $a$ and $b$. He does, however, remember that the first (leftmost) digit of $a$ was $d_a$, and the first (leftmost) digit of $b$ was $d_b$.\n\nCan you reconstruct any equation $a + 1 = b$ that satisfies this property? It may be possible that Kolya misremembers the digits, and there is no suitable equation, in which case report so.\n\n\n-----Input-----\n\nThe only line contains two space-separated digits $d_a$ and $d_b$ ($1 \\leq d_a, d_b \\leq 9$).\n\n\n-----Output-----\n\nIf there is no equation $a + 1 = b$ with positive integers $a$ and $b$ such that the first digit of $a$ is $d_a$, and the first digit of $b$ is $d_b$, print a single number $-1$.\n\nOtherwise, print any suitable $a$ and $b$ that both are positive and do not exceed $10^9$. It is guaranteed that if a solution exists, there also exists a solution with both numbers not exceeding $10^9$.\n\n\n-----Examples-----\nInput\n1 2\n\nOutput\n199 200\n\nInput\n4 4\n\nOutput\n412 413\n\nInput\n5 7\n\nOutput\n-1\n\nInput\n6 2\n\nOutput\n-1\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACb8N2gC/+1YUW/iRhD+KyOLh9CaCANJMFLUh6pSo0q9Sr2385Ws7TFedb3r7K6PoNP9986uDYEIdA2y7loJIgU8O/vNNzPfzpJ8DnJmmUEbLII/NK/wQVoUAjMbhEHRyMxyJZeSVUgOZO",
"part_2": "Iyx+dgcXcbh4HSfMUlE8taq6p2CH8q8QnBlgiFEkKtuVxBpnL3Rj6pwAoa456cC1lWmlWVexZMrhq2IuPGlkouEpnI35TYMOAGPqHeAEsNSjuqHIH8Gt6rnG2gpNWK2RIssqxEDcz8jTmZK7AK",
"part_3": "jGfDwPCqFrhjsOZuAxHAp4a59GDA4EeI4B7SQbtaK8Mtp82cqrFCbchlAEzmMEgHIaSNhZZdofRKWY8mmyp95XkNvyLkCk0IpVoj5RGCxgqdI+1h7caCa2PhSmBhK2XsEHIqqwVVeKg1I8h8yS",
"part_4": "isQ/3KhnS3gaK7Iv7MJGxUQ2EzJY3VTWYJZ3M8d0/JkN0UHA09UnmpajVqu/kJHizVegMpuvIYTrVsN7SVqLjZpmY8S0/K7FhrdK2U1JWGW+Y2bymEVGVYlzwrISMlEtVaaeKhfAKJHLnXg6wb",
"part_5": "6z8503vCV1JsQHCJpDBpGZcUdk3wNctwZLBmmlnSQkujLWHbF1cbuBpEkCQCn4AWQvqVdo/xYLgf911j9wM/FAe5nKkgqkFWvhbAQdf5iaYfdJp3jQ6pSRTGK12uxFaKMBhFrQjeOc5rbnDnSQ",
"part_6": "rY9WGfmOeUKkqAaXxJwi3nijK2gM8ZUlkH0fivmAROoiAadHY1o0QxbxF44cgo0fji4DM3Tglt5ZgwqjPtO/mq+cjbg/QSzU2ILuBea355Zu5cm645XiGJjGDiU/Z9o8c4hsl47HvXOsxgtu8w",
"part_7": "iyYwi6Z7Djdwt+8wivbWbg/R2zWnRu7WKQkh3AExljj7qrmzZ0rViLwrPRn0S9ZuStlcOSz387tad1OrG5B+YDkcjbbR0ptpoOI1jWKNBdVTZm4yk4RTUl/F6isKErZ0robXphac3oeJ9C25v4",
"part_8": "fYw6XuY0RjFujliV3FIURjckSxdU1h9MrHhTl0OVyGHwiDNOvf3YnwzgYPvEbRkNh7ZsTcajq69Nwle7lELpfI5RK5XCKXS+TbXCJbEBMsPgSPj4/t6Ezk/+xCSSRxDz6GgUWSBF0iHz4ngd3U",
"part_9": "mAQLSAJfymVXpCAki8+nXXTNprp5s2p7cmD/EsK/B3PCOAY2G5NA3g7nZHQMbnQG1u2JPM/BiiE6ikX28dvRohNo1PLoDHJziI/Cbe1vzHTeY9WOE4vHEJ8BNzmhtXOoRSeonSe0mx5L1p9opz",
"part_10": "A9ijUdw/QsmR1XxnwM87Pgoh47cHxsbO3fsQX9YU16LFif8r+D296wbno84v0ey14n2bTHVsY9pjk7MTHO49WfLOY9fi3o94K76zHH/+x4jXuUxeQrk+ej+6e7WTaSPzUYLOiPb/zyDwfSqq61FwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/6tWSi/KL81LiS8pKi3JULJSqo5RyswrKC0pjlGyUoiOUbJQMI+JyYtR0lGIUTJTMIWzTRRMsIobKVgiiSP0WihYwNmGUDWxIE5+aQmSdbqGcFVITBMDBROsEkhMFMsMFCwwFMXWKukoFZdU5qQCvVlUCqRqAfLvhKr+AAAA"
}
}
|
codegen__primeintellect___2137
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nNatasha's favourite numbers are $n$ and $1$, and Sasha's favourite numbers are $m$ and $-1$. One day Natasha and Sasha met and wrote down every possible array of length $n+m$ such that some $n$ of its elements are equal to $1$ and another $m$ elements are equal to $-1$. For each such array they counted its maximal prefix sum, probably an empty one which is equal to $0$ (in another words, if every nonempty prefix sum is less to zero, then it is considered equal to zero). Formally, denote as $f(a)$ the maximal prefix sum of an array $a_{1, \\ldots ,l}$ of length $l \\geq 0$. Then: \n\n$$f(a) = \\max (0, \\smash{\\displaystyle\\max_{1 \\leq i \\leq l}} \\sum_{j=1}^{i} a_j )$$\n\nNow they want to count the sum of maximal prefix sums for each such an array and they are asking you to help. As this sum can be very large, output it modulo $998\\: 244\\: 853$.\n\n\n-----Input-----\n\nThe only line contains two integers $n$ and $m$ ($0 \\le n,m \\le 2\\,000$).\n\n\n-----Output-----\n\nOutput the answer to the problem modulo $998\\: 244\\: 853$.\n\n\n-----Examples-----\nInput\n0 2\n\nOutput\n0\n\nInput\n2 0\n\nOutput\n2\n\nInput\n2 2\n\nOutput\n5\n\nInput\n2000 2000\n\nOutput\n674532367\n\n\n\n-----Note-----\n\nIn the first example the only possible array is [-1,-1], its maximal prefix sum is equal to $0$. \n\nIn the second example the only possible array is [1,1], its maximal prefix sum is equal to $2$. \n\nThere are $6$ possible arrays in the third example:\n\n[1,1,-1,-1], f([1,1,-1,-1]) = 2\n\n[1,-1,1,-1], f([1,-1,1,-1]) = 1\n\n[1,-1,-1,1], f([1,-1,-1,1]) = 1\n\n[-1,1,1,-1], f([-1,1,1,-1]) = 1\n\n[-1,1,-1,1], f([-1,1,-1,1]) = 0\n\n[-1,-1,1,1], f([-1,-1,1,1]) = 0\n\nSo the answer for the third example is $2+1+1+1+0+0 = 5$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACb8N2gC/+1a227jRhL9lYKg7Eox5XTzTmMnwD4kwLwkASZvluOhxZbELNnU8DKSYvjfc6pJXcZDBWM+7YM8gKXurj516tplYJ5HSVzHlapHd6PfyjRX73Wtskwt6pE1WjZ6UaeFftRxriCArVQnaje6C4LIGhVlukp1nD1uyiLfMMKHIvusqF4rWhZZVmxTvaJFkfAHZJ4ylVNT8YpFsLMq4zzndRbrVROvsLmv14W+m+u5/oWJr",
"part_2": "eN/V7SMPxdNmdaKdJM/qbKiuFQ01mOKdUJjObbMlw//LJ534jM5vqVftaIk3lOn5HSfclWb1bYsgJAUW03qsyr3tCmqKoUNQCtxs1hSpvSqXoPIDbCrZrGGXXFNVZG37CCS1hUp2K103dJQn5o4o7pg2kZPrAt4ozT8Lkgaxj8XJakYOoyilgMu7uHgBjFLjKo83qU5bm1KtUx3EM0t4/n4KdtDEynECdRh/HadAiatztSIMU1SfSS0Lc",
"part_3": "qksihddvZrXDPXT+B8P1NVxdf/UmVhMSMNJnywKHSVJqoEtaMOFpoaW8Ay21uUKM1ujisaLyfxdGwy42sr2JWg31o9jh+fpUXzeZYUsNnKXsbn0chwslKfSMBpv4POHXE2jQ0+vcMh4GkiGKDKEfLn+TxJq00W76t6nylzDgWMD5S0+8xeXvhCkz8+//lOvvzxnL5Q/PgnTcdjk6zFto3GNtY1W2qiYqzp6H9tFDL1y5geDOS0MGCcBnH",
"part_4": "1P66QfdEw7Fplm1v6Lzy+hosZeoFrT4pMiLK4XCmLiqbeNDWHIS+SJkNooyicz+/Idl3+CD1nfMus53rGP+81xM033oLPkCHIlyxFniCKdZxqKNwWlCLRVlxQx9pD0k7GwviItJW3X+z53BJCjKfnSn41pI5a2qVxUKyrLfIN1nVtwTSKb6P+0y7ON0jBDtdYMtcCFI46sORFd2STOD+yvzj64pZ3fgRziH+dC/iB6zm24wctn47RL8jn",
"part_5": "o5XvddsN07KqSbVczY5x8KuOgoDez6Q1kw/WhWJ+Xa+3dKakUohV8k1apPWtOuxOB5KCc5H7qD9+BVkhL4w65GR5JGB6OGuyDjYtJ2dLLkW7E5m12weRw5JF5Elk1rI+iJjlScRcOqGclq9ETiinJYuIg0h78yjSLY8iH4rznOUC/spy9uDYvpHmn7gRuOq1ScullXJG0TbNMi7bqk5My01MgVfroskSBAOFxhsl3pKs4SeYgwHZgvPu0",
"part_6": "G+q42t7qBnGKVXdlG088PSqWzzaiC2ipxf8hmuLchDK0qqe5PEGDb+2Wk6T6S26YIrP6XSuUX4QQ/Gh8FB0c72MFzV27uXDXKf68/kyUUvabCc7i/ZThJ3wA/+0fucF3hp4ZXI85B88K5M9/Yvk+ebp5oQ/vqfdlL7jTnAS2eFwxyevD/b0449HjZ0TANKyA+HJ7qCpO2wZs50zsmExxzLlVC4xjKgJXhhNN3DWzYkjG30bbzZKJxP+fp",
"part_7": "/irnwAnbSlM23lOv8cRLvlmTTopNPjlVzDKFQiP0oaMvm0Zb1FbT3WxaRqng4MUr1g7xyY8Qn98ANX0pllRpkR6ZS12vXifNlCzMhsd75sfY88Z80cXWEyfHfyimi9Yk8fXjuMJrluD4/uYpT79AFAB0ta6/DrsGEb381aV09bxYaa/PrapRDJ86S7eQeJ72nS6m6BZgcm05Pcd+9akzkPef0fElP6Esecm1pkiSkKydQHiqgu8SRi3dX",
"part_8": "ddfK9Tr7Xyfc6+V4n3+vke518/58m3wNINbq7H338+LF9ZOf6OgVfp+DrFDxkCuYSRCGNHqxRraoahTW6f56P6v1GzUcYOEamrh+7ih1h1hiZumoP+XkCgtlu3+pu3+y+WPTtUPyc9UHZQ6D6WXkDoI7PZR/g6d18M7C4YO4Az0l5wd5A+gPQyO0Fk2+H8kg6vViucMO3w/mCvKg/RwIpAydwBoDaAXVeeg0ahr4Qvue5QyLiuCRF1B8W",
"part_9": "HPqhkGKARwPPB64v+8Nt2wEcG70dNvIckkEU9FeNF/iR7TjOALo+xtz+PJfC8Xzf9geg2vCtJ8J+sq7wXMeTAzJBihC5IC7wjQIncoRtD+gh0o0otPtj5ruuJ4JgQNVHoUO+35+6kQyk7YTOAFiXi9buL1vHC0LPtp0hFRFFiFoU9nvBi/zIiSJhDwF2baTDBcZhJMLQCwb0ZxlGkqQd9TdDH4R9X3rhoN4AwoHdX2xhEErfDQJvUP4KQ",
"part_10": "tD7y81HBCLpyCG4doi6cC/UMYLqCscfkBMR2oP0o/5C9m0JW2xnQEo4IfnehZ6OWvRC3x/ghjBA2JwLD5rty1CEbjDkvY0cD12yn28gMGGEkT0EN0SDkN5Fwp4tPTe0h0wuF+chMXDAujD5HdS8tdOgcKMLby9eBowJ4aA64EDJKAguFJgvXN8ZRvgfXOqhHfj4UzUaAiyZsPT6gR3Xw9wkuk7zwP8ZpHpsdPqpUaO7umzUy98tlaEgTSIAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02QsQ7DIAxEfwV5zoAxGJxfKVGXVm2lKqkSGKoo/16qSHEmfCdz92CFxzzV8XYtcy1P6GHN8Bo/tSwZenPJgELBoMSY85ihMxliYIOW8TDYmiCHcsYdM9pkDSU6jBalQhIZZtZtEd+q0p48/K2pljMLs/VMVlGci9anU3lEjBQpaaPGcysQJAX37a7SYETXWDU9CAuJ2P09wwYdLOX7vrdfmms7th9qCpk+PQEAAA=="
}
}
|
codegen__primeintellect___2143
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nSereja is a coder and he likes to take part in Codesorfes rounds. However, Uzhland doesn't have good internet connection, so Sereja sometimes skips rounds.\n\nCodesorfes has rounds of two types: Div1 (for advanced coders) and Div2 (for beginner coders). Two rounds, Div1 and Div2, can go simultaneously, (Div1 round cannot be held without Div2) in all other cases the rounds don't overlap in time. Each round has a unique identifier — a positive integer. The rounds are sequentially (without gaps) numbered with identifiers by the starting time of the round. The identifiers of rounds that are run simultaneously are different by one, also the identifier of the Div1 round is always greater.\n\nSereja is a beginner coder, so he can take part only in rounds of Div2 type. At the moment he is taking part in a Div2 round, its identifier equals to x. Sereja remembers very well that he has taken part in exactly k rounds before this round. Also, he remembers all identifiers of the rounds he has taken part in and all identifiers of the rounds that went simultaneously with them. Sereja doesn't remember anything about the rounds he missed.\n\nSereja is wondering: what minimum and what maximum number of Div2 rounds could he have missed? Help him find these two numbers.\n\n\n-----Input-----\n\nThe first line contains two integers: x (1 ≤ x ≤ 4000) — the round Sereja is taking part in today, and k (0 ≤ k < 4000) — the number of rounds he took part in.\n\nNext k lines contain the descriptions of the rounds that Sereja took part in before. If Sereja took part in one of two simultaneous rounds, the corresponding line looks like: \"1 num_2 num_1\" (where num_2 is the identifier of this Div2 round, num_1 is the identifier of the Div1 round). It is guaranteed that num_1 - num_2 = 1. If Sereja took part in a usual Div2 round, then the corresponding line looks like: \"2 num\" (where num is the identifier of this Div2 round). It is guaranteed that the identifiers of all given rounds are less than x.\n\n\n-----Output-----\n\nPrint in a single line two integers — the minimum and the maximum number of rounds that Sereja could have missed.\n\n\n-----Examples-----\nInput\n3 2\n2 1\n2 2\n\nOutput\n0 0\nInput\n9 3\n1 2 3\n2 8\n1 4 5\n\nOutput\n2 3\nInput\n10 0\n\nOutput\n5 9\n\n\n-----Note-----\n\nIn the second sample we have unused identifiers of rounds 1, 6, 7. The minimum number of rounds Sereja could have missed equals to 2. In this case, the round with the identifier 1 will be a usual Div2 round and the round with identifier 6 will be synchronous with the Div1 round. \n\nThe maximum number of rounds equals 3. In this case all unused identifiers belong to usual Div2 rounds.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "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",
"part_2": "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",
"part_3": "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",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/11VS27dMAy8iuB1FhI/EpWr1EE3LdoCRVIk7y2KIHcv5RknL11IlvWhhsMh9br9eH66Pn77enm+Xn5u99vrvv16/HO9vOzbffmybzOKjX1/bMVyNHMk54R4kX5MyDwmNIpiJLVIO5aGH58ex2fy79iU245vWAnOYyGiBG5q+Cg2Ti3TgMWL4WqvsOWl4XDX0rFJtAhGrsV5UIsZoMCJlpfoMREwOLBsuNJqsQbnalGOrKjjhlEEjgWWogDw0ON31DJAQx/4VCzD+OhlAMWsZcJCG6XBZKPJNA5rHsVh3tf1+3ZX9q01ETiXJ+qJMElQstAsyeEl6XWFrVZ97Xe43gZwaSfrRkfTZ7rfaovVIb49PesDK75wEZgp3FXHVypPt2qrc+J0XBSi5NGyYXEGIuq2/MJ61JGNtDiojAmvvHo22OselKpl47pm8JUO5bxSa2MAcgTONE3mleNUfZsMZacSfDWMJXNBmAwySb6Ay2nEWcV4EbiYgsPee7ZBgYxsvLQuBFVxvJOZmjdVkD4yv4bi1m70dK5GhEusRr05iJ9jtc/pA+HITHMnVmeitZBgbqdnTgwZmtUxa23M7IJKZqBxx1IS2BUH+y2WU/HO61LjbJTB5GyPvjqmgmcu0GpnCqRjQceEGZP4CO/MogTD8pK2oCHp9eiATYQpLi2CKFmlWuuUfmO0xITSlTlWR6xD++qIda4mDJ+tBKEqBhUulYVHYsTqJknMCpZdJ9k6szNQ2lSNeBWSMkoMMl802pGkWJXeWMoWnAY8K6bMvRTrUmtQRL7AnScPzbKQ1OI3ZTlzGOkBaXEtqX4/oNxHvm4N1fefcWMsg3ZUfqxkJZbxX40992kOOHIUpY9ae1uJR/lUKmEeiG6fhPNdWkn66Xla2i5nDcoSxDqZYSQ/OMRCGudz1CA3BIXB0vHxEvL14Muybw/L36fr5eZZbSskIMJVkPZgzyyBRNYH/KYzx2CRiu35xCCBk6yPpYe37W57ufz9/T0f8edrft7+AedC1azcBwAA"
}
}
|
codegen__primeintellect___2144
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nIvan is going to sleep now and wants to set his alarm clock. There will be many necessary events tomorrow, the $i$-th of them will start during the $x_i$-th minute. Ivan doesn't want to skip any of the events, so he has to set his alarm clock in such a way that it rings during minutes $x_1, x_2, \\dots, x_n$, so he will be awake during each of these minutes (note that it does not matter if his alarm clock will ring during any other minute).\n\nIvan can choose two properties for the alarm clock — the first minute it will ring (let's denote it as $y$) and the interval between two consecutive signals (let's denote it by $p$). After the clock is set, it will ring during minutes $y, y + p, y + 2p, y + 3p$ and so on.\n\nIvan can choose any minute as the first one, but he cannot choose any arbitrary value of $p$. He has to pick it among the given values $p_1, p_2, \\dots, p_m$ (his phone does not support any other options for this setting).\n\nSo Ivan has to choose the first minute $y$ when the alarm clock should start ringing and the interval between two consecutive signals $p_j$ in such a way that it will ring during all given minutes $x_1, x_2, \\dots, x_n$ (and it does not matter if his alarm clock will ring in any other minutes).\n\nYour task is to tell the first minute $y$ and the index $j$ such that if Ivan sets his alarm clock with properties $y$ and $p_j$ it will ring during all given minutes $x_1, x_2, \\dots, x_n$ or say that it is impossible to choose such values of the given properties. If there are multiple answers, you can print any.\n\n\n-----Input-----\n\nThe first line of the input contains two integers $n$ and $m$ ($2 \\le n \\le 3 \\cdot 10^5, 1 \\le m \\le 3 \\cdot 10^5$) — the number of events and the number of possible settings for the interval between signals.\n\nThe second line of the input contains $n$ integers $x_1, x_2, \\dots, x_n$ ($1 \\le x_i \\le 10^{18}$), where $x_i$ is the minute when $i$-th event starts. It is guaranteed that all $x_i$ are given in increasing order (i. e. the condition $x_1 < x_2 < \\dots < x_n$ holds).\n\nThe third line of the input contains $m$ integers $p_1, p_2, \\dots, p_m$ ($1 \\le p_j \\le 10^{18}$), where $p_j$ is the $j$-th option for the interval between two consecutive signals.\n\n\n-----Output-----\n\nIf it's impossible to choose such values $y$ and $j$ so all constraints are satisfied, print \"NO\" in the first line.\n\nOtherwise print \"YES\" in the first line. Then print two integers $y$ ($1 \\le y \\le 10^{18}$) and $j$ ($1 \\le j \\le m$) in the second line, where $y$ is the first minute Ivan's alarm clock should start ringing and $j$ is the index of the option for the interval between two consecutive signals (options are numbered from $1$ to $m$ in the order they are given input). These values should be chosen in such a way that the alarm clock will ring during all given minutes $x_1, x_2, \\dots, x_n$. If there are multiple answers, you can print any.\n\n\n-----Examples-----\nInput\n3 5\n3 12 18\n2 6 5 3 3\n\nOutput\nYES\n3 4\n\nInput\n4 2\n1 5 17 19\n4 5\n\nOutput\nNO\n\nInput\n4 2\n1 5 17 19\n2 1\n\nOutput\nYES\n1 1\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "H4sIACb8N2gC/+1a3W7bNhR+lQNBRWxUNSL5P2gudlFgvWkLtBct4ixVLNrmKpGaSNURigJ7iD3hnmTnkJStOHHSuiqwYVaT6I86f9/3HZJAv3hJrGPFtHfmvSl4xl4KzdKUzbUXeItSzDWX4krEGcMB+IiLhN14Z+PJOPBkwZdcxOlVXsgsJwtvZfqZgV4xWMg0lWsuljCXCZ1wzHXKMigV3dEQfLIs4iyj+zQWyzJe4sNKr6Q4m4mZePk5FsAVLKX5QoJKGctByDXEIo",
"part_2": "F1LLQyj5mGFY6L07jIYJ7K+acevFuxgsGapylcM8hiUYFgc6ZUXFTAPjP7bSaLQq4DE47P/Wd6BXJBd5n9VOm40JCURR2zf3Nlh2HUpWY9MEEmkilxok1IJqJPPAdyaY05fwEoCXi3iveFDVyAKucriNFUhZ/GGrgG8q7qKKxjRZGEAdxcRQHMZokk8zdXwq+d1JnH6/gTq79l8bxOULGNpY6Qmm2cUS5YY40105oVwBd3ojS2jUFn16SKRgtns9vb4Den35WU6E+vJWGe",
"part_3": "s0Jz9LGQhSlO0/Lff/5l2cMLpZ0xCmrrsZMyfYLFYCZofIXF9Cu/ayhBn3Lkb/E5puT1mjFh3M6lUGxeao7sVHyJnFV3LV1X4Od+twe/LChxMuZQUQRWcDuQXTiqACp4Crk9Re7cz30TGYIixb1Vodq5RIkXm+SlYAFcl5rAxOGESOOLuLjmuiAuY6olI1Ax9h78uqFXzilyrE8mHXeXmL2w4zHenOiTN+mTX2U+dAjsHCXItkxQZZ5L1MEWZplTW6gxtPXRWA4L/FtpZe",
"part_4": "EiqeHfxRVhg/WKENphgVrJMk2c+KjKlmPfiS9m+Lu/R1F3GYz3tj6P6As6FMj36gSj2NWIsrX6IEssYawMy7BY1HzvL9W2ANiBwcfcTGI2pYWtOMKg7gkD+1VDeLUxV6Afqgbirxp1Rc88y6VSHHt9A3sTqWOe64nW/jYsbKXmBXbtGH+zMtU8T4ntas0K9FfJ0ugmxxANF039ZuIZHS9FXmpzRY/ebeqXcsFqj5zGEFV0zJG7xBsi0xKtgy9cTUgCfoRJomthT308zTFn",
"part_5": "CE9/GwYQ2qfZPS+xDdUdTJTZNQllUU82NXzbF5s6OfFsW+IdjjtO9+rkkOwS7T2QHSW0zW4fl32XDM5q9gKz+BJOvvrdgKRZuAnPcHNVzxhWtG66NNlZqRKEhgI4kxc4EzKWWGIQnawdQtYCz+lnXrDYLAdkkWBNOrwHOKWaxovpceoxJnZ4TsHjXxu9ucXwVzJNnIyoKNiIiodrkjVrsq8B1jVBdeyriRWOrQkK0SwbTEfcj+CeLtXk8OtSN0mMcuA0QT0qqI2eqSVIU2",
"part_6": "3yhNMDN8TDiFWsuVpwlgROPjPv1euZRyjoW1ox8bwmGa65YpvBH168vXc0LbNqRd7WU9WoZLVTx020mxGu0hm+c04aDN+UvdoU/VZzpM53or5tBvG3wNk+6phyIHzQqWdCqrKVNrJ+geth8EOfALOks04My/GquiUEBL1rKokFd5C6+HH9hngrK5fdaWx31jy8i/9Y631xE2c4Wjnimk48E30Y0p8wgnAyExGMYIi9sm/oZXiOUx+SCocMDNntVwOIZiLEoeEYwindD5tf",
"part_7": "IGf3j0VPd6yH9tm7TS+ol8VKJ2ZOTkxurtw2vYpmZCXT0jCCFuo6kWSR/r3CzYfabHLqPQ3ZKZguC+GaV8J6uFcq2AJrKua0dSIVIxdVpWbChHKOlz0TRg+7YEJEJwcJW8BynnRugqqLuyDAAyf36vz81N3R4XzdbN7fPK8ar/Hb8ypwb91YsonPnlRd8iKC7DyL8w7mG5hoOt2eylOOZ3z//jzlSnf2DcARbx4dkZy/vwgvn72/OL2cCZIVJw7jtLBknSgQdW7JOQWWBO",
"part_8": "8vOA3mz8LLrhsf5PQFQ1GxItas86ZRj+RJfrsiBrrOCYJ+0t19SjEE/GnYeHGNJf80EyxVzBlxBl69PukiciYRRM30ULx3QB93uMcd7nGHe9zhHne4xx3ucYd73OEed7jHHe5xh3vc4f5vd7i1EeWdXXgfP360exvc4R53u/+V3e5MIG7eZeChfDTi6F18mXm6ytnMO8O+aDC7cgTxUFWeSd++JAlsNdAUAZbdDJaWq2Y08dXKgd5+DeDbHZESmlKwurnPCQqoBeuktP0p",
"part_9": "hO7tdzmxJiOgOj1kPDrceAhTd0xO3UGJ1Q+nPyel4enugfPgnYMGjsb40xpqLueG2+iWu/DW3d7Em2EfXvj7M77ztPXs95W6NT9942cMEbkis5NB6wgicHtjrlE6HJwRhCPS1QPmRz8APUZGkU9bR3b8SNA/IlkI6TRokSUD05OjIQz7hi8DGMPggegHh0Q/MDPLCCYwmcDUlX8IUYszAcU8gWh0Cv0IJ7KIUJhSLg/OCJNDJrXISeuxGWF8SKmGplSGnRD28XeAl4ORAX",
"part_10": "9kXLbJ1inaprm9ZUIhEA7nCCGYQnuEHTqRDXAJQ/MVdoDQELdtwQ0dZSMjjj7aiGxTGkLbLSMKB+PBpD8aYNnc5fD0kSbS+OZgPU5QJjDG/AaRyWy8h161VA5yZOHqo/Ew2pvTYUywDSscIjYjnO5GeD2yi8AIpj9Nl2OkeL9P1KM/YxsE6ui0xWYW2oUyaafVmtVr2eHPWctG37Ok2rvcbDPVb17jjn9SAOG/xF/UOjvrfvGw5Uv6r8fqqhT8j5J5Z7oo2dd/ADm3w667LAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/41RwQrCMAz9lZDzDmubrnV3r3rwJFa8KCrIJlt7kLF/N61sTCdiIW14eX19STs8N3WojgffBH/BEjuH1+oefOuwhJ1DCcK5SgoyZFVBFoZU5xHncJjBwBMg8tmK+CdmxosaVCKA0CAUB3FKBWMaCrBznlFASvFDRdxMRA0sOB2plLwQaODCN5c5yMjWI64Sbrg51omwpYmaTJ2xNQMi6SW2w30s18FPxrVdbt7HJUad1fr/9CUTh/KjOrjoMcPWP24n/r4m8NE/AR4fAgDWAQAA"
}
}
|
codegen__primeintellect___2148
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nIlya got tired of sports programming, left university and got a job in the subway. He was given the task to determine the escalator load factor. \n\nLet's assume that n people stand in the queue for the escalator. At each second one of the two following possibilities takes place: either the first person in the queue enters the escalator with probability p, or the first person in the queue doesn't move with probability (1 - p), paralyzed by his fear of escalators and making the whole queue wait behind him.\n\nFormally speaking, the i-th person in the queue cannot enter the escalator until people with indices from 1 to i - 1 inclusive enter it. In one second only one person can enter the escalator. The escalator is infinite, so if a person enters it, he never leaves it, that is he will be standing on the escalator at any following second. Ilya needs to count the expected value of the number of people standing on the escalator after t seconds. \n\nYour task is to help him solve this complicated task.\n\n\n-----Input-----\n\nThe first line of the input contains three numbers n, p, t (1 ≤ n, t ≤ 2000, 0 ≤ p ≤ 1). Numbers n and t are integers, number p is real, given with exactly two digits after the decimal point.\n\n\n-----Output-----\n\nPrint a single real number — the expected number of people who will be standing on the escalator after t seconds. The absolute or relative error mustn't exceed 10^{ - 6}.\n\n\n-----Examples-----\nInput\n1 0.50 1\n\nOutput\n0.5\n\nInput\n1 0.50 4\n\nOutput\n0.9375\n\nInput\n4 0.20 2\n\nOutput\n0.4\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.625
| 0.625
|
{
"part_1": "H4sIACb8N2gC/+1ZXY/buhH9KwO/XDvXUUR9a4EU6EOLBihuC/S+FOttwpXpXTYyqUjU7rpBgL72vT+hv+z+kp6hbF97I6e93kUfilUAr0gN53DmnBkSyOfJUjrZKTe5mPyx1Wv1zjhV16pyk/lk1ZvKaWveG7lWMMCUNkv1MLnIy3A+sa2+0UbW75vWrhv28Cdb3ylyt4pWtq7tvTY3VNkl/4HNda3W1Hc8YhPM",
"part_2": "3LRyveZxLc1NL28wuXG31lwszMK8qzeSbqwjp1u1JLuirrGt6w4XzqlWK0e90Xeq7bTbkDRLv0jSX+01aeOhuv76Xm4C+p2ie9nRDayHDwj9IzlLS+VUC4fD5lVXyVo621Jt5ZJWssJ7QLyp3yv3XUey6/o120pHhhplmxogjrG3iJ961XMW2mOHAf3akZLVLXWqsjC3gERkfi/39iBtje06fa1r7bTqsM+P+G1q",
"part_3": "WakLUhrmg+OVbjuHDbSdNcfQCjy23aNw7rHSMyG95w01c7L/ydPSqs5852htwe1XHqaCXlMzm1MjW1lv/gamrjd0qztaKdlybHv4zpOzlh93Cri/tfUO5V5qR9fqFgLD6nXAyf6tbdeyrjcgXvlVc79Mv+Y9jOy0ksaAeh/6o8h743S9Y8oHASBdIakriJcEi0AjEoH5qoZI77YpJO0Cemc8UXvOsCUeb/cA2DHM",
"part_4": "gH482gJSos1KG+3UnDrArSDSrYstW9rNCWuMgpqhbHmnhjkvNKznnOm6Rp4GtXEirXkUKkyl2RxIadg2ouCCMkotO462ssjJsPShQb2DuDtZ93s5mn59rTyBh/oeR1z54LdA3VApf7Z9O9SX9ni3qm6YWYQ+NAlMV+gbta4kg7OpZ31hXvPzzjS982889eNeorX+uWQ028CLcVIbFnurdhvvyMxZ3o4V+tM//sVD",
"part_5": "51+iMAznFPr3xv+KWUA/7FZ5kSKFLbt36gaT810yGo6lVbKeb3uIV5J6QIOAJLiAl2iJaFHbjGCLS1VpiBj1DG+H8f2hd4cBovka7lrcHpFsBtmh/vT3fx7z9BU1KKT/RhiPaeKkymvw0TvFfaBVMPTKb1sM133nuPDVQwXRkAj/8hkVkn05jOI3DxIUqm4bhydtYQSFQRqSYLMhzoXBjO/qRxbJsUUZ54dGCYyi",
"part_6": "kKJjo2Snh4H9n+NG1J68je2pu7V9vUSn4qxuWIo+TM1JsWxr2Rn/+8He7yWp9scU+2mV69shiTjEVIDjr1Ur1SpT8Wko6e2wheks6CBj/F0Y4yfdVF6GVxg2GK5wiPCE4Am3/x7xcKl4gQhDevWK3GDfojCX04Ze+fnvSajXJUw/bQ3RbQFTtRheCn/CaO6CLU5QNYW2xexqYR5NC9Y+PM1wsNL2gYtLfQUv/oVb",
"part_7": "3xUgpw5v2tvSmzekF0aisN5S+JVPD3Xgj+2+f0s4RKcaBTODsy0EvDYcn+a56Sd+HWBmM26Cjn6FnJCqO8Uw7OfNW9QNuPH0TTEzQ+59jpF316LYMd5S9XLteLl2vFw7Xq4dL9eOl2vH/+u1Y+ekm1xcTj58+DAcVzgrX64g/7srCLOG3E+u5hOnOgcuJpefFxO3adRickGLiZfC+y3JkzlmPDfDx7024cZ/s4Oy",
"part_8": "/Ef+dPR4qy9z+sX+kxP+WeJP8r8vinH/yVP3z+0REJnwjXIURUSiDMqDJ03SMxIFHBHgJzoFE4ZB+NRwEpEzITnlyXjKEpEEYZ4kSSSSKMxEnojzYsFmBaXxKV3FTwwkHiBSStNRiCg4ElZ4ThTJgBGdpCQ+oh3P2fpCrqI4ORFJnDxDEYbfUHC4j6MQcRadI9+Bj7LkRjwOEpXHVVIU2Rn6HWAyEnk6nq7kUZmI",
"part_9": "XJzNShlzOKMwZXxcjCI5q0w8Cgo/j8crpSyfo7UMjWW8x4unNxWfrV3vOkF++Bzda1cs4bek/Gwo4lvhPIJJztdY+Y2TpSyeIZ4s5UMyy2nXoB7DZGkUFDjEolREWRSmRRGfIbI4AkqcUJSMC60QqKedjvM8E2eUf1lwKAJdJs1O9P0yD+LDzh+dEUsSl4ApYsrLcWJg8HRe0pRRyoh7TDYKk6bFUfXn+RnBFAUf",
"part_10": "+RnnrByHQSd+epOJBJ8yeUFxPq4yGDxDzjwzEHSZjzOTRlGQpGVUZhBYGMdxkZxTMZ6ZnIQoshMlcyyAJD0jZZ6YMmUxj/OSP/2MSUTKtES48OUnLnzpM7SYoWBw0Ih0nJcsPpYyEnhGwkSxvWQkeXSiyRTPcAAkGcMUlJy4JOOGdHzz2+7mlzGTc/vPEyqScfphcHyT2fF/xf/h3b3vjf7Uq8mFa3v15d8aHKXmMR8AAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/3WRwQ6DIAyGX4X0bAgVUeurDLPLlm3JoovCYTG++4pxCsvsAchf/vajTHAbet9dzm7w7g4NTBYe3cu70UIjThZypZRQkkiEk7WdhUysMkpeEhn5quHEJpSGgrsSiHW5qXqpqYwwZrfqnDVdiLzAqN7SA3+cTIPftm2Qe+8iZqSaq6eRkB8mA/3/DD8kcRURei6rxLbj1ihJ0xpVVeI+AzwmJJIURb1Orp0hg9G9n1f+p8HzNn8ADMjJE78BAAA="
}
}
|
codegen__primeintellect___2150
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThere are n cards (n is even) in the deck. Each card has a positive integer written on it. n / 2 people will play new card game. At the beginning of the game each player gets two cards, each card is given to exactly one player. \n\nFind the way to distribute cards such that the sum of values written of the cards will be equal for each player. It is guaranteed that it is always possible.\n\n\n-----Input-----\n\nThe first line of the input contains integer n (2 ≤ n ≤ 100) — the number of cards in the deck. It is guaranteed that n is even.\n\nThe second line contains the sequence of n positive integers a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 100), where a_{i} is equal to the number written on the i-th card.\n\n\n-----Output-----\n\nPrint n / 2 pairs of integers, the i-th pair denote the cards that should be given to the i-th player. Each card should be given to exactly one player. Cards are numbered in the order they appear in the input.\n\nIt is guaranteed that solution exists. If there are several correct answers, you are allowed to print any of them.\n\n\n-----Examples-----\nInput\n6\n1 5 7 4 4 3\n\nOutput\n1 3\n6 2\n4 5\n\nInput\n4\n10 10 10 10\n\nOutput\n1 2\n3 4\n\n\n\n-----Note-----\n\nIn the first sample, cards are distributed in such a way that each player has the sum of numbers written on his cards equal to 8. \n\nIn the second sample, all values a_{i} are equal. Thus, any distribution is acceptable.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.0625
| 0.3125
|
{
"part_1": "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",
"part_2": "9/+Zd/5TPT/uGj3CMj6Ox/5dnTcz3g4GqeynaUl97qXA6vp7nECON0wxlOvwGGLPiDv5S/wqW7urrCdz9Pv7g3nvOUH5a/HGZ86Z4UkbyKCdC84rGjVRwBjfb4aqdIODbkP+x3x5aUsJt2MyQXYlJMdZ7f5fMw+EysMq1345GvaY/t/Xq/uoXLD2h7fsy8/hwjJ+4+hc2/4/iMP65NjG+uWW9uZany3We3eHwcF5v5A7qfSz3tt+16tQehyPsE5FtxL2FjYb4Vj27EojfrzUYIyC2m7RNN8Hm95w0LcArGWgt5wGiL6bMh7+HYwH/4afEgkb01ExO411O5nrzLrrokvyNuVkfgsvxYXLieksucvT6R5KPBzf/9+gm5ObqkL7XX/lE8c/Dqt2oRDZEt53NpLsNSnoOcVmWIL5QBYKhjdgGlHQW+OmN7jLR7MbUOfYBkU26xWVh0zNMQO878oWDGjPjolfvufi8Wh2EPU4TDQA03N+PjbjGzwneHcJ/pZrsTppdHb+kwQ5k6Si5snr0v85N71zAkfv9x/YTPLHPMiQLjbMbdfqNLkDQyXkkC2oyfBC8S0JJuJve3CJQ3nMabt2+vp2/kykrm/eZh8SiXd5fOPrvaPq6WuEduAiEuYXXB5t34Znor6cbJr2/eL7+X59/jqzz4N/57GfBqu97Ic799",
"part_3": "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",
"part_4": "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",
"part_5": "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",
"part_6": "nRIJiMHqIqat+UPBC0M80Wk0VVszKFsZo/qc/Aalode/WgshO928wDSWkbWnX4ck9olVtNNCWyZSSLJvtamKsDKAOpJxGwyOTQ3tStlIyV2ZscjSlFXERpwwoOddCAQTJToKw9sjLKlABRfdIRD4XBR8OecEk54J16HQzcrZqnRdIsPC2Jq2WtlglaikezoiYumT+tOXtjUGuGpl6DUGkaJuQeEGg1LxLDXgO3qHO7snrS5oEsJFlzI87hegY5sVEB43aoBs1ygQUpoQZM18AkOUASoKPBzzv1RKWGLBQcrDc7nOMpLTzZLTOeyKr4vOi9FS7BDa5Smna7G6UVsrNSmaeHg1nvRHqwfJesrkzRatbBWaGl5ZAarpuxB3OcV5pLKryC+ZeEoCZRiadNlDTnmqrZpVhlqQIX+dGKZPoCSS1r8exND1rfivVrtPp1DloLMnRd0pd7UFtRFYYLjDBtZCDjgqIRJ2yMkfrIc40lAGV/YumVmOWL2t9T/Dc6nA0JFGYZT8tIfI1n8HkmLTIOOr0Dk32kOALdIpQz5VY18SBuCexJnKZEhHdQgNN4c32MqnHQ3kJSJ3utN+jGqIrRRFQyxZ0sd8EUpqayagNW9FBG3pRrVa8yaYB1quarbI3NWZNpJVbo7qCMELq194JGZFEBnLUHgniw5iWpNJ9HoexE",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2151
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nWe consider a positive integer perfect, if and only if the sum of its digits is exactly $10$. Given a positive integer $k$, your task is to find the $k$-th smallest perfect positive integer.\n\n\n-----Input-----\n\nA single line with a positive integer $k$ ($1 \\leq k \\leq 10\\,000$).\n\n\n-----Output-----\n\nA single number, denoting the $k$-th smallest perfect integer.\n\n\n-----Examples-----\nInput\n1\n\nOutput\n19\n\nInput\n2\n\nOutput\n28\n\n\n\n-----Note-----\n\nThe first perfect integer is $19$ and the second one is $28$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5625
|
{
"part_1": "H4sIACb8N2gC/+1YS4/bNhD+K4Tqg5zahkg9/AB66KEockkLtEAPK2NXa1FewhKpSFTXiyD/Pd9IdrJoJKDmrcXSB4nD4cd5fDMU/MnLM5u10no77/dGVfK9trIs5cF6C6/o9MEqo+91",
"part_2": "VkkoQKR0Ls/ebr1NFp5p1FHprLyvG1PVhPCHKf+WzD5JVpiyNM9KH9nB5PSAzmMpK9a1NCMVSI5NVlU0LzN97LIjhC/2yehdqlP9l8Re3apcNixjtWmVVUBXMPAIUS2bAmYumCpYpnNm",
"part_3": "dPlC7wTddhUzBVO2ZTlsxEO1TJ6zg4XOjAezFfsVWHoMd3aaLdiL6RqGuJxoozWsgN89MlaX9om1VYYgtfZqxXcwK/Ig1Usa73Xd2f6NRD8zikApWam0ZM8KaONWMH/GWZqW8iM7XZ48",
"part_4": "SNNFEASz+Wv83zo7eoDuqkfZLFgutbHXqE85MGL3L+esqqF0Qe7dSDWn9eFITLY0u6yI1ytiMyBdsD4YK79a+CcRRDXfn07RnvHtrE9on0gJClBuZb8kNrPVFUDRoYhfWbJHKFqwrN+G",
"part_5": "1LH2yXRlDoYBd8hla8qOqEzJhK4hE+n3wTzT2oW1V5ISTiNt1+heDArLFcjfyEI2Uh+oFgpwHgt9qQAXDKtq01gEu8i6EtYccMKJ/USu+b2t/nxOJ+aQvVLyS9XafqEw8B/qrEExSJ8H",
"part_6": "c5QBw8jvfA6az/errK6lzn3V61dnIIERun6mlwEAdG+/YYgFq85XGKi9GzbQjJTb6tVx/Kp3XT10TTNmzmsdUIxUYCEdvISZbbWkjfP9P7QvjpAaKX1zpj/nHYz7sUfrXbvQooVfLYIq",
"part_7": "cx9bqzPhw449dH7oc+uXUvtXZQrvIL1K7k5Lvp8jcW1dKupPtsmUxvyS57eO9dax/t8d6wrSers77+HhYSArWsVb9/qPdC8CROK8/cKzYD8S6d19Sj37UsvU27HU63l0f2GIt4Ckz9ew",
"part_8": "yFPs74VmYPkg3fbizwv275HEKBJq5mYkHo4bFSYOWMGEh1EoXNDEhG1BINbB7YBbjAnADZoiD1xsxJjG5IEDpgjDcb9DwCUufvNwym8eRk5+bzfxFGQkRHDhwU2Q8XazHme1EFy4IE5E",
"part_9": "cX07UjSKFDmUSDyKFMe3I40Hax06JHMUactdymGCFA4tjo+HiseRQ9TH+1LCXaI1QfyIRy7ddzPF+cipc4zTK4gdajxJknHb1k5tjYtwvIw4Gn3gUEphnKwn6BaGQeCQ2iiKJkiHFhQ6",
"part_10": "NbVkM04XwXmEa8wpK8nU7YDG68CaNcY4bRBF4ZLqDcbUhUN3mEMgtxGf+LYIBI+crIzjcCo3MNOlmhMxcSuKmHPHb4GJSzEEJYVLauKpvoqKCb56vac/F9v7TquPnfR2tunk5y9CoBVInRQAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02QzwrDMAjGX6V47kFjSf+8yiy7bGyDkY40OYzSd68dLNGL/j70U9zgEZccbtcUc3rCBJvAK3xyWgWm5iIwaIgEgbYRcMxcYCQeCxBqVHLcFeirXIe99796PmHJyWwkJHXzVHr5RGOOxB2SFQZUNgKhQ18PYHNBlV3/n5l3aGFN3/ddHxCzpv0AU/E0QRgBAAA="
}
}
|
codegen__primeintellect___2156
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVasya has an array of integers of length n.\n\nVasya performs the following operations on the array: on each step he finds the longest segment of consecutive equal integers (the leftmost, if there are several such segments) and removes it. For example, if Vasya's array is [13, 13, 7, 7, 7, 2, 2, 2], then after one operation it becomes [13, 13, 2, 2, 2].\n\nCompute the number of operations Vasya should make until the array becomes empty, i.e. Vasya removes all elements from it.\n\n\n-----Input-----\n\nThe first line contains a single integer n (1 ≤ n ≤ 200 000) — the length of the array.\n\nThe second line contains a sequence a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 10^9) — Vasya's array.\n\n\n-----Output-----\n\nPrint the number of operations Vasya should make to remove all elements from the array.\n\n\n-----Examples-----\nInput\n4\n2 5 5 2\n\nOutput\n2\n\nInput\n5\n6 3 4 1 5\n\nOutput\n5\n\nInput\n8\n4 4 4 2 2 100 100 100\n\nOutput\n3\n\nInput\n6\n10 10 50 10 50 50\n\nOutput\n4\n\n\n\n-----Note-----\n\nIn the first example, at first Vasya removes two fives at the second and third positions. The array becomes [2, 2]. In the second operation Vasya removes two twos at the first and second positions. After that the array becomes empty.\n\nIn the second example Vasya has to perform five operations to make the array empty. In each of them he removes the first element from the array.\n\nIn the third example Vasya needs three operations. In the first operation he removes all integers 4, in the second — all integers 100, in the third — all integers 2.\n\nIn the fourth example in the first operation Vasya removes the first two integers 10. After that the array becomes [50, 10, 50, 50]. Then in the second operation Vasya removes the two rightmost integers 50, so that the array becomes [50, 10]. In the third operation he removes the remaining 50, and the array becomes [10] after that. In the last, fourth operation he removes the only remaining 10. The array is empty after that.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACb8N2gC/+1ay27jyBX9lQttIqdlQXyJlBEPEAQJ0JvJABnMRnLcbLlkEU0VaT6622g0kG32+YT5svmSnHur+JBE94w1WgSILIqquu9X3aoC/GX0EFdxqarRzeiHItmpt7pSaarW1Wgy2tR6XSWZvtfxToEAoEQ/qM+jm2jmTkZZkTwmOk7v8yLb5SzhH1n6UVG1VbTJ0jT7lOhHWmcP/AOa96naUV3yjEkAeSzi3Y7naawf6/gRwOdqm+mblV7pn+LyOaZtXFKsKS6K+JmyDS",
"part_2": "Ww71EVJY9TpR+rLelpR56rYpMVu/LAiAzwmF0BnxacCLzhmYrXWyorlROzwEHDnGb6UZUVlepxp3TF+tbgV+u6SuCkeqrjtLNmLCxqU+2ysppQsmEZBatRkPAR2lMqa1ZkxJVX8OqBCrXLPqqSkmpKf8sKUp/jXZ4qESAO/aG0riclLR1vQvwNm8c1z92EtSFIm0oVcEl1/kIyvVfrbKd6/A2bxO0vyF1dmazpeveeJWz6ATOBLbdZnT7QLv6gqNZVknZRbBUoVMEzbJ+qqeVq/IvT",
"part_3": "lBTSz57TBuXCHrP2lb7mv7caNsiIQT9KIgoEP03gDMJexQksgRVIZqqasJOmsUO//PtnDPjtzmY0m82u6Jd//cfk0BRItumMnTYKkMkMGTjSgMQqvQb1vTPBC4GaTqc8+qK/NuowSb7KyJn9c2H07aWr79vf66rvHFYZqukV0a4yG8aBKO67ZRX+1RRRaVVKbFfaX2mXAnxcJjRGAcQTSxGs9Jw88smhoE8T9GgiCCL+uPg4iLf99um9Hv18pR0moKB5B3u0vrHbWv59Vqk2UG/NQj",
"part_4": "WF0C6MuLKQ/QKrPmWAS6mZ4Nr08iKrtknxQHlWJhLiKf14VLlLsx7I6rTM3So6VoZvq8sYxKosY0/Xn2VNVltLOrBgpj1nLb/1lroWiCKwrU3c7FcMUKZOWvFGLDsjvc2U/47bW+tBF1hTT0PlZG0y4ds3SSslbbJQfVPa+BnRXfh6mrmG267po1nsOc4LaY8CpdXSGEOOSNy+sZusLrDiG2uTYXsO0tlScGJ7qn8le8sAtjn4BvK9k8LSBx59Symrwx66lU2jU8ziyuxXtHbFasIy",
"part_5": "GOzKjNHaeBNkRrMejmRCnt09WGsrOo15M7MxfVFDptPnnhqOW7fCElvlffFNC064R9CnBNl8j4BVOCiIgc9Z3XTAXLolAAVCktaiHgUP2ozbB3++zz4xzh48mnOG2V2rujCe4BSipji/FGqDbRn9HacVKfnyGbvvLs+Kyhiw0gLeqjh/ahA8ybN8YgZ1uTWjZPO8wnFoQ+z5+AqHFsKfpltO5VikTQsVP/AWM766MugY6EPUtMzTpBpbiidQLO/MOMd4ZobrbpgyBTL2RxprekOOZS",
"part_6": "yGwR+GwXk8DEePoWRCn7mOFbYoTroax417/IfDyWe6vaV4md/1wMbKN7fkdDCVluqAJAUXVOd03ScUSw3mwzK5dniw3kfnscEnx5xAWZ58H1E08GQf/jRFJpV+GI+v1xPKm+y08o45OP5W6wvMx461Duk9hxpHdEcJkN5zoGjm2sxtwY2fmjpC528L4tM2SeW0A3Qv2mwciGz5tqyNN9frvZSKsd/R+jCjOBslulYdlFXvZzllW9j9DlQwqFiKq3d7ekD8HSw3K7SkP5FZ9PEyLe9M",
"part_7": "VRXlYVnptYSRKd7gFwQH+HRCmus/FzET/j0iQhpSm47irpV3a+RxpI/rzRDq9BghknSxj2j6w/hpQuNrjfjrtF9aA6uhC8gBwhSBsbAoj5hM5AZ4UutNanlMBx0jaTDEdCr0Qek46IFVAQjmtm1e7nCXO9zlDne5w13ucJc73OUOd7nD/U/e4Roh5ehmOXr37p05b9iL2+U+d7nPXe5zl/vc/9N9bqXRBUd3k1GFyw664mj5ZTWqnnO1Gt3QaiTt6d6229EEEGnaBumvujMlOrGgM3",
"part_8": "OwE7yBfp3QbxcZrPqH0CGhweuFRquXTq1DCrzXK5ivho65Q8L91wt3WPigMOcEYeK0H9Dl+W3P2QIvJTI7lzheWs6LJeyeLPCs9n1jkZ0g0jMWns/GRqB3rhh6TVJesNE7VWRA87MKnHF/nZ1ZJEs9VyR9Wz4+BdgNvHO1UhFrNoGzWkpnLSMWGdDLpe6e1n38c65tF2E860L0I8LjnK2CpLznC+o/jsfvUF6DeuYnBIP1OEhXQKFZ+/jhUUALj9/NccNi2+8+5oV95oQa92SnCal9",
"part_9": "3EU3WDgdpD8+oDx+gGqww5aeUueS95lNTgiL5OwU8cz1MMMw4KhJ7mYUCZHQyVzYQONL7wGH4WYsiGSEXwM0ZMILMf4LvS864cDKKfJ8CpFvMcIPpc4i8jDwyVtwXfsO+fbkibmgDR3eQM/lsAHD0O2iOc1hvUtRSJEjU5D5xnBXADyYsRg80OL6PAhFHQNdWiAGLvkLHrjhS+4Gp5x0eYmECOyCxfsygJUGEjbTFnUwYH8arL84HBs5BmjeYW8wOPb39VpFYSM27IAtWaNxuAJOWH",
"part_10": "ARRzeacWKQ7IBLDdmZI2/YE1wpDI8hQchvRjmcbawlcHAGHaZBHiFj4Uq5kxNJqpmTQUJh5XuS0YDzbcQ5zAh1qCYQYsHAAAw8GYeebUMRqozNQUWIHFSX/M6ZO5Kz7pzfqGBW4YkbvowjRjF9NBizMDr1GgLff+fHP8Mn/L2fc52jFu3pBClvfs8l3HHbgwrKHy3FPGhHXsQPWpA77En4emXM4kkJyjmBS3Mxx3Ouc5w5cTZ/JDur/ftWvO74n5DL+1onT7Ua3VRFrb7+Fypfwu3FLAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/41RSW7DMAz8yoDnHLRQW75SBb20aAsUTuHIhyDI30tKsdPkVG0ekkMPKV3oYz4u09trm5f2SXu6VPqafpZ2qrTHSyVb68SyK+1QKasFnU6mNWbdG8MLssP76DOSZJ94Zh3oKbexcYIKe0YKKAbOgxOsR8zwAhi+gDPYgm+1iN3DgyenhGMAB+SCEJEjYkJwyAnZdlNojKJx1x0KjP5Glqg4VpC6nDodSkFx4KLAicK9XB4tSZ8i5f3mj6N9WWE9w8g6aPi4tKf7vt/Qf1DwDxX8RYcr7ejUzt/v8rLzIp/rL6s0uCPxAQAA"
}
}
|
codegen__primeintellect___2161
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLike any unknown mathematician, Yuri has favourite numbers: $A$, $B$, $C$, and $D$, where $A \\leq B \\leq C \\leq D$. Yuri also likes triangles and once he thought: how many non-degenerate triangles with integer sides $x$, $y$, and $z$ exist, such that $A \\leq x \\leq B \\leq y \\leq C \\leq z \\leq D$ holds?\n\nYuri is preparing problems for a new contest now, so he is very busy. That's why he asked you to calculate the number of triangles with described property.\n\nThe triangle is called non-degenerate if and only if its vertices are not collinear.\n\n\n-----Input-----\n\nThe first line contains four integers: $A$, $B$, $C$ and $D$ ($1 \\leq A \\leq B \\leq C \\leq D \\leq 5 \\cdot 10^5$) — Yuri's favourite numbers.\n\n\n-----Output-----\n\nPrint the number of non-degenerate triangles with integer sides $x$, $y$, and $z$ such that the inequality $A \\leq x \\leq B \\leq y \\leq C \\leq z \\leq D$ holds.\n\n\n-----Examples-----\nInput\n1 2 3 4\n\nOutput\n4\n\nInput\n1 2 2 5\n\nOutput\n3\n\nInput\n500000 500000 500000 500000\n\nOutput\n1\n\n\n\n-----Note-----\n\nIn the first example Yuri can make up triangles with sides $(1, 3, 3)$, $(2, 2, 3)$, $(2, 3, 3)$ and $(2, 3, 4)$.\n\nIn the second example Yuri can make up triangles with sides $(1, 2, 2)$, $(2, 2, 2)$ and $(2, 2, 3)$.\n\nIn the third example Yuri can make up only one equilateral triangle with sides equal to $5 \\cdot 10^5$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACb8N2gC/+1a227b2BX9lQ1FQORYNs6d5xgIis5MHwIU0wLNSxG5CS0dW0QoUuEltmYwQD+iH9Bv6af0S7o2KcUaDxUgnJc+WElM8Vz2Ze21Lwby82SVNmkdm8nV5K9VtolviibmeVw2k/nkti2WTVYW74t0E3EAS1mxig+TKy/CfFJW2V1WpPn7bVVutizhb2X+OVKzjnRb5nl5nxV3tCxX/MCZmzxuqK35jY9g5a5KNxt+z9Pirk3vsLhr1mVxtSgWxZ+zj",
"part_2": "5HSYkdt8bEo7wvapLiGH9kyS4s5/b2tMlqnNd2mn0t8byIV7eYmVvUVTf84ndP0O/7xPX6kxYqmP+DL/TpWEbu0WOTxE323f36/f/4wvezFpnldUg4DamoqaLvL8Y2llMUy0pp9LNu7dXNF6/IehsHKoiwuVvEuFrFKYcrjtfusWVMGWO9iRXW2wtL0gS3bHSz7aUrxIaubOdXtcg3ZafNo48MTW3dPbP7pi+2wJV/Vf2DsOieyGhjHbVod4Q+0yopSKuI9IgOj6g",
"part_3": "aW30NzyW7hyudY7eimrXeX9BaGvIQD6x3vpfXHuKJd2VJT0jLNl23eObo+4E7l7VO34eyyym5wD/q3sWp2l2ze2/UjQKwT0nKceQJhdruHPN/x96zpjEP4ORYIY1E28CHPsyKmVSd3UVzw502xbZvu20HZbVbBUT7ZeZ1mBQPRVoe4PKXMgTE0m8o9vic5s39aPJcrmCTFP+z07D///u8//9WR6eUAQ4+t/UvbHJuLLCyaJ6j+Pm49koqlAoNPbZpnzW48x47N/9N",
"part_4": "DutnClr0DHfaLQpIiTYZP9f4tiu7laFuRPd7WR9tW8IeGHsdXZG/G3pAfyyZ+QfFN0ZehLu6xN7FP7WXKlQSlpd0+BXIP4EzOSePvGQM5U3NSxy/9Tg/u/t2cTS+PlNYRHFuN0cq6jrWqY0W9FceKmnVWfUVPlzglKI+AZ5yrVZo/pt2R7o4QnNXTX5P4S65mHBbcyHO6gX8NKnpnFxeDGpUw5/xm2u44p+oyb7ltsEScLTlU/OdHlMr6S4c4NASWU8WmrXqf0C7i",
"part_5": "JRpNFW9RqlFt0VayzbasGqp3NYupYrrqMvk1r1x21lweFvttlJPf7C4K5PxrdJrNzSq9osOF2dklKFJl29kZTmRHJ+DPbOAUH9scHduk2xmOzo8l1lvkV380Pzqao8bPvnYeF7bA4XCDHq56XGevHlCh4/b1y8WieHnWw7mKtz2cszP0S8InndPNnJZzWkFEsWGPeJmtleLVK0fnePZrbNY7cf1q079yU0DDKKgCOeKMBZ3Lg9ju/Lvs/OaaziHp14vLc9ktX8hBS",
"part_6": "ZuLp2K603heyOsTN0D0C8n/Ttw8P9zssanbzaxffSqKkYAbZ3scepYxdHvY+OsLestgZfz2ohPw/lHAW7bgRad/fwXM7IIFVjYV2gje90R+Hn+ex5/n8ed5/Hkef57Hn98//hyE1JOrd5MPHz70jWFRPI9Cz6PQ/8koxFfAzMn1fMJ9FEydvPt5MWl227iYXNFi0hHu/T4FJnOsdInUbx4qJKR0W2Vf1Lq9fvWXOX2bOK6oQ+L0t4v7WgUeUiG/XYVKHOkgyWlDQa",
"part_7": "tBsdY7Z8QIOLQiH8hYSSZxg6ITpf0YwVKRg9XeJRTCsNXeJNAqRgRRJ9aQFiYEkloJk5ARUgU9zBIVrFRGO6edHRFiFaQnCRykIKWshEcqeC2G8dIhCcKJJGijvBwRbx+UAuWFU96TMcoEeGe91HLYO+2dtsIZaaQwI8D0zjoLx4IEwbR10iPdEDY5jKa0Fs5r7UA5kegxCoVQgmSAxQlpaEzgoHbGDrMkJAbqEuWF88qrb9cXhFWeI2cccIXhwZKRiNIJB4XRErT",
"part_8": "0Blln9QjG6GACKS2E1dAH8+Gm90YNE8YrB8+MVxqGJiPUOS2Rv8pYx8y0CowBnlYlJ0qQC8EpFCgngzLJt+szTpPVghxS3MvhoEmQCZ8R5ECkwEMvLQXvB2UrIUFCN6JsCA6LJKQyeX8CnSQko9JWImk7ZMBtWD+cqw4UHhNiI0BZj76FSuTsie4VwCQ/QjagRqiIkyQ5kYM2QcUdkeoogdqRVNIblBgvZFfZkF5hGHwV9rSUJoxqDMhY4ZAECaOFvAjQq5VO/HCu",
"part_9": "a4E9JZWzSgY1pn16r7moCOQ3GdW3osQEPexg8CGgHFiPGjSGwIlHfUb3MUGgYwsOCzduVM9hdVI6bgwIq0jEGDyNhSpS0qKukHZKgoAGrWhfN35DcOSs9TaRqJ12DGGk8MpCIdq5gaNOoLujmMnghmuBQStRIJlPkmD9GIaK4C1Jh+oLhgKtBISBPDXcbZ01Ao3deGENkBnDGGcxEXnufZgpMCygJCFGwwGUaBpBGItehRYxYj5V3gpUVGnQqpF5KNsOcGqYfyIBQ",
"part_10": "THjQCuHEIyhqJdOSnjG4w/y0CgLwrALwxO88xIJn9iQJBhCR/QLzCISSEKtReAwu3geZVWS6BPNFrUI9cVokEqNIijM1YQeBBjhIGgqvzZNoLdLDDyYJxQ4PCbnkYOomtIiz1mh8gYZYXigHS5pKHYOIx1TVI75lcDxAIuxOmCCAKKYLD1+/0Ben2g7iUaUNUKNkcKHUYga9k8EtGaOINSib4CJw63IYeL3wnPIpd/30mv+Hwf1+7bIPrVxctVUbfzlf3NKMr6yIAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/02Ry04DMQxFf8XKmoXfj/4Kg9iAAAm1qJ1ZoKr/jgGpmVWU+Ob4xLmOt/NpO748r+dtfR+HcV3Gx/FrWy/LOMDjMiqFAijJzUAoJQk0OEKW5biMB1gGSZiCoFYBCaMGKBLXTCinOBBTqgFnF7nzDa57JBNYFJIMKvN+LKXVBUQTEAmVAMlU9tkdkw2Bu6USsGMbgAqVTwpFmnexYdj6aNEcDVfZcaCdQP/2T78Hp23dzSG57YtVpdmMu6eVETfIxW3CuBCdOk9aPtOMRGazabavpyZLtdS8r8jIPbSMKMt5v4jcmxnGGLiz+Ne+jYdxWb8/X/sjz1svtx8AgwjR4AEAAA=="
}
}
|
codegen__primeintellect___2164
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLet's call a string adorable if its letters can be realigned in such a way that they form two consequent groups of equal symbols (note that different groups must contain different symbols). For example, ababa is adorable (you can transform it to aaabb, where the first three letters form a group of a-s and others — a group of b-s), but cccc is not since in each possible consequent partition letters in these two groups coincide.\n\nYou're given a string s. Check whether it can be split into two non-empty subsequences such that the strings formed by these subsequences are adorable. Here a subsequence is an arbitrary set of indexes of the string.\n\n\n-----Input-----\n\nThe only line contains s (1 ≤ |s| ≤ 10^5) consisting of lowercase latin letters.\n\n\n-----Output-----\n\nPrint «Yes» if the string can be split according to the criteria above or «No» otherwise.\n\nEach letter can be printed in arbitrary case.\n\n\n-----Examples-----\nInput\nababa\n\nOutput\nYes\n\nInput\nzzcxx\n\nOutput\nYes\n\nInput\nyeee\n\nOutput\nNo\n\n\n\n-----Note-----\n\nIn sample case two zzcxx can be split into subsequences zc and zxx each of which is adorable.\n\nThere's no suitable partition in sample case three.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACb8N2gC/+1ZzW4bNxB+lcFeLAGyUKcp0ApwL0WKGijcAu0liFKbyx1JRFakSnIjy0mAXnvvI/SWR+jNj5In6TfkylobDvpHoBdTMKQdDr/5+M0MKcFvqkZFFThWs+p7b9Z8ZiO3LetYTapFZ3U0zl5Y",
"part_2": "tWY4wGRsw1fV7PMnX0wq583SWNVebLxbbwThB9e+ZoorpoVrW7c1dknaNfIGn7rlNXVBnsQFlqVX67U8t8ouO7WEcRdXzs7mdm6/5XgUSKu2JUUhevFTjfMKOGQWZGKglmNkL16WaibPqjVLyw0ZS6HTK6zc",
"part_3": "qh3CqSgxd+Dl1xS3DrRs4J87tpGW3nWbQG5BMKiWwm5duzbQyLrIeW1jFgv2A+d1F6JgRIVIh9l+6XhKXztPfKXWm5YnpGq8yIQD/9HOdYl19MqGxMqAoiOlVF1PaLsCYFbS+CDkPfPtdpO/ylyEtzoGtG3I",
"part_4": "YQGmP/zy23C2Pg7jCdUdCGMIDWyMkAfNohMr6LRxIRghNtBlo3w0kv/buPBGhMBJwV4J7QBkGp5Kzp677gi8l+Y120PWwpS+WrF+JbsShrLVPmNh0+LBWOxcMK2zx4xa2iF7deahOeRU7pPYo2YVkOp615O6",
"part_5": "s0SBxl7tKX0jaqqhR8oGOPraIAUeATmKWKnAOVXDIVba29weyzizmy6mT2L6ET7OtjtqjeV9QYAwjU7ow6+/09vwNr2ffPLTZ+MkrglRNAE+GoS9RvOh/GHbqzwM9l0Xh9HQocjLzfvnHG7+kB44ULwrqNLa",
"part_6": "+dR3IiyctDfANgql6NCiKM6b9+cOIKlktibk/D2TWsg89oAbiZk76iCWsB7yfJYrPfRMk0Zzm8pefPI2UB4c5LGfvr7WV1cfn94x83D23OWAfchzNOetMGdo98QgMUullNAfKLM7VXKtU99cwzO1AbKyXRl8",
"part_7": "GPTqtM+z5yPpHACYmHr40B/mXnhp1v0yTII+bQ3OMWESG1ESQeUECCvXtU3WWAyegmu7hClUY+Nk5/I6d1uZ64/X/WkqOJ5j523OskMf4pT2nM4jLYd2oNNMYTSe2yBPqPRRGAsoKqhliwf68pSe4tQljL0R",
"part_8": "VjAdfTqhp+N+SkbiOjpCro7G2crtYMnpKT0ZeKNHSSd9wsDahwlT7TqA6bTs5J7DINi528cajhrH/auDmdvA9yAe4nrH6Q7+YG5gh5ypeiAlat9YPPfqP154jxfe44X3eOE9Xnj/+4W3BwnV7EV1eXmZT1Xc",
"part_9": "d4+X33+6/OYWYlYvJ1XkECFu9eLNvIq7Dc+rGc2rlNuLPmvVBJYkdp7MzQCl04TLRZ1mpOzF/m5Cfx8uN08xuNRsD6Gh6/4xmCqGVEO0crRq3ZRTDGhFmeHiL1ge6u4ox7Qpl48G30ZqVTAlta51Hqponhte",
"part_10": "LFflJMyIRfHKbTeEj3Tcv0LTuinbcrokWtH+LXh8FmxX+TVRMJ8AqwuyA1rBhNbYbNEztFYaf03R1NaFa7ikgP1lUaeBivZF912Sp6iIvHDJDi57+4qCf5Xpl/IfhHDRWYPfI9Us+o7f/QmKpt8NghgAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/6tWSi/KL81LiS8pKi3JULJSqo5RyswrKC0pjlGyUoiOUUpMSk5JjYnJi1HSUQDxkpKSkXkITlJiIhDBucnJKSlIChOTgTgFxSQkZjJEXyyIl19agmS9Xz5cWWRqMUlsJK1YTImtVdJRKi6pzEkFerqoFEjVAgCF7Z5HDAEAAA=="
}
}
|
codegen__primeintellect___2179
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nSuppose you have a special $x$-$y$-counter. This counter can store some value as a decimal number; at first, the counter has value $0$. \n\nThe counter performs the following algorithm: it prints its lowest digit and, after that, adds either $x$ or $y$ to its value. So all sequences this counter generates are starting from $0$. For example, a $4$-$2$-counter can act as follows: it prints $0$, and adds $4$ to its value, so the current value is $4$, and the output is $0$; it prints $4$, and adds $4$ to its value, so the current value is $8$, and the output is $04$; it prints $8$, and adds $4$ to its value, so the current value is $12$, and the output is $048$; it prints $2$, and adds $2$ to its value, so the current value is $14$, and the output is $0482$; it prints $4$, and adds $4$ to its value, so the current value is $18$, and the output is $04824$. \n\nThis is only one of the possible outputs; for example, the same counter could generate $0246802468024$ as the output, if we chose to add $2$ during each step.\n\nYou wrote down a printed sequence from one of such $x$-$y$-counters. But the sequence was corrupted and several elements from the sequence could be erased.\n\nNow you'd like to recover data you've lost, but you don't even know the type of the counter you used. You have a decimal string $s$ — the remaining data of the sequence. \n\nFor all $0 \\le x, y < 10$, calculate the minimum number of digits you have to insert in the string $s$ to make it a possible output of the $x$-$y$-counter. Note that you can't change the order of digits in string $s$ or erase any of them; only insertions are allowed.\n\n\n-----Input-----\n\nThe first line contains a single string $s$ ($1 \\le |s| \\le 2 \\cdot 10^6$, $s_i \\in \\{\\text{0} - \\text{9}\\}$) — the remaining data you have. It's guaranteed that $s_1 = 0$.\n\n\n-----Output-----\n\nPrint a $10 \\times 10$ matrix, where the $j$-th integer ($0$-indexed) on the $i$-th line ($0$-indexed too) is equal to the minimum number of digits you have to insert in the string $s$ to make it a possible output of the $i$-$j$-counter, or $-1$ if there is no way to do so.\n\n\n-----Example-----\nInput\n0840\n\nOutput\n-1 17 7 7 7 -1 2 17 2 7 \n17 17 7 5 5 5 2 7 2 7 \n7 7 7 4 3 7 1 7 2 5 \n7 5 4 7 3 3 2 5 2 3 \n7 5 3 3 7 7 1 7 2 7 \n-1 5 7 3 7 -1 2 9 2 7 \n2 2 1 2 1 2 2 2 0 1 \n17 7 7 5 7 9 2 17 2 3 \n2 2 2 2 2 2 0 2 2 2 \n7 7 5 3 7 7 1 3 2 7 \n\n\n\n-----Note-----\n\nLet's take, for example, $4$-$3$-counter. One of the possible outcomes the counter could print is $0(4)8(1)4(7)0$ (lost elements are in the brackets).\n\nOne of the possible outcomes a $2$-$3$-counter could print is $0(35)8(1)4(7)0$.\n\nThe $6$-$8$-counter could print exactly the string $0840$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "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",
"part_2": "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",
"part_3": "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",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "cGUUQbUGMms9QdtoTvtG24m/gTuRlM2HwxOA2egE9MluROwxoBtJYfzU1SPmIWKjILOzQLk/SUgFrKLxkxdxqg0N6P9H6UrZru5ExqBV3Ewoj8PpNkgCrBgZlfIyNIZEReSaTQ2UAkKAxSAuJ5mFeTo0joZu9XeGgezcIz5t44FHvCcHgSqimOE4VOHvTLSWAIfiXsLdjOE9IrJBPchAdiAIcK+VoaSYLgVJx7KePSryzK81RI1Vi/x3IwOGHilT/BCCHHbzGKkUnlQQgMuKaym+VxCRvZUAYmjNORCApHjcyPxdNFAAxlkkkJ0AZ0lPv0LSiBHC+YKjN3BPZeeuiqpRh5DD+c3Z3OnV7hK3WzRN5y39uqmJz8u2Mn3zIgFz2eJ4t2YBy/8NB+W3G8YKLxMlgzH7+fRbNFI1Udx025ftAeviRuotCcdulD9HRgDcXYY7uTWIpP6YMlmnL4EY9NRUhL7F7URE5euajSITrwud5J+8yzj5nolZJGY3piOPaL4uTIW+dDZ+13qxL2S0/x1laaYjIZs6MiAEOvU0fqylLtE2Mk68CX8dmTMeyFL",
"part_8": "wYklMRZqo+Yvv6Zh1LKofTAFbWUK0iplOGLqlQhIbO9xbn4FIsyHJ6OsA6pWxqzDyuXkn0aZzk21+74v7r4Jx/KeuUIaJVGnC1FZHK5M7pinBvko1DCYY2/RNtkIXYQlkeUnQ1E5cVRUEZElyTefEgwcYGtF5Tyyat1ninFkDhmlygHiEzEHdYy5iyy3G2Xg7mjqL7QD+E+kQQb/6jHpwNuG6oXwz677CVlFHsSu/ikTkYpWQSeinzuAylZvs9rsZMpIo4wLoDFSQoeafUgm8jFAZpx7lYNMjL2TRRC22MTAim/XkKQ0pHSgcM7kBDIoJGjhIBhcBmBfCQj6MkcV2R/71MNlQ8j+jiMTw/lBCmdYpQTZHsZXjY+S0gKfFbtln5iUmAL/bUi0cLXAHQUEEaBqIoC0XQYiOYUiA4SgigMjAPRoucPrUIcKjmtOBiHyhGjJ5w/hGRgPw4NXHowDi1chYov9dPi0OwrCEB6AVDdq3DKMqyRqWGlbgR/IewU/FwccZYQ4IfLwt3LXUrVZ85J5H391yJgT1kkdNaUgQyxL8SoVKWD9hs6mTKMvSaN",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2184
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThe start of the new academic year brought about the problem of accommodation students into dormitories. One of such dormitories has a a × b square meter wonder room. The caretaker wants to accommodate exactly n students there. But the law says that there must be at least 6 square meters per student in a room (that is, the room for n students must have the area of at least 6n square meters). The caretaker can enlarge any (possibly both) side of the room by an arbitrary positive integer of meters. Help him change the room so as all n students could live in it and the total area of the room was as small as possible.\n\n\n-----Input-----\n\nThe first line contains three space-separated integers n, a and b (1 ≤ n, a, b ≤ 10^9) — the number of students and the sizes of the room.\n\n\n-----Output-----\n\nPrint three integers s, a_1 and b_1 (a ≤ a_1; b ≤ b_1) — the final area of the room and its sizes. If there are multiple optimal solutions, print any of them.\n\n\n-----Examples-----\nInput\n3 3 5\n\nOutput\n18\n3 6\n\nInput\n2 4 4\n\nOutput\n16\n4 4\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACb8N2gC/+1aW2/bxhL+KwMVBSRXUbUkxYt6XKDpBQ0Q2AGSog9V6yyplbQtuVS5yzg6RYHz2vcCfT0P55e0/6S/pDO7pC62mNRKgIOgJg2YOzM7881114B/6s254VqY3rT3pJKFeKSMyHORmd6wt6hVZmSprhQvBAogSaq5eNmbxoE/7JWVXErF86t1VRZr0vC0zF8IMCsBizLPy2uplpCVc/qFMmkuCqg1rUgEKcuKFwWt",
"part_2": "c66WNV8icWNWpZrO1Ew9QxlteGWgXNgNSlwDz/hcFDKDjeAVpFVZL1cGeFrWplVqzeAWnmVlUZToH7qAmuq5UEaDVKaEeVkV0qADQo/gUgmS13W22mfAimvg+P7xG6Sgf6x5JaAQRlRwXWIYKqjKshgB4cyQZ/gPxOJkBE3szAsQL3lm8g3swUCwlRjBwwZ3zq9B8w3RuXFMKGptIBWAhFxw/A4PUGhYo71GIbqFSAkQ9K0KqYdW",
"part_3": "sSUtymrftlW84k2qUCG38dqaUYd2Bjd9zLgCoXJeYcK42kB/XWotU3QwLc1qAFrORZs0az/doBwaSqWpeLUBlJdGon1MhliiRhR2tkbwpcjXsJIFZCssCrFTojGmmJA833clK+t8DrnTBRJLQc3tFlManm992yq5JhUadEF68KNBLkZUcTP1gJ5Hal0b+9WW4UJWGJdcYqFkpTJcKkpUJbBA1zwTD7RY8woTPW8d0qCGVDsIJoU+",
"part_4": "gz9/+Z+lDHFJ32z8XTKAP//zqyvsukhdELZ+tW5o+W+sxD0P9oFe1mYfKfavMg2uLQ4sA37FHBL83efWPpI++v2/DguSd1AW1NC3w0bbJcKycEbwaNGUqC2SOjdynWPG10ZiXDFReU09h6bXFhLViNN2AP/zl7zAfbpxwIZ9pnzwYUIyzruZYjERQyI1Ih4EEByIILchUbokicG1xBSnNEPm1BzowaasQa9sxThgSKi2cKlpUbYk",
"part_5": "hfRelNfEa7qkHSykB/ugrpQl43QTI5yLlVhgPFRGY3LmXvUp8rDzMkzgp1g1AkvIC0P4TL4AD540+h6SqU9qnHoVwJSKvjQyu5L8h5l63EzFKTyxYxH8kT8iLxsDM5xCC8iEzOfyRZ8P0wEOTsCnAcg//DCFD6j+JLb3+ymIXAsYD9qdBRZyv92jhqgAznEvn/cHjqZxHZ4ptyAdZyl8fA662UKPDWQfGYNbtOE+zUFya4NqSaKP",
"part_6": "ugdwdgajSSNplsRLxmPWWkUKR9J4u0p3Kxprkvq+oknRZzjxPmCDPXAZyrbh0UO5B4ecgX8hjKZH8TPb29iIEJyPQZ7dZO2gIu8oizDLoxzCnx0ASXdA+FsHknYC4TsgLmFIG9xY8yGpsAXz3usfuLi8ePD08vFXzx5dXsDTZ1998QU8/Pzx5ddtwdnawjNRnHttmt6D8RSeGjS4bAlsCo+lNm4eEkO3HG/HaQdcU5vU8dqWFX70",
"part_7": "ByPauG7LGANIRuH8nIw1zeG23BJgNwRGep1Lc0STtxXMEVK/4Os+Yhre2DbYNtt1JY3o63NsXOrg1n/UiHcSDRelwj4nF1xvNzyJ1yW8BOFgwQK2lgatFP6Mvi+xg8k0+jsEPdjrW6T09UE+UYFQcwLQs6gcIjcEBjjDLGScX3hGS4XrZuTd3+vu73X397r7e90/8l639bk3/ab3/PlzN8d2V7D7O979He/+jnd/x3sn7ngzhROs",
"part_8": "9+2wR3MKJ1rvm59mPbNZi1lvipbsQL1qRmVviBTrp2O68U1eEaN0A9pycI67QU7Mn4fw93W6eX9UJ2lrmXfSyQDfozpJJTsFJioct8/e53Hg41sPme3cfycgMUQdOQgoB/FJzu1B6wrcgSsQvoEHRwPx/41ps9PH2EYdsXUSts4Zg8AP7Ruf4D7rtBIR9ghdeTdSSDG3cX+FOZcka+yNnAr3cvx6725Jv5u9nrSFifdI1o1hEsc7",
"part_9": "Ex54SXB6YqkFwuPFaUv/pBnPQmBJ18nhUI8b9t3OjknM4nHo+cBcxsPONE2CZBz7kW1YFAsjSMKAnXC2JO7xsU07unjiJELPs312sDzZWNTR1Afad4tG+hRjybb8gXmvspkEVApxMpl4no/nTvQWjgLWZfOgvSe7XScElTXbGfiut8iXo0bx75Mxce3lhr73ZE8ILZnEPL4qkdi5kT0D4knEAg93nBRUhnqCBFhk/YteMTPjAD0M",
"part_10": "bAfiLoqIx96kEbuOtrfXgG3NtI2VvOa4a44DVy5v57bydw7YcDx+A6uhF7HxJOy+KvhR6IW+H1ILRglO1yCanDTO8PrNOo4VmsiTtl7vFrSETZII0YHvJ3it8v3Yi4/XBQuSkI2jCTUyCsfBnvCdExV1xgvTEfjISfB4Yyd0sN/Mi67yjl3jstCPTopYe79kncdKewUN3d8wB0s09i39Y4a+qpX8sRa9qalq8fNfBJoeI9khAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACb8N2gC/5WRzQ7CIAzHX6XpeYcWGB97FVm8aNTETDPhYJa9u92MMqPRyAFK+6P9twy460+526xTn9MeGxwiHrpzTpeIDawiaiIG2cDF2EWsIKIHB/XzpmrPnqzS4i0M02MBA//j/mQW0AKHRXFB2BCZAOymJ8o96HYKn3JatCIyaVLIVjvgUt14MT3YkrU2gbx22s80WQfBGjZPwC6VMdh3ob+J0t0L+r392Va0mIBk9oZUMHNApjF9lro3145Y4SVdj1v52D7LMd4AVY/tVfABAAA="
}
}
|
codegen__primeintellect___2188
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nIn this problem MEX of a certain array is the smallest positive integer not contained in this array.\n\nEveryone knows this definition, including Lesha. But Lesha loves MEX, so he comes up with a new problem involving MEX every day, including today.\n\nYou are given an array $a$ of length $n$. Lesha considers all the non-empty subarrays of the initial array and computes MEX for each of them. Then Lesha computes MEX of the obtained numbers.\n\nAn array $b$ is a subarray of an array $a$, if $b$ can be obtained from $a$ by deletion of several (possible none or all) elements from the beginning and several (possibly none or all) elements from the end. In particular, an array is a subarray of itself.\n\nLesha understands that the problem is very interesting this time, but he doesn't know how to solve it. Help him and find the MEX of MEXes of all the subarrays!\n\n\n-----Input-----\n\nThe first line contains a single integer $n$ ($1 \\le n \\le 10^5$) — the length of the array. \n\nThe next line contains $n$ integers $a_1, a_2, \\ldots, a_n$ ($1 \\le a_i \\le n$) — the elements of the array.\n\n\n-----Output-----\n\nPrint a single integer — the MEX of MEXes of all subarrays.\n\n\n-----Examples-----\nInput\n3\n1 3 2\n\nOutput\n3\n\nInput\n5\n1 4 3 1 2\n\nOutput\n6\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "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",
"part_2": "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",
"part_3": "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",
"part_4": "tG/NWDE7Dn7vcVBkbQnwmZkHY/Q72SWqmc99ayt/Jm6t7vO6aLhGU9/Npt5epqDg2fqHeWuxQCzmH4BEGdzIJypD5YBoAywuW3Ix2NUDWsHYq1q24E6MjluGh2z2WK1ldXqYWNioR6oasFEFO1CfWPJ8gUFJvZiqG1msWjiVDN36ZTqxqdUZOniScUEzDlZi4M2IUJgG/XDvEZrfFAY4Ite1Zsj0PWgfYjWFwZst059tDxkHfDgGvDnx3NIqwcgrWR5nri7u71qT0uh4pU9M6dAte1ShWdrDrUmV9vuddw0G8ZZovcdwrZwBho8iOb0/LjBFLMPJl55mRHMKFj/IkPMYXbh8pKsqLOr7FT3Fm02TMTU9jKHsgJqPnqx/Y/eaPuXpNr128KSUkpk05X+qbuFVDAiw/O66Z6nIww3PTu1U4+KnEukXhiV9vb2l0rzPb2FSruuYGPf3ghVan8nHY1wb+jmIk6y9RqBFLckEI0FDrJCOffRbI59",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2193
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThere are n workers in a company, each of them has a unique id from 1 to n. Exaclty one of them is a chief, his id is s. Each worker except the chief has exactly one immediate superior.\n\nThere was a request to each of the workers to tell how how many superiors (not only immediate). Worker's superiors are his immediate superior, the immediate superior of the his immediate superior, and so on. For example, if there are three workers in the company, from which the first is the chief, the second worker's immediate superior is the first, the third worker's immediate superior is the second, then the third worker has two superiors, one of them is immediate and one not immediate. The chief is a superior to all the workers except himself.\n\nSome of the workers were in a hurry and made a mistake. You are to find the minimum number of workers that could make a mistake.\n\n\n-----Input-----\n\nThe first line contains two positive integers n and s (1 ≤ n ≤ 2·10^5, 1 ≤ s ≤ n) — the number of workers and the id of the chief.\n\nThe second line contains n integers a_1, a_2, ..., a_{n} (0 ≤ a_{i} ≤ n - 1), where a_{i} is the number of superiors (not only immediate) the worker with id i reported about.\n\n\n-----Output-----\n\nPrint the minimum number of workers that could make a mistake.\n\n\n-----Examples-----\nInput\n3 2\n2 0 2\n\nOutput\n1\n\nInput\n5 3\n1 0 0 4 1\n\nOutput\n2\n\n\n\n-----Note-----\n\nIn the first example it is possible that only the first worker made a mistake. Then: the immediate superior of the first worker is the second worker, the immediate superior of the third worker is the first worker, the second worker is the chief.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACj8N2gC/+1ZwW7jNhD9lakutRvZkOQ42RjYQw5bYC/bArvAoohSh7Fpi4lEqiK1jhEE6LX3fkAP/Yfe91P2SzocSrIcJ5tNqt4cxXZIDt88zjwOmeTWmzPDNDfexPu5EBl/Kw1PUz4znu8tSjkzQsmpZBlHA+wScs5vvMmr4xPfU4VYCsnSaV6o",
"part_2": "LLcI71X6iYNJOCxUmqqVkEuYqbn9QJvLlGdQatuyJtizLFiW2XbK5LJkS+xcm0TJSSxj+SHhBQeGLwkrVVzzQoOQwBAxy5lc+8DZLAG1sGgZJEzjWCnFbyUHMYcFkoIQjAI5hDc3bJaaNSjJmwnC2s8SwRc+JNjAOfiu0djCOo/Ab2Y8N8SXTMkNRzST",
"part_3": "OjSRZXwumOGgy5wXQhXDDfkVcSo4UtLGUmkxbtaE3TbkkKgVvTJcWwOmoSeVQU/ornHVH8JHmvy9bhnaSNE6dhj55G+3v2by2Cwm56AVOh/Cj8rGgmV5yn0QNK1KjkkKztsJoljVKaIsrBKByyZZiAIDge6agDpums8UOlvVq3qAazWJENwkk4jim+Y4",
"part_4": "dJokd2ZSRs1KbSLp35fJBtlGxA7anDS9Q/jQyINE1fjH1DLMbDvblaASkWmeLkgr71XG74tiZcNLak/KoliT44zNkQFkQht2jV5/UaXLgMKo4Lidj7tJZGUGsswuOSW4kVnCDOalTC3QdRvIcojlwH69lXlp6KdKxFXGUiFtUqVhQrpo5UoLIz5ZkoYv",
"part_5": "rQPp9AK9EL788Tc27Xv0+Z8w+HXsg+vUbqj/+a8vv/9JhHeJsmopuB+roFBo621Va2WbktzwYNMQpTuNfBgOh/anW3kHvYA8Y0PcVfQGEPZ91CYJmforuWwofX0XthIGK2ESqiC423NVGD4HdqlK0w7uT6VpRxfLrTRdJO2N25e6QqYcxnIEUSwjCOxH",
"part_6": "LJ3vWIa2UVmMYYQdaBHAIYRtq8ihV/jvlOEN67eytZGrigCC9jRKQgss8o41BWtjWsXpvoYxoXIC8ESB2oLY2tRVp/8UwtaOb5eSbYAt0K061chP2OBhvnFfX+IEMxdO+GvcjTqhVOWUWewosHympT1C7SZFW2Wja593WOh1c1rWh6PFKbgpi7qKzvkQ",
"part_7": "D92CL1CkcmbPYOlreI1hzHvowycyvf5Q56nAz34sT3E0xej2HjNBG6zfp2d6EJ7Dd68hwMMWEwAYL5waukY1jKOx5KnmWzbYdzrUKPIeYmXsxhG66Z1ik0nbOgvO4Qfo0dgBbjPqX9Hkui+WClsD/Fxglq5srSvwEsB7sl85I5ZXSGLD0X4pOGhoNoYI",
"part_8": "f2aNd6xbA/WkqtvSGVAnkzhol3ZAy1B+Ndy3ibrPbhD5gxC/a5bu3VqZjRV6PAjP0c6tYGtCi7HZobvDbeOCWGKl6DHpt9g6a18d2IJ2RUUNeZMCcayP6qHEo3JMgZUS25XY9te1/XVtf13bX9f217X9dW1/XevyulaDaG9y5l1cXLhDMpb7q9v+6vaM",
"part_9": "q1ssUTveue8ZvI2glryz29gz65zH3gRij6Q8rUTq+dhDcnGDtprU5QRDQcPKVQsaD6n3zodvh7Tlp11/HoKNng8bElTwIFzwfLjIwUHQ1bJrwLBbhuEjDKOXA4bdLTnqOobRV2L4giWf1ElpniM4hlcPwo/+O/y4W/ijBh4DA0GXSoj+DyU8ptUXiH+0",
"part_10": "WXq3kBF0uOyaZYfVc1OQw+4W7iCjLhcedR9Ld2x0KqJRxTLqlmXULcs6PVFX+3sM46YudVg2jinbh3iqH1XP+EHowxec7gEcxfaXm6D1PE7++CUxqfdqCCM47EoQJw0sFgE8AKqn2yNgbPcush51XbrCp1R3bv+Vq6fuz2/exBQlv/sXK1sTpAseAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/22QTQ7CIBCFrzKZdRcMja32Kk7jRqMmhhoKC9P07k6BADVmEt7jG3j8LHi3kzfXi7PePXDAhfFp3t7NjAOcGVvQzEaDBhJlbKAwFTSyU+groFQH6KCHY+6Tgk4mrWwqRdtYxbYhlnaMEqMfpnbHR0ZyzcjGDU7eVS8pAVVUdn126s+64lL8ig3O7vO6yZdZL7J+AZo/LipKAQAA"
}
}
|
codegen__primeintellect___2207
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAfter playing Neo in the legendary \"Matrix\" trilogy, Keanu Reeves started doubting himself: maybe we really live in virtual reality? To find if this is true, he needs to solve the following problem.\n\nLet's call a string consisting of only zeroes and ones good if it contains different numbers of zeroes and ones. For example, 1, 101, 0000 are good, while 01, 1001, and 111000 are not good.\n\nWe are given a string $s$ of length $n$ consisting of only zeroes and ones. We need to cut $s$ into minimal possible number of substrings $s_1, s_2, \\ldots, s_k$ such that all of them are good. More formally, we have to find minimal by number of strings sequence of good strings $s_1, s_2, \\ldots, s_k$ such that their concatenation (joining) equals $s$, i.e. $s_1 + s_2 + \\dots + s_k = s$.\n\nFor example, cuttings 110010 into 110 and 010 or into 11 and 0010 are valid, as 110, 010, 11, 0010 are all good, and we can't cut 110010 to the smaller number of substrings as 110010 isn't good itself. At the same time, cutting of 110010 into 1100 and 10 isn't valid as both strings aren't good. Also, cutting of 110010 into 1, 1, 0010 isn't valid, as it isn't minimal, even though all $3$ strings are good.\n\nCan you help Keanu? We can show that the solution always exists. If there are multiple optimal answers, print any.\n\n\n-----Input-----\n\nThe first line of the input contains a single integer $n$ ($1\\le n \\le 100$) — the length of the string $s$.\n\nThe second line contains the string $s$ of length $n$ consisting only from zeros and ones.\n\n\n-----Output-----\n\nIn the first line, output a single integer $k$ ($1\\le k$) — a minimal number of strings you have cut $s$ into.\n\nIn the second line, output $k$ strings $s_1, s_2, \\ldots, s_k$ separated with spaces. The length of each string has to be positive. Their concatenation has to be equal to $s$ and all of them have to be good.\n\nIf there are multiple answers, print any.\n\n\n-----Examples-----\nInput\n1\n1\n\nOutput\n1\n1\nInput\n2\n10\n\nOutput\n2\n1 0\nInput\n6\n100011\n\nOutput\n2\n100 011\n\n\n\n-----Note-----\n\nIn the first example, the string 1 wasn't cut at all. As it is good, the condition is satisfied.\n\nIn the second example, 1 and 0 both are good. As 10 isn't good, the answer is indeed minimal.\n\nIn the third example, 100 and 011 both are good. As 100011 isn't good, the answer is indeed minimal.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACj8N2gC/+1aa24bNxC+CrsQYBtVBK7zMgwEQVC0gNEmLVoD+eENHEqiJNYrUllyrahBgB6iB+hZepSepN+Q3IcdeZ1VH+gPGba0JGfn8c3MxwGSD8lUOGGlS06THwq1lGfayTyXE5cMk1mpJ04ZfanFUkIAW0pP5fvk9OSEDxNTqLnSIr9cFWa5Ig0/mfxaMreQbGby3KyVnrOJmdIXZMa5XLLS0opEsDMvxHJJ",
"part_2": "61zoeSnm2Ny4hdGnmc70i5mTBVvlYkMSr6RhSvsXczmXeiqKDcuSl8IV6n2WMHzlZr4Zsm+l0CX7UcpraZl1onByyqamHDtSs1BLK/PZKVuKzViytWSFFHm+YbmC5zBwrQpXitxvK7d5zs4NmyFqpmYwrizDrytKOWTwREs5xdIwuyXwGPGIYvlOugPLJrDEBJwqAjDaKuu9MjNmNJz4RRYGXguYMxoPc2O8YeVI2gml",
"part_3": "LZuq2UwWUjumy+VYFpbevvXiiH1jCibfi+Uqh6cpfjk+OH6YKKTXO2Trhcol4/6UPuntNE0rIW2cF/QBvJbhRaCkmxAGdkDWc6nnbsEGevAZQY3Y6wAc4TYpnVeiNBaoBLUE9CtjrQJ0MUBSZMtxMGkhfglf7eXxkGVZPjXO0upqAJnJAikQjhHMhtKFeqvCHbGXpqD0FEvK95BSvxCUtJjfyvp407YbjVr5rpR6ImnP",
"part_4": "J6WHN3BDFQTMRDipBTUUO/zZwJyeHzEoFjnpGQyZGsmR18i+JJX4zDJS6ZdX7BmzA5+MG8kFhM67QplLeYASzx5w2oBw3AtbtEeoXKPAUQXCvzkkURSCr5IoQDCGSqH3gNdE6APncxZtQSvVvCVIAdjWfInGM0uvh5p21IUj9sIFBeAX5sA+dTik5FZAIaJaj3eftI8Naq+2hs6IRqA9t+Zujb4vWo41eKDdwlasiSGT",
"part_5": "VPZgpnK+8LAMHg7aJps++UpotjElyCFfBSp6TvUO5JhdmHVdEcQYpS8Fka/FxiKfaBs0x5mv2yK027LMnUKWmVk5X5xC2zVafghyQRBYbrzVTD+gnzO9Kp1/oq1zYiNVWAdu0zI2BGKHTMMmaGUEkdO+A60WvokPBymKGf3H/BdAGxz98fufv/4W6dd3e9TXMMGoMmol1E+D1drQTdkO1iDKmOFC8bzRoo1WnN+Xrh3o",
"part_6": "WbgWmliHzHiJLdFdNdFdVUGJuvc/bXyfS6KJNlONWlZbwdZmycr9BCFXohB0Oa0VFfBKTIgcz28gLMWkqm244a8a3FogSOXAxF76E25p5Dy30DM5TkC2ibEiv3GrercXX3fRfR2IyMZ0+BrMdOp/Mx1SVa3j4TEWvH1KG4zX50/oHJ2Z3pYBB8Td2vwr4+T2SqgZslV6KVsLW5FYuClAE7HjI9mROOVUeTSxbYGrnSk5",
"part_7": "3ZL35o4N5BrYqLl0oPsG8wX1AVHSTfOUrC+ftgEMG0VbP68YPd1qg+DqZ+e8ZoO1Ql2MCSSMat4KlT34qsynMenYKBrOoonHYaZyIRGvQGzNBFRNeqSnkK4sdIR0KkeYIAvpx5cJDZQadxq0H3o3Do+OMhDFMxZXI8rZ6hCbmIDsaGJKSB7wgyP2xbNmnR4cYVpkwc3D9Kh5tniWuZWt4+P28cXpg/QNmvECX0dwzK4w",
"part_8": "8MEpV4CwsI5x7Mfa/Vi7H2v3Y+1+rN2Ptfuxdj/W7sfa/Vi7ZaytlNjk9CJ5+/ZtmPgy/f8ZcTMNt5I3w8RJUDLG2osPWeI2K5klpxg5PUqXMf4EbZ14J8MhqEXTXzgIfNA+ST4O2edrO858p2xT54/QM/0UPsnq1rpTKR2zvp4+wpu4Su9WS/dsX6U+dNzZdGvj726XK5HeeDx6FCKmoDnNvkFV9ZxGzdUe74Ttc5X0",
"part_9": "xuGEewBrbTyYiOuoOdiNVnkAxK+j6fplL5beXaT/uKG+SffR8soKD+oaF4LWtHamcjGu09rH2ineoM8rRbyrVv99471r4Enooa7O9cc7Nxm/R3st0t9C6I+0Lo+OJqqF+lt5XDsZs8M7iPiWXE9TJ8HXphq8srutfSra8x7gLYaJZeg/76WjlnBvRB/62yJ63oaL85v131Ez977c/6Z5HAuFN23J675qGrZuy7QrLz20",
"part_10": "9HPzaR1/WjFkTQoNFLxFF2m1W1FtWnnBuwH++wZ635uRpGvj9X1R3QwBsxaS1Z1x44Lkrfdb12XNsV1N9Z8Y32Fc6yKdvg0YGrmjfnvnjYC7G9Id4u1wr7d3J5GZ7xv2dhr1HoZ26cjObunppJcdNPLOmt8JUn7vyL/b0P+0pnjeBas/3wGIztLaDYhAet235i4DejVS3DtARZTf0P8QspelVu9KmZzSPyh8/As7qfaJYiQAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/71RQQrDMAz7SvC5B7uDHfqVueyysQ1GOtLkMEr/vjim2PnAwGDJloNENnikpcTbNaeSnzDBxvCKn5JXhilcGM7MkRCRqAKGITAIQmMouO6ltJEiOdNhK9SNioQ1iRQeFO0Zcmol2BkwO6fm0PgovF+jO1a58lkGS8ku73jkDeTTGvxHUJfSIHrizXUHNRnMOwyw5u/7Xj80ldr2H+QopqjoAQAA"
}
}
|
codegen__primeintellect___2208
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAs you know, all the kids in Berland love playing with cubes. Little Petya has n towers consisting of cubes of the same size. Tower with number i consists of a_{i} cubes stacked one on top of the other. Petya defines the instability of a set of towers as a value equal to the difference between the heights of the highest and the lowest of the towers. For example, if Petya built five cube towers with heights (8, 3, 2, 6, 3), the instability of this set is equal to 6 (the highest tower has height 8, the lowest one has height 2). \n\nThe boy wants the instability of his set of towers to be as low as possible. All he can do is to perform the following operation several times: take the top cube from some tower and put it on top of some other tower of his set. Please note that Petya would never put the cube on the same tower from which it was removed because he thinks it's a waste of time. \n\nBefore going to school, the boy will have time to perform no more than k such operations. Petya does not want to be late for class, so you have to help him accomplish this task.\n\n\n-----Input-----\n\nThe first line contains two space-separated positive integers n and k (1 ≤ n ≤ 100, 1 ≤ k ≤ 1000) — the number of towers in the given set and the maximum number of operations Petya can perform. The second line contains n space-separated positive integers a_{i} (1 ≤ a_{i} ≤ 10^4) — the towers' initial heights.\n\n\n-----Output-----\n\nIn the first line print two space-separated non-negative integers s and m (m ≤ k). The first number is the value of the minimum possible instability that can be obtained after performing at most k operations, the second number is the number of operations needed for that.\n\nIn the next m lines print the description of each operation as two positive integers i and j, each of them lies within limits from 1 to n. They represent that Petya took the top cube from the i-th tower and put in on the j-th one (i ≠ j). Note that in the process of performing operations the heights of some towers can become equal to zero.\n\nIf there are multiple correct sequences at which the minimum possible instability is achieved, you are allowed to print any of them.\n\n\n-----Examples-----\nInput\n3 2\n5 8 5\n\nOutput\n0 2\n2 1\n2 3\n\nInput\n3 4\n2 2 4\n\nOutput\n1 1\n3 2\n\nInput\n5 3\n8 3 2 6 3\n\nOutput\n3 3\n1 3\n1 2\n1 3\n\n\n\n-----Note-----\n\nIn the first sample you need to move the cubes two times, from the second tower to the third one and from the second one to the first one. Then the heights of the towers are all the same and equal to 6.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.0625
| 0.5625
|
{
"part_1": "H4sIACj8N2gC/+1azW7jyBF+lY5yGAkjC+K/ZMCHXSABBgg2C2RvI8dDSy2rLbKpIamxvYMBcs09D5BDnmyfJF9VNUXKlmbHXgdBAo1XFFld//VVdVPYz71FWqeVrnvnvR9Lk+t3ttZZpud1b9hbbu28NoW9smmuwQCSsQt93zufTLxhryjNjbFpdrUpi3xDGv5SZJ+0qldaLYssK+6MvVHzYkFf4LnOdK62FT0RCyg3ZZrn9Jyl9mab3oD4UK8Kez6zM/tdpR6KrVrb4m6o0ixjobVZVMpY9b0uIbNQWQGDmyx9IC13pl6p+fZaVyP1J1PXmVY/6vohVau0UlbVxZ0uKz",
"part_2": "hkK1PVJFAshZ1uSHuFOFVlftYj9RMxi0a7za9xbxpJZk+vPpsvTrqq0/laL1RhNT6ws2kUFriUI+fFQi+NBTstGAuha5OZ+oG1KZSAhcRH+JuqT2m21Up/3KaIvWCxhVkudantXKtrXd9pbZm80uZmVe/CWOFJV7WiBNEzKkGPblVMjNQfi1Lp+zTfZHqozNI5eb01Wa2WBmml4BqHOBGNmf5kqIKh8ocqxs1geCiiemUqDgpfuxBi1e/6x7q5OKJZTYZ7/iKdnUV/MFKEi5/AcV08qLvU1geT2Vhu0wnTCAWqoJm+NkVVGcBxpL4DrqBhnlq1KMhXsG50uSzK/BGOC5BT",
"part_3": "6gbo/oRbBIR2qc5Vna61S+xGcrZEP6iqyF32uA6bLVJRd+DB64wPx9V6DsBkGk2pbFGT6rR2xbkrttlCWbLPCskqWyxsi1/Rxj7crcx8RWbvEHSpczTLApmYp9uKQENFsmv0U/2G8AYmmKOsITDJ9fcamdDqpuCmLVQ1XxVFJlXiGhjKX0pNb9j0Lnm2UDmJwnur1qrawpFdCqtdSxToB0TJxXRlytKa8l6qeZZW1RCJ4jkgVgq4nW2QqFyl8znGTmaqlYANY2w9Iqdn9oz+vbNIEd81qFmaErDK0ITUynUK3Kj6DlFt0rk+q/QmhXvIEOBhauoAg2F4QwCyXMO16nvql7",
"part_4": "//C4909cbjoRLCuiGMB+qXv/2D8+PGRotCI0W6gWbLAG36M0/vTb7NOxJtplyiCKAutZhNVGqNEBaPgrHfEIoMLheIPIjvfw1b38XjN5CCdJo1nd9N75+3dTe/7yS4Too3paGaHsivLeyZ1TfpvmMV5yNX/VxSOpBARWMzg6XhZTK6eYYNhLPXNPXeOODmoeRRk1xTlmA/XdbUQJJOQjZ48gJW1p3EC8hdmvfNH6yT1XoB3QRcMjrqJMXqexjgrFRNWmiY62pemg3PFOjSabdFaExR7p4W0HCebodOgJNAyrVMaaAsM7nBaOQR4FHPWE7lA0bAptSVZvu7oVIXxfrA/OLB",
"part_5": "eoap/2iG2WbY3NIizei+QcH+qW5RsB92A8uBHZv8XFe8M3Xy3Unbo+2rnZqVK9ucKLsd5GddFpJajhsDJsUn32a1wT6GTihLnF1Qto9b2iUrKq1MwV+FCoqLhBoM18WQJw5pTmn8o6w02bhwqX1oct7thj/IRlq5fuDZM7OB8mc2UhMVEaN0zMyOieorjy6BwMRxh0Ty6avl9oiRFe0YIxKbKBCxowZd5oAePbn47q7jJZXncMdW7D6HTUCmeGm32O0wAkbe8YYtPlx3CELcEQUILOUoRJB5zEp0xyiGQWBwHjzINKchKUS7xZHm9lAxaua7ofTIngQUVzUOnsxKUVUr3j",
"part_6": "uliCCUgFq25U6jfa1eFJQ/+vsBZ4Rqd5Btzq2kp9T1thRHcarVI5yHS+3OYzj9wnx9wT70B6MKO1Pdf6PeDGbWglr3afn9+BLP6/bZo2dzlVX1xfvLmb3d3eUXYywc00hTxlCPlTg4636mLasbDHByVvjHus1la8dcPpVaN9y5vUBniAZHub/AptSl4ICY299d5PdOhmlXOYW2qUf8WtDP7WBv8X5v8b67yD5B/PLthfeUfH95tkemrIzSzUbbRZ+WO5puH611Xch3ynVW6Y7j16VO1zP7e0ZDEyXNgmuaBG3oZ520CG9Vl/0d4+AtqvGWSPngSFHIu11VOiqIjqK89Vod",
"part_7": "ty1tAGRxuYGqusSmhWcHxNNb1ukt6/SWdXrLOr1lnd6yTm9Zp7es01vW6S3r//4tq1FS9c7f9z58+CDn16+8H53euE5vXM974yJMAlm9y2GvxrEYSOu9/zzr1Q8bPeudq1mPgX7lINwbgsIwkUWaHM0MgiZeLmRa8PqY12kayTgini9D9RwD4awZW4cMeEwP2IDXMSb3zzQWsYft6DtkMGC6567+7v6ZpkIVs6g3Ru78g5Z8ZmlyJ9c22O79i8KknPLfkcKNn6/Yk9S/ukIcfMevrtQPJq+pczoldV7wqn5K3L4XvaJa1x9Azqsq5dZLlD89orRF8Yv8/Q+qDhIVekc68D",
"part_8": "eo9r+qen8wvqiJHTq4O9SR6+tVGPaS1pra+z5oBQ0ROxnJBQ+syI1MGV6yeYSvwvPMeCYsOsX0TVSEaT+hUewdm8Qh7wvtNeH9bvKSyQ8gy97R+XvFoYEkCSoQjPJCRDdVIFK/Rwg0UZPDYy9KnCBG2d5XuPfkjb+BGh1c9F7E89z4ETdLY1cF/KYKLSj/ebTZQWlweIz4nhPEhtx+hXyN+Bp/48KUF5LuwvQlMJlOWEcyVnE0aT/JVMVT0CbhEdSEYzbt8zXga/gVStKhJB2e5Ks80X+N4u26v+vns7ObRJSmKTAyJvgBGmO0yDjEh0brsb1Ryio+eLv78AkleclMikMV",
"part_9": "EOaDmHA7VkHsy/cEn4RQDHpM9KnQ4ljuiUZrEcmF7jkQ2QTpi3EfJ04GLUCG6HlnZ9Lh9UVPw5N4zg+69x0tcfoj4Ysa240ux0u+JPRMfkatHbbr/GN65HTTfXL4oO9LbpDkSJoq4FMstgMhhzGn3XUcH24w/pgZTLwRRSKTiAi4WMaTXvbdiSjyRchteGgAwR2LkkwkMizry+tAMJHe90RFOHUq/MauL70U+HuqgsSpck6yykB2FeiaOFV7XrlQnov3WA4iu0oRcrjisavixCHDVYbREUh1E3fPlQwEESw7dmh0SGK9keOZuk8kehOHIEar08OoihyqI6ff6WXesNUVO2",
"part_10": "TGDvUN8lhv3NHTsUN6omkrz/cNv4uDUe45GUfnbqN8HN4psJVyLpNwdzKlr4kUGeWLeSTEKuaDisyDWA6EkPF5j3OwgnA4FWmWImmih3KqDWX8RrKRkA5nWDCJmMYOQVNRGjuPWAmUJrQeuHOuvGiGbp8KRFnoPIENVhZR4GIsJD4kiZXDaJSI0ViGHdugE8ZYbO8nY+IM+2KZwQvT/guOuhMM/VheBH2az6fL/8zl9Q62YftTgApUcOTXmel0Gr/8959w92OTf0S/HE3D1/m5ye+E5B0LJ/kt4QTflrLgya9Z3ksOVf7ez2G/8p5+Sf9TfXW1tebjVvfO63Krv/wbiw/StpUvAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/+1Ty27CMBD8ldGeOXj9iG1+pUa9FNFKKFTBPqCIf2eJkQmFQ8UNCR9mNzuz69gaj7QZdqX/+sxDyd+0pDHRT/9b8j7REh+JAmxKfUSAh0MnkRVYSy3RAokcjOQBBlpY0+oaLDkb8LVmJ56VLNGbmZoZWk2czAZb2SxCiud+J/t6hNDEwYO7abrSFm94IfhjD+NheWYPfmCP1ZnalTzzpJ48GWYo3qwubMNqO19Qt7yyCqrlMUZzJ2Nc/9X5izkZ8SbYmy9W/6i6hyQ/pbk/Sr3Viu1wXW1FfbOrIy1onw/btTz2oUg4ngCQP2xtBAQAAA=="
}
}
|
codegen__primeintellect___2209
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nSome time ago Leonid have known about idempotent functions. Idempotent function defined on a set {1, 2, ..., n} is such function $g : \\{1,2, \\ldots, n \\} \\rightarrow \\{1,2, \\ldots, n \\}$, that for any $x \\in \\{1,2, \\ldots, n \\}$ the formula g(g(x)) = g(x) holds.\n\nLet's denote as f^{(}k)(x) the function f applied k times to the value x. More formally, f^{(1)}(x) = f(x), f^{(}k)(x) = f(f^{(}k - 1)(x)) for each k > 1.\n\nYou are given some function $f : \\{1,2, \\ldots, n \\} \\rightarrow \\{1,2, \\ldots, n \\}$. Your task is to find minimum positive integer k such that function f^{(}k)(x) is idempotent.\n\n\n-----Input-----\n\nIn the first line of the input there is a single integer n (1 ≤ n ≤ 200) — the size of function f domain.\n\nIn the second line follow f(1), f(2), ..., f(n) (1 ≤ f(i) ≤ n for each 1 ≤ i ≤ n), the values of a function.\n\n\n-----Output-----\n\nOutput minimum k such that function f^{(}k)(x) is idempotent.\n\n\n-----Examples-----\nInput\n4\n1 2 2 4\n\nOutput\n1\n\nInput\n3\n2 3 3\n\nOutput\n2\n\nInput\n3\n2 3 1\n\nOutput\n3\n\n\n\n-----Note-----\n\nIn the first sample test function f(x) = f^{(1)}(x) is already idempotent since f(f(1)) = f(1) = 1, f(f(2)) = f(2) = 2, f(f(3)) = f(3) = 2, f(f(4)) = f(4) = 4.\n\nIn the second sample test: function f(x) = f^{(1)}(x) isn't idempotent because f(f(1)) = 3 but f(1) = 2; function f(x) = f^{(2)}(x) is idempotent since for any x it is true that f^{(2)}(x) = 3, so it is also true that f^{(2)}(f^{(2)}(x)) = 3. \n\nIn the third sample test: function f(x) = f^{(1)}(x) isn't idempotent because f(f(1)) = 3 but f(1) = 2; function f(f(x)) = f^{(2)}(x) isn't idempotent because f^{(2)}(f^{(2)}(1)) = 2 but f^{(2)}(1) = 3; function f(f(f(x))) = f^{(3)}(x) is idempotent since it is identity function: f^{(3)}(x) = x for any $x \\in \\{1,2,3 \\}$ meaning that the formula f^{(3)}(f^{(3)}(x)) = f^{(3)}(x) also holds.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACj8N2gC/+1a247byBH9lYrgYKVYnmU37xM4bwlgYHcTYPclsBybM6I0hClyIlL2TAwDec17PiFftl+Sc6pJkTOWglir5GnmJrK7WPc6VU3702SZtVmTt5PLyZ+2xSZ/VbV5WebX7WQ+We2q67aoq7dVtslBgKWiWuZ3k8skCeeTelusiyor395u680tOfxYlx9yaW9yWdVlWX8sqrVc10t+gOaqzDeya3hHEqyst9lmw/syq9a7bI3F+/amri4X1aL6sd6AF1SSbF3Ld3ldFUu5ySDgfVV/rCS7qnetFMt8c1u3edVKr25zIa++XJVlviqqfCm4zAQWyyczFzuXi4uLuVSfpWik2V3fDA88W8ulLBYgA9ViUS7rt",
"part_2": "gElLj/jF8bftNl2W388QvNsDjMzKFBvJavu5dkdVovqGHXntu1mV2aynq6nd7OZvBR+yk1dLpsLOuW7vP2mgSkVjJOskdVfPk0/v5+RSJ/vdV9JdntbFjD3vfqwkbZWig9Zucvl7kK+r7dOXlaW93NlZGafyeilrPAxH/PmkruVF2JmqhvtyjM47L38Toxq9+d6JxnYrosPeSUNAzh4c/XLvHkh4L4VJOt7hgrmIJxLQfoUm91GbuumaCFWCiTwOt9CK42mC8HeLYNJ4DHkjmq/qF7w61V1u2v1ikuvKufYYtu0UiKBpF7pSkEyXsFe8EJKIZHLQX4lUyM//+NfuOBf63kz+fnv/9Rnm+JvymcUrmW9yYrqYiSyya9rGK",
"part_3": "gyXTkhCIZxmdpZl7araTXr5aymxawTuA+N2ync8mw+ZEBD8dlegbH9f9y1Ywe4272fT3br7++yzW2ZNx1j9fKiChaVEYvvYJCFJecGvfYXlRVf/PG+/XLfjPd9J7eT/AN0ORzPRlWSNm/GxnQJPxQEw1tu82x5P4YbxPs6Z12AzFWI4YeZ65rt1iw/rFvzuzV/tBZ0awE/ggPxH+l4KfKf1ay+eQCIV/l1tmvGOvpyhVh2mtrfHmZn91Z/aW2HZXdStFqF213e5cLwIMTMUfwdSVbi8ku6gV4fuJCR5e1Nsf0/Gr7qlHhg+zGOj9R33K3jvl+jwMcyVEovxj/uYuc1LFdt0d7veVyOn3uJABxpK75rJps8q1yjzdoHnaX",
"part_4": "nMnB7pJPGa2g4P+2h7mNRlvCDNC0aOkQv5R5w39zUu3KJZg7c48IWkS93ajUgGrQ1C5LfPwDAmv2A0M8D5LPN293WhR7TQn6BOWObrwCs8AemigoKgvtU1ZjOZotqhZWyaNrpJrvFcjuXbu+iQdMjDYngoAIbssVwkQMoMVUIE+l18UZevHSIgaFA1tfLaTaXq57g402BvJtm8quX4qmCV3rZ7/OL9FDiag4Q/bVcuY3Ojkyec8UxL683D5jvaX4DBt9+OwjnA1nViCoGtKXVHheP2fGhIPHrPyBg+Ruwq9zyNUIAf7mbBq655b03J7PBOswPZPAa1G9GZvVLeOInlOyw4biudHNYBWw+V33Vr1QH+wfUcDK5BD+umpFA",
"part_5": "KDdwOCyo88Umu5vykgbN3I5zl3q4wpwAbV64zUWl+TidTvkUbFcenFxmcDkfe45r+AyXM2SbZg0yrd2iB+O+S86nifZpon2aaJ8m2qeJ9mmifZponybaXzTR9kyayeXrybt379xcsKieptun6fZ/ON2SHNk2eTOfEHeQfZPXnxaT9v42X0wwvkw0+d92aT3BkDLRbHObwWLoZuCk27VrSbpvdPXzXP57lv6ib3+HGNrTGZqDDP2vZ0hG5lzmmkhdGIjxJRVjxERiAokkFGMllkRMKKq+d1ikF369UOt1cfMhOIQwyoF0TxWw1AU6QDCVicVAiVSsdy6bnXhDGVaFxlAihRoQ5PMuFicdonkVOM0Oio9PcLlH+QGtjuCAR",
"part_6": "OJQEisJdPAkgreRfJGk+mNTiSOJYrG4ltjyjlp6fC6FXzw8YiQMJQ64YRM+m6RQG5zSgGShT/dFkBdLasTX9TTmYqCSw4h+h1iLaBiJVBcbcjFS14d40JKPb8geQmKPF6CMlYD+seRMqwKSxSk9mGr6JJ5yTnlLs+B0/RMx0DHyLlU7YFpo+RN4VCCE8ilMOVyHwal+h7cCo/wBG5bmQysYG3nUH56GRXBdlNKpSSR+QKdBXRrOhEEkYBOUTenlNKSpMJg5G6kdCRxpGEuY5lu6x/fpe5iFANK7iQS+JH1mpeo1jwFAPAKrPoITEwYpBC2879N9iE3I5LSxRptZEIFOswi7Hl0Wih8z6IhdAksDLaeYKRYb5oWfMtwWT4",
"part_7": "pmBmKJ8ESaaYmWWpQcrrMgDNLQP6XaXbGfrXqVnTknO3te7ewR7U5oHqFj56DyINPg1I50LCQnaBkMWp6LZTQ2XMJzmR70zfh87TgcWB4JkX+q+R3TI+afwDZ+yFaig4yjr2ecPGYs8blYm0Arnq2HkwE6DTGMAEdEJqCxl+AWMJ3o7KJNLVW0NewlnmK2dU0vJPbGCqwGDK32ODAPqDRQH0DM3oUeAZg1aAzoB4DfhJAKqV6g44K2BmCntk7SsQFQCHGanbxvyMBUyyGDdJZNxqAfAJkjbXacQDhoxYRf42kHJnhDXxoKmDZeTNxHDzDoIgZkKdsmtfEJ9WgABlxCbaTGS9hfOENpV0C3gPd0ZogQFl+bKts1uk5Ap3E",
"part_8": "G0dmG4xcaBNpIrAMIOgXaGzhChK+TRkSuHDjceAajoA96Thpo08MciF+wRr+Ez6m5Gwd4b9gT0VrRjpIjg7ofn5oZEIDgjH+YK6ELmaaL2a97o22358n+eaNd3OsexY8f7NdG27qqVByIgu7vI06Pn3A89xcdg9G9OcLB29swUq+/HC11ujoGjumg2MCzs3tk2YjdyGFjOm9gub/oGDz0Wq9td/k4GGOPjbUfVB8exE3v2rOddDRbrJtRtbw4sgY6djp9LA88BAVUSWIVZ4AYRAMehdL+CvgBLqErGy5wbjKsUjAB7Cgm6FCnlR5qYXNOTlhfHM9cISsieVo1EREo1Ket4g9HYrrGhR01jc1EpzuezQLT65KqIbgnCNCR",
"part_9": "RuVaKk5tQqXi3BooIBHuQmVLzEkUH30n0XMnMGifEA2iUOs91nnRj1VNv2eq96GeCq2DKT16pA6v1LZEsQNoGOnMC8QlEviE4pDmpQoH6ncT7lMHOJdomoA+cSkCDWx31gFkHsyG5PSu4hDNNRCjcOoOPr4awwDDOsKYKxMNdUqwtOr2yKGoWhIx2kyi1HeATxDWUxEYpxr8wPUhpFikQz2dbhRpI92DOnowIZYj+8icjmImwTNMLC2WwMVewRetKFX2VLaPk3FpnDBW2EKK8xTpM73hRY2NgrfKjDQC7BUAdrAL2GJAHFEsmxRCSgtcKwxVUJQ6xO+iQkWsWkEeSaTiYQBPPVbXjJ72QvUNyLCnhxRXBXSR5xocPBCoI",
"part_10": "JXadfxAUwBOSULXVvRJkJJOT12M0+EpqXtt8FXJwTMn8lVfSrALMtPtueaZfqTXaj4X036w61+nnG2wA1CN9R3e1ESHXtQY96KGUxXqwL1RQD3x5YWDG3114UY5X3sBoukrviCaTAqP4IZUAlKgqAJF60BPtN0R1+hLAl/PuiFLInSHZB2uIq1I5q6OgZG+OomSfq4z+gbFJxLGeoSPFaGAMMAaFC/fwujBPNH5DsXOHpb2ZaqVneqZn0d0rbr+3UU3GXm+GxF1GopcEjM5PTd0KcqYviICB32mmyFNXxCemyc5N1pfC8TolBgpaiu06rh4+AgTBVEapb71vdOPR8GR41F34nrD/2nbvN1VxV93+eSS/9b0+d9UDDcBqisAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2213
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nPolycarpus loves hamburgers very much. He especially adores the hamburgers he makes with his own hands. Polycarpus thinks that there are only three decent ingredients to make hamburgers from: a bread, sausage and cheese. He writes down the recipe of his favorite \"Le Hamburger de Polycarpus\" as a string of letters 'B' (bread), 'S' (sausage) и 'C' (cheese). The ingredients in the recipe go from bottom to top, for example, recipe \"ВSCBS\" represents the hamburger where the ingredients go from bottom to top as bread, sausage, cheese, bread and sausage again.\n\nPolycarpus has n_{b} pieces of bread, n_{s} pieces of sausage and n_{c} pieces of cheese in the kitchen. Besides, the shop nearby has all three ingredients, the prices are p_{b} rubles for a piece of bread, p_{s} for a piece of sausage and p_{c} for a piece of cheese.\n\nPolycarpus has r rubles and he is ready to shop on them. What maximum number of hamburgers can he cook? You can assume that Polycarpus cannot break or slice any of the pieces of bread, sausage or cheese. Besides, the shop has an unlimited number of pieces of each ingredient.\n\n\n-----Input-----\n\nThe first line of the input contains a non-empty string that describes the recipe of \"Le Hamburger de Polycarpus\". The length of the string doesn't exceed 100, the string contains only letters 'B' (uppercase English B), 'S' (uppercase English S) and 'C' (uppercase English C).\n\nThe second line contains three integers n_{b}, n_{s}, n_{c} (1 ≤ n_{b}, n_{s}, n_{c} ≤ 100) — the number of the pieces of bread, sausage and cheese on Polycarpus' kitchen. The third line contains three integers p_{b}, p_{s}, p_{c} (1 ≤ p_{b}, p_{s}, p_{c} ≤ 100) — the price of one piece of bread, sausage and cheese in the shop. Finally, the fourth line contains integer r (1 ≤ r ≤ 10^12) — the number of rubles Polycarpus has.\n\nPlease, do not write the %lld specifier to read or write 64-bit integers in С++. It is preferred to use the cin, cout streams or the %I64d specifier.\n\n\n-----Output-----\n\nPrint the maximum number of hamburgers Polycarpus can make. If he can't make any hamburger, print 0.\n\n\n-----Examples-----\nInput\nBBBSSC\n6 4 1\n1 2 3\n4\n\nOutput\n2\n\nInput\nBBC\n1 10 1\n1 10 1\n21\n\nOutput\n7\n\nInput\nBSC\n1 1 1\n1 1 3\n1000000000000\n\nOutput\n200000000001\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIACj8N2gC/+1a64rjyBV+lYMhdHvG7dVdcpNOiMyGHQjJggIhrDc9slxui5ZKWl2mxwwL+Zu/IS8QyEPkMeYZ9klyzqmSLd96Zp29TIKr7XGp6qjO951bVcG8GyziJq5FM7gdfFmluXglG5FlImkGo8GylUmTFvJexrlAARxK5UK8HdwGgTcaFFX6kMo4uy+rIi9phajI3ghoVgKWRZYVT6l8gKRY0A/KzDORQ1vTE4ngyEMV5zk9Z7F8aOMHHFw3q0LezuRMfllk6ySuyraGrHgjaljF+bytHkRVwxtRrSFvk9",
"part_2": "UYvhAg6lIkaZxla4gXRYWitH5PHJ/y+BHHn9JmBau0huJJooBc1GPo6WlWqXykn7ihJSoBMX4LiQs3q0oIWIhEyAYQciUWKXZRuOC1++qWaI9biGFeiXgxgjpua+KG6iBZCVELRv1UpQ1CWhAUwlshhxK1LRngMn5TkADMBr8T8EW3OCLoAZ4NIK5RUd1UZEV8NRNNQxCuwiu4Zv3DEVxF+KBRDOH9v+FqigMKynAMf0TlfUbpDp6HgvnAvGga/EG6TVGO0MEViLdxXmZi1InOBu//Hk3DCGFVokQ/KAP1fQFPbNZm",
"part_3": "T+VRJcRt14Qjbb+RGmeLbqz7EKdyvBc4K1xC3r+bfwtliq6ryUR6SRyu+8N9L+Fc0p9TWjvDPKYNDsgxhKJOF6Ie8Wi9QsRSxNV8zWoxHHXQ9IiOdOSntDDFVsngqhZzo2abxkptD2jJQPfm+mhLRrsnoAPtiD2qTh29S37AIVS0JqsziYJp5mP4E+VBHr9N8zYH2eZz9B+F5zbSk1jSEklRPP4a/ly0PBDXdZsLlUU93Tgli4ZZPQKCrTO0AoJY05psln0XdSRRuMubQ5OzrSW0MktzzJdFD+h2QREnq54f2CwzeU",
"part_4": "PtlSzbhns0RLmwTKu6gSyVokOWkgyylA3GGCWcLOSNwJq37lKPySKwpErnuv5s8/n5FFYJmAn5gLVJK9SrLgpRy6sGEy0RyMw0jFF/egOIK9RO6rdlKaoECzt8Lh+ytF5B2BWCw6loyLHAVeFwdjocd5apBapcKNNslHdB3ggOCU43nV4jnUnXJnz3t38dnaJx5DWE7/76D+a2dd+zMbEtphSvW3tebdOTEGNFrz4AuFSoSoWq7AM+NnUAmLOZEBZSHCTvEbi6ilDwjuG3tIFm65HeNNsKY2AXrcaJaatBVRrCX0zr",
"part_5": "mNV0cu8mvaoDmYipdi4KoETk/Ydf/kWWYR2lPXSZ4iJYB7i6YtopGc+5mafN1mLI4P0/X74cw6uGqgdW+qWoMLXozbZWayapxGpdYNpgsIo4r2k5VvbKc3ra+qn4h7bp5yKeRyTvw8/XoN0Sw5sxIltyXYope3h7pjqzeWlETsO1jb72z9VuVmv9XBdmMgzDKJrOpAcOmDNpggX2TDr0loI7kxY9bMSnJGQaSlj9WmZf3O+LR0pcS9PSGFvbtqNmO2x2CakK01OKe82cygIetTjU1liKMcBa9KtiigNYcYuspfMcV/",
"part_6": "pmUdCq9Pf74onm9NGtO6nROpVo2krFK57jxBhPgOxsIRM6EC7EEq2byushntgAWw13CtP1UA3EODDHb4JfQw3xyYEUINZav0ctXarhuzssmOFs0JtSK728IzN1zyLbeSE6eGF+8EIt9kSSnoiMsSTN8UtQ87i8RrONOjLjusxS/NWsSpQtUbb8CNlHNklzrWeHZHAaz7YWqbBrGi9emLZ6flqlGe4fcINCvwKzBxrJwnUGL6EawmefgbWdSWTzGwbz9ho3iRheoOwNkhruiIRbkXknMt8VmW5Fkk4k6YnkWObW5FFS",
"part_7": "+AJNgWh4ZezPVX9K/WTHs+qtX97B454LyAz5s06qthIcy9cZ21DFHQYkmxuDsalwBJ91/F6uI5fryOU6crmOXK4jl+vI5TpyuY5criP/l9eRbpF6cPvV4PXr1+rENpOXq8nlavLzXk1mEsNx8PVogMfqBsNz8NW72aBZlwLDAaOCs+Nex/1ghCPsBjWp07zL8y7RKdNRAUsXKg9Z3OJR3BO+j4bpbFMSeh3LPKrBP0NDpDV0CpjAbj05SqZfWL6/1j2d9GsHx0nZgXUuLRtc8PDXBxsmitZRFaZxtuEMo6PR7x3V4p",
"part_8": "5hqAgjYIr/sJ1cA9TaNvYnYJkbTx03nH8OrZA0HrYIW6hbFHV8jQ7RxomeFQQn8Exc17DOQ6TaKVwf0xgxWAY4xgF46wRg4xMFeyKIP0W09v+Sae1nK55jBW7wKcKemI7pTizPtTW+g8iwDXfimME59WfTnqPxPHauXlSysAjTDmXaYGJFNj8Guuf4jmW6/uQsw2PljKhc4S6NjZ+5fNEU1m/EzZ+wE6BH/cA8o2nIHZ7lUrw1AG39IVOAwEdCdAxwwMEPbaATN3Bta2K6buAf98nE9LzAOmdPIMwKXkgdxQrxhIyX",
"part_9": "MWM/JC5EnzFHGv6UGUVKOFK2IEF6mnJHLYWoXA9sZEN+8QPwYEI76cRwTN8JfNcxJ8d5OcbECyaudwYvtnPEaMMOj3aXoqiRMvmQ/1gm0j7RLyoOWpjcNFUfWoYi0QbfBo/c4gCSdGhPCgIPg9D0HNs8cXjzMRDdYBKcs4crjzEezYiAqsFQeVA5U3/CLh6VvyIVm1PlzUhHo1pJe51cg2dQDwKXMgy7AUwotgLbcyeGgYnmWMeJmb5rWaZ13tkx4jSaRspzOoCiqc4u3VSkKq9wj1hFTFOfJziZpl32qZCO2MuUVj",
"part_10": "64DgR8uiDX2T6HpGXZluEicPt4IGKIYvXwzzhx6Bzg/Cf02j+hQqbJ6exROaiySNGJVKR28RpubMSeUnbgs6NvAn5cAuhaEAR88vZcx8EdyHVd3z1RzJG653j+j8krfLZtGPTOvFTSLVX5PkjAdb3ADCbnMDh58PzwjWUr0R3Qz9wJf7x2yG7/6SM5nnslO27aE6rOOU6QA629i5/5IVbuf33V7MfpTxMu4U/QdvmcFSjGOdv0ab0/2Fn/58vz3r3+DOV21xzb/oF1nyKr1HxN/+23vm9l+k0rBrdN1Ypv/wNoP9vtNywAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/51Sy44CIRD8lU6fPfCawXiET+C4GC8a18SMZoTDxvjvdqMzGN34KkK6KKppmnDEdb/L3XKR+px+cYbHiJtun9Mh4gx+IroR/h+ENxFjJwUoAUYUKuA6aaVECREnQOWCfzBIoHFRK2rGp/7gA01PIXAHjqLzjqUiD/AXmyt7zIiz5MjOCMxI8oUENgZ2so+KtRYaA1NiugWrQVuidqqUVqKRyur7lodLU9Svmx29Xz3M6PnkseecsMvp5nPUg/QAo2tn9Qx5cy/ZGNkaa9WoqFpJvkp+6pifcIKH9Ldd0U/uM4XTGWPV8u/hAgAA"
}
}
|
codegen__primeintellect___2214
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nOn February, 30th n students came in the Center for Training Olympiad Programmers (CTOP) of the Berland State University. They came one by one, one after another. Each of them went in, and before sitting down at his desk, greeted with those who were present in the room by shaking hands. Each of the students who came in stayed in CTOP until the end of the day and never left.\n\nAt any time any three students could join together and start participating in a team contest, which lasted until the end of the day. The team did not distract from the contest for a minute, so when another student came in and greeted those who were present, he did not shake hands with the members of the contest writing team. Each team consisted of exactly three students, and each student could not become a member of more than one team. Different teams could start writing contest at different times.\n\nGiven how many present people shook the hands of each student, get a possible order in which the students could have come to CTOP. If such an order does not exist, then print that this is impossible.\n\nPlease note that some students could work independently until the end of the day, without participating in a team contest.\n\n\n-----Input-----\n\nThe first line contains integer n (1 ≤ n ≤ 2·10^5) — the number of students who came to CTOP. The next line contains n integers a_1, a_2, ..., a_{n} (0 ≤ a_{i} < n), where a_{i} is the number of students with who the i-th student shook hands.\n\n\n-----Output-----\n\nIf the sought order of students exists, print in the first line \"Possible\" and in the second line print the permutation of the students' numbers defining the order in which the students entered the center. Number i that stands to the left of number j in this permutation means that the i-th student came earlier than the j-th student. If there are multiple answers, print any of them.\n\nIf the sought order of students doesn't exist, in a single line print \"Impossible\".\n\n\n-----Examples-----\nInput\n5\n2 1 3 0 1\n\nOutput\nPossible\n4 5 1 3 2 \nInput\n9\n0 2 3 4 1 1 0 2 2\n\nOutput\nPossible\n7 5 2 1 6 8 3 4 9\nInput\n4\n0 2 1 1\n\nOutput\nImpossible\n\n\n\n-----Note-----\n\nIn the first sample from the statement the order of events could be as follows: student 4 comes in (a_4 = 0), he has no one to greet; student 5 comes in (a_5 = 1), he shakes hands with student 4; student 1 comes in (a_1 = 2), he shakes hands with two students (students 4, 5); student 3 comes in (a_3 = 3), he shakes hands with three students (students 4, 5, 1); students 4, 5, 3 form a team and start writing a contest; student 2 comes in (a_2 = 1), he shakes hands with one student (number 1). \n\nIn the second sample from the statement the order of events could be as follows: student 7 comes in (a_7 = 0), he has nobody to greet; student 5 comes in (a_5 = 1), he shakes hands with student 7; student 2 comes in (a_2 = 2), he shakes hands with two students (students 7, 5); students 7, 5, 2 form a team and start writing a contest; student 1 comes in(a_1 = 0), he has no one to greet (everyone is busy with the contest); student 6 comes in (a_6 = 1), he shakes hands with student 1; student 8 comes in (a_8 = 2), he shakes hands with two students (students 1, 6); student 3 comes in (a_3 = 3), he shakes hands with three students (students 1, 6, 8); student 4 comes in (a_4 = 4), he shakes hands with four students (students 1, 6, 8, 3); students 8, 3, 4 form a team and start writing a contest; student 9 comes in (a_9 = 2), he shakes hands with two students (students 1, 6). \n\nIn the third sample from the statement the order of events is restored unambiguously: student 1 comes in (a_1 = 0), he has no one to greet; student 3 comes in (or student 4) (a_3 = a_4 = 1), he shakes hands with student 1; student 2 comes in (a_2 = 2), he shakes hands with two students (students 1, 3 (or 4)); the remaining student 4 (or student 3), must shake one student's hand (a_3 = a_4 = 1) but it is impossible as there are only two scenarios: either a team formed and he doesn't greet anyone, or he greets all the three present people who work individually.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.0625
|
{
"part_1": "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",
"part_2": "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",
"part_3": "ubi44Kvv6u/Nmacz8ab63vzK1OfMVCaFfQL/PqUBk4Jq8PPq834HYAsXS1gjn3y57sdOeeVIrFnfLXoX8rF8RR35YSPuWHHkxdnktQv7bKIkcks6JA3eac2AFrwq29UanI/C9pg+XzjrSNK3tpDw458DsWqPeASe1psL84V1UeVA1ytTeuseUiyPdW781uoK347VWpVF3Q3QfuRShbos2mWF7Up/Lvl2tEQJ1NvI4d9qvewr5i5kguO2fmR2u9p18TFRYBLWL7Y5KNCzmEPyyMOzyattEs4m46D/4UOxghqdC7vyYlbHszowvgmNZ3xVfUEDuTvIqCMTa0FgtpvyWe3hfWgifOIbvg5+enOKzZSfmEzL862MyMrw948dKV+PdP8CFLKD6xiAnYzaVaSO3cSqdFjbehHldUc514hF51qk7qUx29hGIkKygTkr3kbm0njnKkWLgvxnib6xteuXu23x3rYY23y7TZWrG5eu7Umj7f7edh/bg6e29w/NDhBn21fR1MTnI4nhnsQQEsMnJe53FvsypzBkJ3Z4FrLcrwbK3fUdQ4ErBhoeaR",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2223
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLet $n$ be an integer. Consider all permutations on integers $1$ to $n$ in lexicographic order, and concatenate them into one big sequence $p$. For example, if $n = 3$, then $p = [1, 2, 3, 1, 3, 2, 2, 1, 3, 2, 3, 1, 3, 1, 2, 3, 2, 1]$. The length of this sequence will be $n \\cdot n!$.\n\nLet $1 \\leq i \\leq j \\leq n \\cdot n!$ be a pair of indices. We call the sequence $(p_i, p_{i+1}, \\dots, p_{j-1}, p_j)$ a subarray of $p$. Its length is defined as the number of its elements, i.e., $j - i + 1$. Its sum is the sum of all its elements, i.e., $\\sum_{k=i}^j p_k$. \n\nYou are given $n$. Find the number of subarrays of $p$ of length $n$ having sum $\\frac{n(n+1)}{2}$. Since this number may be large, output it modulo $998244353$ (a prime number). \n\n\n-----Input-----\n\nThe only line contains one integer $n$ ($1 \\leq n \\leq 10^6$), as described in the problem statement.\n\n\n-----Output-----\n\nOutput a single integer — the number of subarrays of length $n$ having sum $\\frac{n(n+1)}{2}$, modulo $998244353$.\n\n\n-----Examples-----\nInput\n3\n\nOutput\n9\n\nInput\n4\n\nOutput\n56\n\nInput\n10\n\nOutput\n30052700\n\n\n\n-----Note-----\n\nIn the first sample, there are $16$ subarrays of length $3$. In order of appearance, they are:\n\n$[1, 2, 3]$, $[2, 3, 1]$, $[3, 1, 3]$, $[1, 3, 2]$, $[3, 2, 2]$, $[2, 2, 1]$, $[2, 1, 3]$, $[1, 3, 2]$, $[3, 2, 3]$, $[2, 3, 1]$, $[3, 1, 3]$, $[1, 3, 1]$, $[3, 1, 2]$, $[1, 2, 3]$, $[2, 3, 2]$, $[3, 2, 1]$. \n\nTheir sums are $6$, $6$, $7$, $6$, $7$, $5$, $6$, $6$, $8$, $6$, $7$, $5$, $6$, $6$, $7$, $6$. As $\\frac{n(n+1)}{2} = 6$, the answer is $9$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACj8N2gC/+1Z627bNhR+FU5QAXtRPJG6B+uPYRcgwNYO6IBhiFJXsWmHmUypItUkCwLsIfYAfZY+yp5k51AX261cNNpfO4klHpIfz/nOjUAerGWmM8W1dWb9WokNP5ea5zlfaMuxVrVcaFHIucw2HBaASMglv7POEpo4VlGJtZBZPi+rYlMiwqsif8eJvuZkVeR5cSvkmiyKJT5gzVXON6RW",
"part_2": "OMIlIFlX2WaD4zyT6zpbg/BeXxfyLJWp/JlrYkubXHGSSSJArzWvZuT7Qiqx5BXJ8pyUvNrUOkMlFSn6VYrY1Ca6MPuFJDm/Ews8rbwWC1JUsN0B0CUoJxeZ5hL+UKcNAhQAxMmVWBPF39ZcLjixS3tGfioqwu+yTZlzh4gVYJPnxLMd3ChhCYwuqEOYQzyHUPPNzG//3sv7ZTh7Cdi/AR85l2t9",
"part_3": "TYoVAAq1PfxWgKFAApyXpotloYn8yp71DFGQ5vwtEe3zpn3urjYckjITFcKDD8WCqxn5nZMFsoje2No6KefCIeX8QZzQRwdQAEQZwc0pCsr5zdQGOFVfZVWV3SOkIehcq84I0H/JV0LyJcmUwZf15oo3x8MyDqHAJcKKGZ85xL4hp2DBCaEtjqo3CGI0g1fYhooObk1TWDF/+PO5eHx9A9r9CRDI",
"part_4": "zh9FTbKKk7V4h/6R6EIw/SNtOitUawY+WiMweK6zdxifqAMctKqyxYOcyBM6fXxgj4D4SiBnxmEt5gYYAbrzrFpDnBS1LmsNipNNsaxziMgkiZnve4Fnkwn4BHOu3Tpt9E7lKX7OJWw0byjCAClkfk9yIBXDVmfChDzvYh7V/fB+0seDbJ/UfR3aUwf9sORqUYkrcArkRJuCJikVpJBhdbajwEuj",
"part_5": "eq9BM0S/AyF5f+yH9//+/c/nOP1iMp0Binb1+bHJPdVqZPhJpbfVLZUJDtoJf3ciCHdmqLs75bluwCLXbU5qz3pRaN5bft6QtRKV0kS1BQAkEFsYXzYN7WGTPQxm2dQbE8JlybMqg4gx++9xuyl1dlc4LoEF+6ItFc2gLRrNoC0l/QzrB6wrJu3gs3u+8Jy9GdbPfAywB23KWRuxUG7A16phKcRF",
"part_6": "5ivafwv6ofmKPzvb7p2R79RADEEJDpuCDNVd3QLrkJd20oQRppDACOgrqtLQmkwfuIdaoa6LOl9iRkqNAlC+yGtsLdhJYG2B4YI/L4pbnGtbXZdEiFNxXVdNuEDf4zPomBVfQaSAz6E//vLyB1CxD2/EyoXScyX+4jBBXfxQFK/mOGFayiX5mvSrcKY6OAez0KQEpjeE2ZpPtuinhE4x1nSDfGGK",
"part_7": "7SWAgLWTSSdEvAlOsemUPCOg7xRRoZaTsgA+J9Ihdw0OdMA78hyUNqNUt6YjQXCDMLPPCMMV7v6KBsgcK+E42R3kGFXuyDd4eIOi+P7WftNWGWPYrq4dPxenxrxm5aoXObgQNrHpAF0Qv1vGTraMdYhih7Be1hAJvO1uZdjPPuFwUWyuUOuqp1CSb0m1b6TbMygNe1A/SNW/GdlHO+gwW5PerxJZ",
"part_8": "Qh17tVFSGWmn4+7s3ozJZtkabhJogv6BBANZdwAwO8SmbAxt1k7wcdKTIPDIPvLQW+hKo0aLicJWiVSavESIKSSVKnOBF05dQRuEcZuDxyvo8Qp6vIIer6DHK+jxCnq8gvZX0A5EWWcX1ps3b5oOl8rjdfR4HT1eR//vdTSVkFLWpWNprjSkmHXxkFr6vuSpdUZSy2T4vM1dCy4zllG6mfRS0McI",
"part_9": "my7dSBMjhXvOlwP5g0DQc56MBK1pCKrvUU8HHMSjTwdig0Ds6UDBsIVJMMI45seDaGEcegFLXDbGA+Yz7FE/icIw9EbQFx7wa+w/HSsadkUYshGKDRPIAo/FI8ItOaCaz7xkhHJ0OHy9yPWT0I+TMSEznPQehUbs+iO8Qb0DOvpenEDejkA8UE9iyoIwGuMWOpx0kRvRkPlj4pkOB3QCHAKL0Rgd",
"part_10": "h8M6DCkNQjrK1/EBqz3qszAZg3ggvgMWR2HsRyPK6nCl8cHPCQ2TEfEYMq/T5BNUN2JJEoyqORgpw5EeuBRU9ca0O48NhzqjQQT34mBMBYqZxw40BY8x4HVMIEUH2h/13DBhwRjHB0l8oHSwOPCDKKAj0jIxn+GCxGIoH3E4pkckceINeyqEjhi5rAv9S/wvtZrXUrytuXWmq5o//gexyKFp5h4AAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/22QwQ7CIAyGX2XpeQcoFMpeRYwXjZoYZhgclmXvLi4GONhLvzZt/z/d4B7nHK6XFHN6wASbh2d457R4mIaTB+m8Dx7GoSA2FBUV6tZWFd0RtWyrdND5i3NOnRISsjWsbbuhpGMUugkoIQitaOooyTJq6vxYrdiVuc4hIxk28o8b5X5+dhhhSevrVn4Qc0n7B81oUEIbAQAA"
}
}
|
codegen__primeintellect___2233
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nBerland, 2016. The exchange rate of currency you all know against the burle has increased so much that to simplify the calculations, its fractional part was neglected and the exchange rate is now assumed to be an integer.\n\nReliable sources have informed the financier Anton of some information about the exchange rate of currency you all know against the burle for tomorrow. Now Anton knows that tomorrow the exchange rate will be an even number, which can be obtained from the present rate by swapping exactly two distinct digits in it. Of all the possible values that meet these conditions, the exchange rate for tomorrow will be the maximum possible. It is guaranteed that today the exchange rate is an odd positive integer n. Help Anton to determine the exchange rate of currency you all know for tomorrow!\n\n\n-----Input-----\n\nThe first line contains an odd positive integer n — the exchange rate of currency you all know for today. The length of number n's representation is within range from 2 to 10^5, inclusive. The representation of n doesn't contain any leading zeroes.\n\n\n-----Output-----\n\nIf the information about tomorrow's exchange rate is inconsistent, that is, there is no integer that meets the condition, print - 1.\n\nOtherwise, print the exchange rate of currency you all know against the burle for tomorrow. This should be the maximum possible number of those that are even and that are obtained from today's exchange rate by swapping exactly two digits. Exchange rate representation should not contain leading zeroes.\n\n\n-----Examples-----\nInput\n527\n\nOutput\n572\n\nInput\n4573\n\nOutput\n3574\n\nInput\n1357997531\n\nOutput\n-1\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACj8N2gC/+1a227jRhL9lV4OFpEQWeBVJIX1Qy4DxMBgPMjMPo28HlpsSZ2QTaW7adkZBMhH5APyLfmUfMmeapIa2UMtYsL7EqhtQGJV9emqUxe2AX908sxkmhtn7rxRouQX0vCi4EvjTJxVLZdGVPJaZiWHAURC5vzOmad+NHEqJdZCZsX1VlXllhDeVsUtZ2bD2aoqimon5Jotq5w+YHNT8JLVmp7IBJK1ysq",
"part_2": "SnotMrutsDeG92VRyvpAL+TVXEOcT5rvebMreYQu/W25gyZnKDGfVii1rpbhc3rP7qmZZUbAfZbVj2ToTUht7yk2tCs42mWZCLhVHqDnTFSvr5Qb6DEYV06LcFmJ1bzcss2JZFxnFrSdMGM1WKrM0ZAXbZsqwHcAkXxNJAIOLdt9D3wRMyBOt6xJGOOSGwxROGL7makoBfs8LkYEU+FOrJdfwEuwJuaqU3UM0gl+5FF",
"part_3": "yxr6SpJIWsq7Izsk6y7KaqTY8LT6AHYHCxrJSqdlP2GjbNcWSuO5oadc9BOwHkJjx+yyWTdXnD1YTtNgIkLyGGsroxOBVhrVAsbf655tI0GDf3TO+y7ZaKgd+B7wLZ2FUsF9ogcQZf1pQLAQrNlF2ubDgWptJaEIu3WVHz1tuScxufRj4rmYs2m5/7fhj5PhAyK7M7UdblHn7KLgxlFWWqMiTRJsjykmf3/QWAwKs8J",
"part_4": "wScbzNrc8/klH3Hi23LMUoj54Yr9AF/ShYPPf8HldNCntG6kNva2G8kemeLSCHbBeGDDErD//Dtj9///PW3p/sBEpoWLbhcmw2ZN2XA5BeaKd4mu6lYcLMTZoNcKnuALQmfmPDc/0QT6tQCc+KWN5CPdhM0yyuu5RemCwjx3OPozI6an7mCdnrAyWVtDkm5WNkAe5qo5RMuf5ZNOIUaQjnCkUmTe9GUlGrbfU/ivgR1",
"part_5": "M1G6Cpyg5mHD2BnzrHuXtHsnNO80z9jF7zZwSm+qusiP1XSXoor4qDRvHM8Qj+3jZrK1kkf9Swn/jKXjTUy9O2UvH1g/Smvrqqw+JfV4Ql/eZRjZXLcptTW/kJEfW1ZttvEY+zbbjTKM4uBQG0RxeKD28JymcRR4h0ZnXtdEgsz2E0KbXDQEUU5a15sUQqAwpIvaRkVvF5NXhEU/NFr1/iXZvRMJR3FTK9nWS86neNc",
"part_6": "qvuKUeHr1Lpof+Q10yDO9Lb4BSxwF4CcJ+1bcooHetHhf01Ff1cipYmzOQHplxPJaZD8u5Kv2TTtnb+yrlgXTcEo8tQcs5IunL/b28tW/311cvqb9cBCVJuRojNc4w5LsHOFl+cgdNwJwdU7NMpLvz7yrTpghlnNGjNMjFbNg3YgYYayM5PjM6zBpLfcoogOhJdAx//TZ+TlzLbNL9i+ceLCPVku3fD8XV+xLZh2xn+",
"part_7": "JLb77/ftWL+giqdVw0Utg1AgrlwLI9sAvv0/lk/dAFkhx4YQ2a8hmUnBfsu5ev3rz8/m2HQQmy+ShRTOd+R+kLRMbeGhTxuhN4c/YKE89eO6xCdxr/k6adeq3K9om2mcGX0XhKG7ej8Z4dOrShsSOh2fKZgffIYKpxSTM9SP7esIBLozLbjgTN6IfbxuMu9p0Sho/0Ocqd6r6LH4iaBvnrSqI7KISmI1qd0DRucRvD1",
"part_8": "ok9adxZ4Xf6Q4WKp6MR74TpcesmGUAy0u2znREEwGVODjjWq8ajpmnG6HzrMrreKIjw3A6K0w37dMM+3bBPN+zTDft0wz7dsJ/hht2BaGf+3vnw4UPzbvx0GT7dtk+37dNt+299215I9L1zNXGouzEHnPcfF4653/KFM8dJdgxdtwPGmUBi42yUNA0pJhJXzTxr5BiLJP9lwv46mJ2efWh2jD4Z7mDa9oGeeQM8pNXv",
"part_9": "o9UM8NLH6ucwJtUAwHCWHKERmgGA3vPx54VBNIuT6AiHnXoIj6EfufEs7cVNrW4IqIsCPwZqdQNAoxlF2E+q1XlDiv3R8o9U/WM7LxhQEUG7/CDu56YzSIMhcyCJ+rlJng4Vx66Lv+xnRwZLHAeN2h1AQhRGXuSliRslYRJ7aGM/dMNgFgW+n0QJasMPUz9N0yCJ3Mhzj822Fib4izADXA1RUnEEZNSyl6bezKfAZ8n",
"part_10": "Mw0hIfT/1Q9/3ogizMpxFaZi4fpSk4M6L3SCZ+WEYJUHshhH5kQAqdZHZOIpnPkYsag2o/T3y/z94yMg90hpDZqN7rM0GpClyia4j71Oo3OGd+mA92ziP+tez4afps0FhVEXHahQVOgQQl5JjiFANuf9gn38c0h9Q6uih/nQns2BQufe756UDatN3+1Z/P/ler/GQCI53bAt3Rf/koa9rKX6quTM3qua//BcxBX/IJSIAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACj8N2gC/22QSwrCQAxAr1KyrjDfjtOrGHFTUUGmMk0WpfTuTi00szCb8MjnhSzwyCOn4UaZ6Qk9LAiv9GGaEPrmgmD/BWJCaBsE47qzkFPehC4KWx+MoFZVyQeZ07rqUTtcNxqZqlNO0maL1xwUf14nvHkFdVQy6IMUqoW6iHfvCi1MNL/v5RmZS1q/d8TxSyQBAAA="
}
}
|
codegen__primeintellect___2236
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAs you know, an undirected connected graph with n nodes and n - 1 edges is called a tree. You are given an integer d and a tree consisting of n nodes. Each node i has a value a_{i} associated with it.\n\nWe call a set S of tree nodes valid if following conditions are satisfied: S is non-empty. S is connected. In other words, if nodes u and v are in S, then all nodes lying on the simple path between u and v should also be presented in S. $\\operatorname{max}_{u \\in S} a_{u} - \\operatorname{min}_{v \\in S} a_{v} \\leq d$.\n\nYour task is to count the number of valid sets. Since the result can be very large, you must print its remainder modulo 1000000007 (10^9 + 7).\n\n\n-----Input-----\n\nThe first line contains two space-separated integers d (0 ≤ d ≤ 2000) and n (1 ≤ n ≤ 2000).\n\nThe second line contains n space-separated positive integers a_1, a_2, ..., a_{n}(1 ≤ a_{i} ≤ 2000).\n\nThen the next n - 1 line each contain pair of integers u and v (1 ≤ u, v ≤ n) denoting that there is an edge between u and v. It is guaranteed that these edges form a tree.\n\n\n-----Output-----\n\nPrint the number of valid sets modulo 1000000007.\n\n\n-----Examples-----\nInput\n1 4\n2 1 3 2\n1 2\n1 3\n3 4\n\nOutput\n8\n\nInput\n0 3\n1 2 3\n1 2\n2 3\n\nOutput\n3\n\nInput\n4 8\n7 8 7 5 4 6 4 10\n1 6\n1 2\n5 8\n1 3\n3 5\n6 7\n3 4\n\nOutput\n41\n\n\n\n-----Note-----\n\nIn the first sample, there are exactly 8 valid sets: {1}, {2}, {3}, {4}, {1, 2}, {1, 3}, {3, 4} and {1, 3, 4}. Set {1, 2, 3, 4} is not valid, because the third condition isn't satisfied. Set {1, 4} satisfies the third condition, but conflicts with the second condition.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIACj8N2gC/+1a224byRH9lQ6xQaQsLbC75yqsA+RhH/Zls4ADBIHpaMfiSGJMztCcoWxB0AfkP/Jl+ZKcU9U9M7alJCb8Fml359LTt6o6daq6uPezVdVXXd3Pzme/7Nfb+qemrzeb+rKfzWdXh+ayX7fNRVNta3RA07pZ1R9n56W381m7X1+vm2pzsdu32x1neNVubmvT39Tmqt1s2g/r5tpctive0Oftpt6aQ8c3dkHL9b7abvm+qZrrQ3WNxrv+pm3Ol82y+WNn7tqDede0H+amasyhWa332Fi9wpxNo0+YYXdjPqz7G9OYpl3VHbqu8PzCWFOvrvG+7sxlBZFWpjL9vq7PzF8xbbWvzfX6tm449RpCX9d7s5LB2o2LdOuu5/baqzj7mfmxuryRZ7M2NxWWM7fV5lCb6uJ+/WCqrmsv1xW3Jpta92eU5S+17AGdoWrzihPKGrpjTLBemfXV",
"part_2": "J1qDtNR9Jzvtqn7dXa3r1TkGQ6CmbV7U0Pndmb4PCjkzPzWmhXr35kO7X3VzTqurHES4W5lv3ZhXc1oB4mNb2mFzJ7I2Yp1uvd1tYI8KQryt+w81usYZupv2sIGeNl2LbzBk3dUNRea0Z+a75bLd1fuqb/cEzv22+vhwcX8wyyW/P1BThwcY6PNu6wbdbqfdbh/wtqnfm9V3okYYbm8A13eUuW8h9qHpZbvNYfsWMkOvqkyoGbZ6tW4uFY/Y4mHTwwgNd3xb7++Auf11PReMbQ9dDzEAAxisQ+dtRaDvzbZdHTatsYvwl5sTu/hbab43+ansaNm84N9Pze7QyxOb/kwHWO8x52bdCJB6zIcdf2hNt6su6xddvav2lapMoNcBeycL869//BMPvDqsdhqwfGKlqRk/nMVluppI+Wyd5otVdm0HNN3W43LVhYVXXbi5OTs749N98xDWUSR/sZbioqk/",
"part_3": "9sG9ZNGa7hBWBlrWYoNhlYiYMPNhjmcR5dSs6qbtlQsqsSFhSe8Vt/0cc8B1z89giX2F2SFTHNfVwdGv2v02+vjENn869FPj/CJmfgozX1p8OtWPHyt6RRcmE6svG2uSZeOgEG8c3+Til41n+7LR9ZdNwZcwZMHv6BluHO6nff2kb2IwMjeFyU1qEpPhP7vgsCyMTdkhrJgum8zkX6ydWJUiyPFz29eDQn5SwypgOxFwHuxBqqg/Vpf95g7rj1o6N/f2YW7uHS+el4QXIMqFuzT6uUkexH7SxDf4JAhQeoYWpbNeZ5/D7pfVoVOn7W/W+9VIhejZ/K4fuXCcC7PE1u6xkZj20PP1arO+hJGFmvvRfYaOg1+tqXv0AzmCL7oeMUwEIVsE+lO+uCMlde3mIDsEJ6FvS5Xzn5/bD/wWYmIMgZxnX/eHvSoeAbI+Q2jd11fQOQgLgfTKvAQ/bd+uqnOz",
"part_4": "rXYnWGmuezo5Pet2mzXup8tmi24jUrkiNNig8eoEX3tOggh2ciWdd3h9/foN3QShC/LAka7rk+b0zbJh298nbfTvU0Rhgz9x2jClvJsXWFWfbyfPu9eHN2fVblc3q5Pb09h2O7QdTmWD9ZW5PsGcH0E6sMvcvI8LvTPDXNzPLffDScNn/iGYVeYH02Na88NL89agn7y8fIkPyjV/MO8nI8KoW/Obl+bjOdb4/iUuv8cebucULe7B/NZsdVQwzTs1YYdNLVRB76dKC0tU+Ny/fv9G394abuN7s9LXjotdn7yfmxd2XImzCnZOOi56CtOLRWH2fg8WxXtAynNG9ZxRPWdUzxnVc0b1nFE9Z1Rfn1HFSbrZ+evZr7/+qqEQwfw5u/q/ya6WDQw/ezOf9XXXAwiz1/fLWX+3q5ezc7OcCQ4vAsJmc7QIDvQjaWjkIeUG5QWlA6wlQ1rlBBlTSCt99X9e",
"part_5": "ZiETKnfFRfT5y+n9109PtnuE7pTv4nqpdIqipUslvafFBP199UZy4zixtR7rZ8baAvdCnxcu3Lm33Fi3wPck3PmNd69j+C53r+Msvi3S0Mbx3Bs/iniZcaJWdCpFLF4t9kIVYASlL4318uYSbUxCH7W3zeUmm0cfmV705QJAvGjQpoqWhajbFqI+ERmbsvI2KjwR9X6p2OwIxUJJIg20QfEXohfLCzXjeXHUrS35VMRX0T2VvbDsnEhnjvVs8+zsU36VD6LYYhC3VDm9KQesYHrZRqr686KiRGROVHmDKq0bNZaq8tNgL9GOwo79S1VfIatY+7hTuCOUlqq3pfCK8r+6XXKEUUR8dbgMjsd/RrQoFJyqRZbOTTEI7p8AR36EnOUAeG9oXdi2NLCrd/JvOiztgsOnn1nByQSRnLJHN2aP4KUsgMERaS7B1pzPeEn5uuCFT2kRn7QfSSEhglI7dGHn",
"part_6": "tBxeS3XiTP3QLjXjGxVdThRtIzBdIInR173iOBWZA94DWNV77VMknX29NgqFui0LLFuWRH4JLimLlBeSV8lLUca2spDDBJ8StslFhmV6ka+xi0wV5JiGMg0ETpWlXhos7dXpgqQ2sls24dLg6IkqzU0AXKraOUyJtXzcrdJjoqVSNgCT5GAcMn6WQGbgIc0Qx/js4dc+gfHzjF/wVCbpwEnTCG5NPjhirupQwEcRTASG+0/4d8cIImyZ0/IIKxnJ2nELDuZIYF54awmOTsDnKbk6BYUUBZ4J8jzXYFnmGJbgsyMqPJqAjLBjO+I2me7fqVVUtGLC4AqA6CzJhNMH0g8BMnqN9AwAmIRc+7i9ZaqvVxPlyCB5DudPM9wRvgqs6iBtDhIrkNjAO3wGIrNkOe4TigOuS75nEBu8l+RWEwowYR4gGxI8F8RIJwxYDPryMVmQnagqnKoiCx4UvEVVmsVU",
"part_7": "w0Zv8WMSEGKlqix/wjGOCWiLkK5kKRZOMho5ZVZE0i8WVIkGcu6cUcDnZD8yZkbyXZTMggSAGv+xxaxkP863yDkfqTlljpE62jpxk2wpuDrNEnA3TXasHdQdRPef5Awx51S9FUOEzCPv+ACsYmKwUfdlSM3c49o8wjttzKlSEGiZ0j9Bfg5LwMMYejISa5JJYCIf8qlMgoZLAdOCojLpssyecuoRXT27F24iXQSRKYdMvIx4suqwspfgfnkk1SlBBcf2+j2fJBdJwLZOno9k8G38k+oX45TMO0vG4oToKFLGHJG+IJ4Y0qxCiXFjIQgUeBFZmR2zxBClRbo0pCayRKb7Vg/Ko9L8IKULmdy3y1Hk3CE4LUAotiACM3pQSnEkI8npN4mjwTIeXIiDXEiZQbdgbM1T8bSCaOArw3mm9nVTfOdTnwnozgIo1NaBadVDMoVDiOhJoKp8NLqoszD28SzF",
"part_8": "HaEPBhlJa50cJWAwOawxlRNPyAhtz4OendBrPgkqfjxKhYPnE9Y6Aoqpj8HCpEgHS77CRA4IK5PSZEgbc3pziVCAkOGwdooIglwJQSUB19Fk9OGEOdQC8aZkYNFU0I4uFeNnHp20mIhjNbsMLugHNSTDiXMxKCUNqejAoNmgkcijQ1B6wmVBLUfAmmdmJzwjQbuASyGBlCQ8Zf5ENVlfiBtLWJD8EW9oyktQM11aqM3D7pKMFGzK6NsZh2R0Fe+oD+CBURq4J2iY7zBfyZnsJ4sQHkKOkg2qYayKeUwyRMrgLoEcArTLUFfARrIBY8kkG7UhuxPEA6wuul45smU88WST+ELJQglBqUbKA2zWCPdEuMl8foRNcihR519AkzkcrMyZu/L84xmHrYRlYDhlewYrpDwHWSRFWUHFiBUSzX9yJWOjNRE4LR9wT2hmTuQjrLyGTluO5ZAhTqdDyBiO7kUo",
"part_9": "p8TaiBuKAFRoMSJcOQrw0nrJIkardOAqm8TcMtLeeD4O3Palcsv8mKO+7A8JCzbBA4ElU1uy8vSShgAFVA7BKJtkx+HwM6nS2QnIHnHNozxTwewRIzxw4HGk88xt4aIetvNwHw8/kjZpxzNI2eel9pe2z8eU4Xt4LjiHH8tTMa/KY3QJkTXUZVT2eOJzQ6aiMAl1m3iSjp7pQtrh/ESXk/N0LHc4N7F5dDN9ebzYAzY/JnKFMohj0utKUi7xKpmKY7T2WnEgtcv5KkuGI60NcpaD9V1AcT4pHH27MOZBvsLqpASGJc3NnZOqB+zBjN6CfFN5QJQrnJRI5QApBVEoPJfSnQu8gYE6bgHaLSB1ATIoVXor0THHEYGn5VLqL1Ig5JFLwzojZqoFxTLXyGWLSdk4+HEsdqq7qRCh4BqQ4CJxwOSLkclDeBurq8nE39wnBQgfoqLMlgYuV6v4gDqFccgm",
"part_10": "0aUcz8HclfqvD5EnGYtFMVNR1g/h5JES/xHlHUoWDylGqrSGPMlanFRf2MoKnWX2aJhdefnMLMBwDInU8wNM4IXWs6BJ+2mBm0PcJFd0QY5Qfc/jKTSUALwawxWTgkCothZjcqmZddBWMHemFkliYSwL5s1HSs+jOdNw1BvJtIy2eoI7vTuG6WOZpswlYXFDOUwqJW6orJWxYiYfyjSW18pyEtTyseZsQy07/Sypi6gK68bS4rcrEtlQjXDh9w0igwnaIptkN35y0E6/1a9SWeBpsAMzYRCGATtkdnBMPz1fTvbwGGUfIXjAK2vUCFmJYTUPAuMh4xU+xF8yeCCXsjargcCe+FBm5HcL48WTfKmvQ96RDz/6pBMuL8ZKZog9zn3KWSEuFiEQ2BG/Q/Ejgjp0L8ZDXabixEN7Hpx1MS2vPfWbkI0KfMP/A7+7ODTr94d6dt7vD/XDvwGp8fk4wi8AAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2240
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVladik often travels by trains. He remembered some of his trips especially well and I would like to tell you about one of these trips:\n\nVladik is at initial train station, and now n people (including Vladik) want to get on the train. They are already lined up in some order, and for each of them the city code a_{i} is known (the code of the city in which they are going to).\n\nTrain chief selects some number of disjoint segments of the original sequence of people (covering entire sequence by segments is not necessary). People who are in the same segment will be in the same train carriage. The segments are selected in such way that if at least one person travels to the city x, then all people who are going to city x should be in the same railway carriage. This means that they can’t belong to different segments. Note, that all people who travel to the city x, either go to it and in the same railway carriage, or do not go anywhere at all.\n\nComfort of a train trip with people on segment from position l to position r is equal to XOR of all distinct codes of cities for people on the segment from position l to position r. XOR operation also known as exclusive OR.\n\nTotal comfort of a train trip is equal to sum of comfort for each segment.\n\nHelp Vladik to know maximal possible total comfort.\n\n\n-----Input-----\n\nFirst line contains single integer n (1 ≤ n ≤ 5000) — number of people.\n\nSecond line contains n space-separated integers a_1, a_2, ..., a_{n} (0 ≤ a_{i} ≤ 5000), where a_{i} denotes code of the city to which i-th person is going.\n\n\n-----Output-----\n\nThe output should contain a single integer — maximal possible total comfort.\n\n\n-----Examples-----\nInput\n6\n4 4 2 5 2 3\n\nOutput\n14\n\nInput\n9\n5 1 3 1 5 2 4 2 5\n\nOutput\n9\n\n\n\n-----Note-----\n\nIn the first test case best partition into segments is: [4, 4] [2, 5, 2] [3], answer is calculated as follows: 4 + (2 xor 5) + 3 = 4 + 7 + 3 = 14\n\nIn the second test case best partition into segments is: 5 1 [3] 1 5 [2, 4, 2] 5, answer calculated as follows: 3 + (2 xor 4) = 3 + 6 = 9.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "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",
"part_2": "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",
"part_3": "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",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2272
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nEmuskald is addicted to Codeforces, and keeps refreshing the main page not to miss any changes in the \"recent actions\" list. He likes to read thread conversations where each thread consists of multiple messages.\n\nRecent actions shows a list of n different threads ordered by the time of the latest message in the thread. When a new message is posted in a thread that thread jumps on the top of the list. No two messages of different threads are ever posted at the same time.\n\nEmuskald has just finished reading all his opened threads and refreshes the main page for some more messages to feed his addiction. He notices that no new threads have appeared in the list and at the i-th place in the list there is a thread that was at the a_{i}-th place before the refresh. He doesn't want to waste any time reading old messages so he wants to open only threads with new messages.\n\nHelp Emuskald find out the number of threads that surely have new messages. A thread x surely has a new message if there is no such sequence of thread updates (posting messages) that both conditions hold: thread x is not updated (it has no new messages); the list order 1, 2, ..., n changes to a_1, a_2, ..., a_{n}. \n\n\n-----Input-----\n\nThe first line of input contains an integer n, the number of threads (1 ≤ n ≤ 10^5). The next line contains a list of n space-separated integers a_1, a_2, ..., a_{n} where a_{i} (1 ≤ a_{i} ≤ n) is the old position of the i-th thread in the new list. It is guaranteed that all of the a_{i} are distinct.\n\n\n-----Output-----\n\nOutput a single integer — the number of threads that surely contain a new message.\n\n\n-----Examples-----\nInput\n5\n5 2 1 3 4\n\nOutput\n2\n\nInput\n3\n1 2 3\n\nOutput\n0\n\nInput\n4\n4 3 2 1\n\nOutput\n3\n\n\n\n-----Note-----\n\nIn the first test case, threads 2 and 5 are placed before the thread 1, so these threads must contain new messages. Threads 1, 3 and 4 may contain no new messages, if only threads 2 and 5 have new messages.\n\nIn the second test case, there may be no new messages at all, since the thread order hasn't changed.\n\nIn the third test case, only thread 1 can contain no new messages.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACn8N2gC/+1ay27jyBX9lQttYgNqQSRFkXQwAYJggOlNJ0gGyMJy3LRYspimihoWObbRaCDb7OcT5svmS3LOLVKPHisYK15k4X6Zj6pz7z3n3Mta9OdRkbe5M+3oavSXptyY97Y1VWWW7Wg8WnV22Za1vbX5xmABHpW2MI+jqyybjUd1U96XNq9ut0292RLhb3X1o5F2bWRVV1X9UNp7WdYFf2DNXWU20jnecQme3Df5ZsP7Krf3XX6Ph0/turZXC7uw32469ymvCimd5EVRLltTSF",
"part_2": "vLn+rCrOpmadxYclvIJ2O2ThqzaoxbD+CbvLSyJaKtW+7alA4w9kmWa8QyTvCeCxejxiyNbSXXUt1iJFXp2ol8Z3DxCQuxuTE5Qq/1x7K2P5rG5bpaHtamMWLy5frgvQOAk3olm65qy22FdIxzSMZNWNhfjwKKW9cPSE3DcpOVolytAIs1HhNYTYEHhdw9adIthOJSXld5a7CxjzCU5TdO5O9rY4FtzcN+hZNt7UhmyVd92u06H8LJP7sNGK17pHq7C6XEfKilfah3JfHlrxPOyQp4GkIp",
"part_3": "uBEHI2n2kyOF17lDUFSxKm3p1lhPFGqZV5WskXG9NdYUe3hbDIpToSPB4Q1xNeJs6mbPPGVcGUCsd3YC+yozHFIuFQZZ2lrJGgKtcxg6325N3njCBh40hb6q8l27lm2VL83Rila9wXBHJD+g2H5jfvu5/LLffEdf+/7pi9P8ito4+ztutGplALRGvaw+GKiqQeSuWlcLULhDKyd9ELR62hX2UCLsgS28Nb8z1VZ2skCNQurO52q7zR30VCt4CK3GdY0BrPJ0BCd/HKp+3C9yX3txtWcJzL",
"part_4": "sOfeTMD52xS7MPJd22oMvlgm5irUOUS5/EXY1i0HhF6VtqDS6uRPYJKHzb4xRyUbaaTC/2Du33sldPW06CsYRjmUwmY/TlMDpAaH6LN/nt8A5C2i8TIYUL+46/3ttt1+oVH33PkVg2gK1Kq5WVfM+cWxiXhsaT1twjpB2f4PsikF/+/TPy4L/B9B/x5UQIbM1jj7uHO5gmbgtvvXNmmze573qN456toR9oaswhoL/R0JdkktnRbBBD+R7Gg7ZBT3nfB2TXT433LbdiyDfwpDF9L7C9+90+",
"part_5": "CudGUVLkZTs5oPPPXXvIp79FmfyaVGbH3S//+uk3mLWn6diLh9G+fcw3GNuuj6daLmyMPxJKIJHM9kksbMibfk20sAHWRIfvpwfvsXGG/UA5XBH52H30D3VrdpW+90R68+ikX+JzPd7VFeogipU4nSLF4Rjp1YDOGAh44Mxu44bzdmDiuHO/75dgW6TwM4zXPW1fdc2YXXw0W4acfj0UDipyhg17XBKtx0h35usg4s0ypuDLo9p8n6KbOSJ9hxaHcdp12RyFOUgVWi7ReScKmwyd63v1oY",
"part_6": "RZkZlrC3oHuT/VHb/eHXuhgQX5gN+eqtO2wJjA2poC8/eH+oHv+gPScB7yX7K2a3y2OC2ZCc5ZmP/8oC557MJAyBv5hia/0FQuLi/Hcs3bx0v93D2y3/pXE7etSvy8ub66ehfcLGyOefCNwIRcWXJlQ5IuoK69xElLqF/eXJc38gf9Ke8kuLkSvhHxuy2elf7BHYj7xHq05Au8v0S+GhS5tg2IxH1f3tuZ8O1M+HYmfDsTvp0J386Eb2fCtzPh25nwfzgTDiBudHU9+vjxoz8XLez//fnQ",
"part_7": "14qMRzfjEVlHBaPrz4tR+7Q1ixGgRkrgbU/NaIwnmq5/GS8OuwxYuqD2jaIrQn36ZSy/HTRaDG35HOD05YDMbOjj5yCjl0PGfY7xycLPAGV2wWsVHfoMXxPuFH/BeRqrbV4LcK4axzKX09Y5RxJSFUwBnGGuBpJC7wQB5s8GSM81e3RCqDO7J5JTygfndY9yesLoZzYkAYPXGxpzLZuWmkOo+FnY2cthkz5Tb63kRAPMXw6cKvBcDQUaAP18zsnLoTNs0VxVtBjgqWSvlbdvCDnkBOgSTF",
"part_8": "/LG4rUd7GG+K8BgjMDxACdAXYIlJwKEJ8ZYMYhgQD8QKQIcjJAcmaAFAGoMScTicKQen4oZWc0E5OawTkgaSoRugojClThFj6dc1yFEiYSIQFckMw4kflc4qnM4GbMSpA6lRCVz2Qeygw+DEg3zK7Dad9QUwliCQCO60xCbMJrBACBcwlRG0JHEuH7DSrRLcCeyQyh8PEFKnBiiREf4GAA7Y+AgE6e/wKc45dIP6X0CBIJkFgAIhKICwOFmvoUuaPcQPNKtexAOUCGwTSUFLVnLAYsJVgH",
"part_9": "xsBuMEXCqQrnC0zJAMgjw1g1RUjgT8l3AFYCrEwoOygJABYgDrJJEpadJtQGVGJhmpILBsA1EVJJZxQmnVOkJJMkJnNZQvKg4FxJTSkOVcpiCp7G5DjiNQRGPngWUrCMXojYknRdTH1hERglS2mAOQnCX0gZq6DJjOLP1At8ntA9pDCgUgEI5BiE/pQ9puzwFRwzB1loHuQDaOQVSQauA7oRmdIvxAlJDp5HJz54wVkz6NSUIzHMIGIxe+OmB94NB/tqKaw2VR9P1crhgZu10N7TvnG0U+",
"part_10": "jvmFaCoOzAjKyCwSPHz+mlI9+HtFHv/jnJg7cgLPwGomEkcAkloDysC8/ASTACdE3VJBAfHoHm8Ai8BAvtiQ+V+xl9AQXgGgidkY1XHPpT/R7O1K8hK0cxKDjzzo61k9QjMWsEIRlFANngA6yD3ZmyTjojbauAjCaaKQVJqRIIo6tUSbACFsEuyPOjxts1844lU1Gv/F7rTMee1/FQRK9g2M8mqEa9Yp2KU5XGi+Ll8FqoCj3/h+R75p/j/BThcc/4Df8biLvtbPlDZ0ZXbdOZL/8Bjbt5UUciAAA="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2275
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA boy named Ayrat lives on planet AMI-1511. Each inhabitant of this planet has a talent. Specifically, Ayrat loves running, moreover, just running is not enough for him. He is dreaming of making running a real art.\n\nFirst, he wants to construct the running track with coating t. On planet AMI-1511 the coating of the track is the sequence of colored blocks, where each block is denoted as the small English letter. Therefore, every coating can be treated as a string.\n\nUnfortunately, blocks aren't freely sold to non-business customers, but Ayrat found an infinite number of coatings s. Also, he has scissors and glue. Ayrat is going to buy some coatings s, then cut out from each of them exactly one continuous piece (substring) and glue it to the end of his track coating. Moreover, he may choose to flip this block before glueing it. Ayrat want's to know the minimum number of coating s he needs to buy in order to get the coating t for his running track. Of course, he also want's to know some way to achieve the answer.\n\n\n-----Input-----\n\nFirst line of the input contains the string s — the coating that is present in the shop. Second line contains the string t — the coating Ayrat wants to obtain. Both strings are non-empty, consist of only small English letters and their length doesn't exceed 2100.\n\n\n-----Output-----\n\nThe first line should contain the minimum needed number of coatings n or -1 if it's impossible to create the desired coating.\n\nIf the answer is not -1, then the following n lines should contain two integers x_{i} and y_{i} — numbers of ending blocks in the corresponding piece. If x_{i} ≤ y_{i} then this piece is used in the regular order, and if x_{i} > y_{i} piece is used in the reversed order. Print the pieces in the order they should be glued to get the string t.\n\n\n-----Examples-----\nInput\nabc\ncbaabc\n\nOutput\n2\n3 1\n1 3\n\nInput\naaabrytaaa\nayrat\n\nOutput\n3\n1 1\n6 5\n8 7\n\nInput\nami\nno\n\nOutput\n-1\n\n\n\n-----Note-----\n\nIn the first sample string \"cbaabc\" = \"cba\" + \"abc\".\n\nIn the second sample: \"ayrat\" = \"a\" + \"yr\" + \"at\".\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIACn8N2gC/+1bzW7jyBF+lY5yGDsrC6L+LBvZABNgF5nD7gbYyWlkzJJUS2yJ7JbZzZE0iwVyzT0PkEOeJI+yT5KvqpsUbUuD2OtDDuJ6yO7qrv/qqmoB+3NnHrvYSte57fy1VIV8p53Mc5m6TrezqHTqlNEfdVxIbABI6bncdW5vbibdjinVUuk4/7gpTbEhCj+a/JMULpNiYfLcbJVeitTM6YM9SS4LUVma0RZAlmVcFDTPY72s4iWAe5cZfTvTM/1WJGYviPVcvN2XsRO5+iStMFpssF868fa7d1fROIp64ps4zYTSWZwoF2snzAIslK03ZrEVsXBxLrXriR83MlULlcZ5vu/WpA2RLiutIU5XFKaUgJRdsaqsq+EC",
"part_2": "FLVxQmpTLTPoWIpMFT3xF0kr81LGrAyYF/GaRjVeLLCWi7h0PdLsW1Va1xWwwRbCWuEMrKStK6vUsWlqPFfG6VpslcuwIXYM6okfnhiAkeodrLsMuJCLJlbeV1KnkhZTk0O7uUhyk65tV2wzWUohyYIMYl2gosOeOKAXsJX4Ri9zZTORS+dk2RPvCRFGkF0hYat9I0Eaa5GQBDIORGIB7bDE6v9NA8lVGovkAC8HjCP1GycWpQRUWJPPyS7a6KuEYkZaK1L4whSyhNBJ5YLnFqbS4KHh/oXSykmhqyKRpVeVBbLC9sTb3Bq2OQWDTZW1pgRX4C7zSvYCNei+NGxnAx4kRyFbZLpkDg1BEGIVCWsKbzlvdEx2ceogv9GEpoFW",
"part_3": "mQpxqCSMf2GrxNvhsmEslCNeZGUJEOhQ3HrnBb498V0TjthWxLB0ZoyVhLjI1cbHundewh5h0hyxrtaMQu0Nx9pamy0zRLSqoiqeGkxYYqSlnNvaEEoLU86xC/OldA8izoWjYB8GLiKVKFallSx4DA88FoPtu4VGAMCOSob8EWu7RYxRuMz0FT3v9KZyPGqOEBKClnW8K1pnm8dKh7BlWwv7n3/9+vd/PpQ4877elNIiJ5B2jJCZDfKDBJW5J36MnntK72BiVs0khNQTfzY4uR6LA5zDWSJXIuzpxCvLqcpoivgjZ8zHJxipEhC9BLW5kZbOidylcI8YRP1+20o/VK5tpveUig+mgn4VzlVQ6mEMgBroHTk75HhxFQm1QDTB",
"part_4": "darYGGsVsjknLj7kTGouraLEUoctCfBu0XJnnT+vonCOHlYKzULaJ1JuDfzj5JLssfv4s/qFrbKnkfeEF9qS1DhDRCrklKBjakr4eWP8Gp/FnoBkntiv//i3J1bLpOrzikFloVAgU8pllcelPwddFkLVRP4USJxAxNmlOWP2BAqt9ieItzdyhgOWyX1tg8Sf5Hn71NVR2Hb7N7u42OTSBsfzWZnpOElnOk1i/s60j42ZHsz0UEQzHYkhuyhsxrZy7/DBmMK5jTKk3UCZiPFMT8V1G69QM61Ne/dV5EULwn2PUtJE5LvgdQ5Ky1LXGs06QdaO+NpPMPoKI4b1WtjWn1CPfks7WGCPV2PtyxrdBez3TZrYKpy1hDgjJHw4mao2",
"part_5": "+obdA0BJZaiiDojsj72mcl6v7zl11c1O3dsQnVK6qqzDbi576JlQJFEoUX3RIc3lwiNe2K67RJ8j8KAiZR8thP/wLXKkvBN/EIPxpLXmjq/FZUkLd36mMUaSuLCXfk45OaXQsoHNgdUHRNpFenkHjPdlJR/td4/3u5P7Fe0v0bzJC0h12ULEyaCjHvipOzZOoKbuWhvpYYtfXEWXD8Helh6GMwTu9sPt7VUUFFbdFUD9bt9Pt5lCLCnxR7aCawuzyOPlA9npcUjEAJI4ByBRVIia6ADydFfH6DZkviI6q7uHKzABL5IdyA0+mbcg0OkRsZaw7O6nqwny7foheEXsowemJxqPSO/IfD20SPMLkuHyiaw78buvkZqPSIQ468Wb",
"part_6": "DXLrxcWOjNOlN1uDKF1ePkX5ffDpm+hN9xjKQwwJVY/w3UNk2Oik0I9l0+JK7Lv8xr+GGbH/ooyDN90voR4wj8j5yKwfKDxf0bYQ5suyD4/al9H+JxvvHtv4mAbHDL1ja+0eWWvwRWFH3tCnUFshDKlWfupRaSMkuGzltl2Xu1JAW2r53Vi6pDRNOZUT/gWmrj3BWpOFkaLtJld0gUXfqjTmIaOfr7TnK+35Snu+0p6vtOcr7flKe77Snq+04UpbE7Gd2w+dn376yfc4M32+3p6vt+fr7fl6e77e/v9cb2mGFN2563actA4pu/Ph51nH7Tdy1qFKwxXjY6gFnS4gTMcvUqFqKi5I8brxVZE3DGa+9vriSzt+6Ypn0D/U6LpI",
"part_7": "H+MynPly7eu1L9jP54W6zoX9GIer6PkES6CUR6lFjbwvIJm8noDIyUQtwbc8adgxm3QgRi8VOuZnxh0Xf08ZZPxbaZ+gPmDqk5fKf49O3u2Bt+dBKbf39/dHGY05AidsLnqPxMHTv5G1I7YnbTd5kV8+4z+g0efzScMNgvsHz2dQ6ORTuvucr1fZcjG38caoqlHEq1Yps4ntfLHMVuv88y79lOjipJaDF6mpCnQcWZwv6PeKWCu6qDiTSEe/5lg0ZfHcbDO0cWjJ6TeHQppsj1Qoy3m8T+NC2mo+l7ixbpdrCrQ8L6CEqdABWytlIefWLOIyxqUeF3zlcmPWIIuWt1pmdLcpJXFyxrp4bzKVyJxu/Uo3TI7HEhn8Wkw5nU0b",
"part_8": "F4yHYtw6lVMxmHKg8em8FhElvsFQDIYHvBsx7NPqVEQ39B2IiBPmjRjU8AONG3HDfK9b1P1seC2G9J30xSTitD5qQX14j0P6PdDz7+uJuKYDMeyLIWsRjkdb6lEkRsHLA6ISgWRbY5KGj9a1GJCMg0gMeB1MJy25xkgkg0YissWokcnDRtdiNAmWoJ0jJLeh5zR5QYBtjcmM2co8V/AscqkqZGz3CBR432GS4DZUaL4TV4j+bK/oxwfct3CZizkaCykd5gswD9RwM1cLKfNMxp/2hXRx7heY/EZpywOigzA8fni9EWpHksnGOMyk4PVYXI+DaQ9Or3dFYxGN2w4J4VQHDDmAqY6Co3xqHfvwGt+I8U3LDRMYlSWZhHXIMG65",
"part_9": "azDwbnyZ0Z9rptfz1atV4cw/QDyMTlXIF7Q1RbEq8G/FH8qtNFoxlIBHmfkDE/lTPm7eOKj9lwiQF7n/wysvaF7QFF+qPrkHN8DW3lez8RrE1jm9/QsfTNf0CnAa09D/8TaAwGmzPuyrCfjN6wbC83xdL/Lo1WRP0iRJUjz04UEaQEkzS3kpSZutARye1jBtkUsDYjNlAHUbNU5DuNkViCQHOjXZNCA0K8lB4kbEFtcW7qvZarVaJfSX8MMDPwtD/qMxbfRgP/IDXkk8Ef88wKR9q0AhoNfgBrhqLa4OuEGKmkXD+ABfHQQ7iJQkNVdPko5vrcUqfA5ojUgN4+RgDy9iQztpxK0t0FDz4xaTxkirFscGt5HyYJhal7ZijWYH",
"part_10": "4zSGaejhe7yWcfMwFUNOgyPcKEdUSyYoPVzWR+i0h1yFhjcoXryrj+ren4YKwy1KfyxuuGCNsGnE/dVQTLmkodkY9JnAFGseVqPdUOPErXCEisfFikB9ypKTUFGjKXVRUb2pz81Zn4iynFMxZjmnffQ6w4dEIeeAU22EUhldD3yDMrx56WUo8feh1714ev+epPuivJawrOGFT3K4ygUQvkmSfOFmN/JVyTeT/oLHvUbfw54pUe4W98U2X6ztdlPs6NcAP1QnL0fT0EqHjum5/qrVT+JaS++8Fty/kpMW4M7Yt7FT//Ht2PNFafsiyMKiJI1vkmbLSWcMfL/JXhhxVznyUkGeO/o/BOzHSqv7SnZuXVnJX/4LRQxlr2IwAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/11SZ27DIBS+CuJ3KxU3o81V6qqC+DmQYHAYcZwod+8zWGRY1hvf8rzSnbPRNH/BxSDphl5rqkwfg6/phvzUtDPitD1f9GEvd23jeW9VHIOD4VjX5jiAC2NUtue+aXdyf9CX8/YkTIdkTd9ITYXgHM+5YEsd6TuEXYh5Lj6ZD9zvU2aKkL9YppyHK83RSGc8X0IUSfEN1kprBwlGtQBaAj+NHQSuM8FNo7peGZ8GA9Bo8GiebaC10goSCdyPXOsgIeAiYpj0J3A+4guTo5rMo429RiE0wXYAAfdyJw4nVzYd2mM36Pbgh747K8TzqJLid5LYGB6+FUOiWhFWEhY4rQlbYVuQqTJSTfUjY1nEEr4ue1LM6ueoKqmqlLEg36myqkje2Usme8r8IuxzgpeELfMT3Ogb9WHUgP+di9hu/1jT5I+PAgAA"
}
}
|
codegen__primeintellect___2277
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nOkabe and Super Hacker Daru are stacking and removing boxes. There are n boxes numbered from 1 to n. Initially there are no boxes on the stack.\n\nOkabe, being a control freak, gives Daru 2n commands: n of which are to add a box to the top of the stack, and n of which are to remove a box from the top of the stack and throw it in the trash. Okabe wants Daru to throw away the boxes in the order from 1 to n. Of course, this means that it might be impossible for Daru to perform some of Okabe's remove commands, because the required box is not on the top of the stack.\n\nThat's why Daru can decide to wait until Okabe looks away and then reorder the boxes in the stack in any way he wants. He can do it at any point of time between Okabe's commands, but he can't add or remove boxes while he does it.\n\nTell Daru the minimum number of times he needs to reorder the boxes so that he can successfully complete all of Okabe's commands. It is guaranteed that every box is added before it is required to be removed.\n\n\n-----Input-----\n\nThe first line of input contains the integer n (1 ≤ n ≤ 3·10^5) — the number of boxes.\n\nEach of the next 2n lines of input starts with a string \"add\" or \"remove\". If the line starts with the \"add\", an integer x (1 ≤ x ≤ n) follows, indicating that Daru should add the box with number x to the top of the stack. \n\nIt is guaranteed that exactly n lines contain \"add\" operations, all the boxes added are distinct, and n lines contain \"remove\" operations. It is also guaranteed that a box is always added before it is required to be removed.\n\n\n-----Output-----\n\nPrint the minimum number of times Daru needs to reorder the boxes to successfully complete all of Okabe's commands.\n\n\n-----Examples-----\nInput\n3\nadd 1\nremove\nadd 2\nadd 3\nremove\nremove\n\nOutput\n1\n\nInput\n7\nadd 3\nadd 2\nadd 1\nremove\nadd 4\nremove\nremove\nremove\nadd 6\nadd 7\nadd 5\nremove\nremove\nremove\n\nOutput\n2\n\n\n\n-----Note-----\n\nIn the first sample, Daru should reorder the boxes after adding box 3 to the stack.\n\nIn the second sample, Daru should reorder the boxes after adding box 4 and box 7 to the stack.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIACn8N2gC/+1azY7bNhB+FUKXtVvHsPyz3l1gbw2QvSQFkttqu6Et2iZWIhWRWtsIAvTaex+gh75D73mUPElnSFGW5Z/1unazLawAMUmR8/PNN8NRkM9eSDVVTHtX3s8pj9mN0CyK2FB7DW+UiaHmUtwLGjPYAEtchGzmXfmtVqvhyZSPuaDRfZLKOEER72X0yIieMDKSUSSnXIzJUIb4A3sGEYtJpnCGW2BlnNI4xn",
"part_2": "lExTijY1ic64kUV4EIxLsHOmCEipC8zxKWkjd0+AA/P9E0IzRlRGlYwMO4JWWxfMTJQM6YapIPEwZbcJuwS0Rk8QDWQjICa4lPtCSiSW4E15xG0RxNcidkfkQKY6hR1CxMapABM2rBNaFTGYFERh8aZMwf4ZCxry3gZRyDZeoKLJAjMp3w4cSIB8U0DOE4KMEJqtAywU2FtoZxavWgcZPlZ40j606bw3qSyinhmnDrhU6p",
"part_3": "mjSJRXVKhc5NNRbgVjqlBoXc+fyYTEMAfQmzdyNwLksVIKEnXJGYUaFgSDWqi/l4ogEiwuNEKsUh6sCGtFAGoYRpTJSMGVptDDpTzjUHG6I8pJmydErZp4xj8NBvUCmkdtGpOm8C9QGMAZnTydzqHVJBQjbkoUFxSsHOTGge5XBEUj4oC4CFjglQaV1fQcRCDBMq5gSPTHI8m+QNs5okAgFw4I5EcqGNhZBe4JSeMpDuvC",
"part_4": "65m2mUBOfPtCEIYJZjYtUDEQBK2BJKNEZbRyFbc2jhDeQSj7M457pTqvCQYCxUlkJVv5S0wbPaicqGQ6bUKMOsAPuSiGmgHOgpRcvZDRmkMSCQvSlgAEqsLPbI0rmLFniDoWMQd2YYqRYBBYsGLHc0NC4F4hU+NyLJtBnZgAKLeKo0ibgwvOH43qQg5YZ+IBoMGINrgtR88u23P2GAf3e+/uW3funVv/7x7dffzcYFPrZc",
"part_5": "oIbXFNIsJ5JgM405jLrUQhlEPoW0mXINCQmzFMtA4IF7gYfhCjzrR+ABLFaSsbZ8DhfzI5jkhc0zZ/PMWl7PSygwA4ouH1Jt6yZga8KtJjKLQkOUPJJWfu7axsrSJOjshqDN6FBD0J3jObgLFyF3Kd4IYBTyYUEhG2EsUiFXYOlQuwpWleQQKglzHKIRMLFqEy1IFEGu7cmld5kukwluOkjJbQljIN6SMrD4vDQpGfN6Rn",
"part_6": "Gzys0xPA9EJxAYSz8QOUJm2rY/ncWq+4XLyDgVCN8E1ErpF/tLpysyu6vCyq/P7U8uqbd588KCtvUu9++t1KyA+sbWTJu6yjjeWCLwKrZ0pGEOyvPrnHQclxf1PRerGBAr3Fdu11AUR/1VDR9MPcGsn3KI6QDfhaboh2QuCzWJoRIspFBGowz5bMihQ4nI4J+3cLeqojFyfZBtWnSWWk+gS2JNaLBSNoI2RAyx38ILNAXU",
"part_7": "5grFhGxEYsihWh26IwKPINdYPWrGylq9vlgVP7TtJINJyw5TQKCYzGB4e2fHeDdzvM4g7casJpx4fPAIqG8a15vQ5YSYzrX6YgcfEXXbuiPX1+QsPSsdNep/vPaXV2B7xERtVr++blU244NlgouMrRya3b7yjZJszalZM5FJ2Sh8WKTYur0lz8sPwrNk7ZrztDFAPJoqibiu6ps1aZIwEdYwJAMXDUOPGgivWy7YAEKcjQ",
"part_8": "yIMXRlXMA8p8Wphz710Kce+tRDn3roUw996qFPPfSph96jh3ZClHd16338+NH2Q4E49dP/0346EBBl767haaY0RN27/Rx4ep5AibyCcmnQvs/pBDdG4JkQ25edwCV4kZUu8V0dKL0oBlaOtMlrBPlm9UuD7K67X1JRVrliS3etDUtbzgNXc1zR2Xpk1f728+3vluxdgcrZ7Rw7tjHtbYHcoqr1fFX+OlWHkdxzotuVePot",
"part_9": "N/BLEa6ypsyEi41cKbQUAXQMvKww0n+CeccbHIQTfreCYrvq8Are51Vo1iJRRGRp5bKE/FKoOt8dvM4e4PlV6l1W/apS8byKSKeCSHu3graetv3vwqHOLkV6F92twxTYFfj2KrB73Fbna4xYSqFNJGj/87jtYa5/XrGr/YT91Rv0osr6lQrsr5STouAsCvn596qgxwa4vVNCHOZa7L+cWJpB/wUG9cDpc/ECITeDi5eM/W",
"part_10": "GD0F0Tg/V3Y/f4Xyv+5UtmhBlc/ieocdiw9NYw4OnvoKU3veN/4nYrnKh2jv2t1u7VQx/E/qeqYH/rx9baL/Tevj3wUUpKd1PL/m+0lE9d673dOv/NaK70o8cBc/c63Tl+IfC3lOW9+vKDWre9WywHvbNbiA/SYF5u+chbV74un/HZ2tv45mI3eh/m9m5tun27+33gbvRk4z8IHKbY3eF/Q1b3meCfMuZd6TRjX/4GTL7fyccsAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/7VT0QqDMAz8FcmzD23XqvNXVhkDZRtsOmo7GOK/T6cWjbX4sqcLSbncJU0DV1WZMj9rZfQNUmgk3MuX0bWENDhJYFKWlzwPaIeqeFbvYkyweUJCGEigrrdDic9KPXJMd3DRroOBLUZsDJGIEWM/2UrIohJ5BNCpA2WzVr8EmQKKxDAkOhox2VRgu9jpTQaPyDDlfqf/C4Z5MIfHzdkRZMImuOMvbLO5Z5agfQjvNvc7FGh7B6RZeO/DS5/1/JXRs6sjti9ZXBeO2I53WQsh1PrzKLrzVqaD9gt2FxOf9gMAAA=="
}
}
|
codegen__primeintellect___2280
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA super computer has been built in the Turtle Academy of Sciences. The computer consists of n·m·k CPUs. The architecture was the paralellepiped of size n × m × k, split into 1 × 1 × 1 cells, each cell contains exactly one CPU. Thus, each CPU can be simultaneously identified as a group of three numbers from the layer number from 1 to n, the line number from 1 to m and the column number from 1 to k.\n\nIn the process of the Super Computer's work the CPUs can send each other messages by the famous turtle scheme: CPU (x, y, z) can send messages to CPUs (x + 1, y, z), (x, y + 1, z) and (x, y, z + 1) (of course, if they exist), there is no feedback, that is, CPUs (x + 1, y, z), (x, y + 1, z) and (x, y, z + 1) cannot send messages to CPU (x, y, z).\n\nOver time some CPUs broke down and stopped working. Such CPUs cannot send messages, receive messages or serve as intermediates in transmitting messages. We will say that CPU (a, b, c) controls CPU (d, e, f) , if there is a chain of CPUs (x_{i}, y_{i}, z_{i}), such that (x_1 = a, y_1 = b, z_1 = c), (x_{p} = d, y_{p} = e, z_{p} = f) (here and below p is the length of the chain) and the CPU in the chain with number i (i < p) can send messages to CPU i + 1.\n\nTurtles are quite concerned about the denial-proofness of the system of communication between the remaining CPUs. For that they want to know the number of critical CPUs. A CPU (x, y, z) is critical, if turning it off will disrupt some control, that is, if there are two distinctive from (x, y, z) CPUs: (a, b, c) and (d, e, f), such that (a, b, c) controls (d, e, f) before (x, y, z) is turned off and stopped controlling it after the turning off.\n\n\n-----Input-----\n\nThe first line contains three integers n, m and k (1 ≤ n, m, k ≤ 100) — the dimensions of the Super Computer. \n\nThen n blocks follow, describing the current state of the processes. The blocks correspond to the layers of the Super Computer in the order from 1 to n. Each block consists of m lines, k characters in each — the description of a layer in the format of an m × k table. Thus, the state of the CPU (x, y, z) is corresponded to the z-th character of the y-th line of the block number x. Character \"1\" corresponds to a working CPU and character \"0\" corresponds to a malfunctioning one. The blocks are separated by exactly one empty line.\n\n\n-----Output-----\n\nPrint a single integer — the number of critical CPUs, that is, such that turning only this CPU off will disrupt some control.\n\n\n-----Examples-----\nInput\n2 2 3\n000\n000\n\n111\n111\n\nOutput\n2\n\nInput\n3 3 3\n111\n111\n111\n\n111\n111\n111\n\n111\n111\n111\n\nOutput\n19\n\nInput\n1 1 10\n0101010101\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn the first sample the whole first layer of CPUs is malfunctional. In the second layer when CPU (2, 1, 2) turns off, it disrupts the control by CPU (2, 1, 3) over CPU (2, 1, 1), and when CPU (2, 2, 2) is turned off, it disrupts the control over CPU (2, 2, 3) by CPU (2, 2, 1).\n\nIn the second sample all processors except for the corner ones are critical.\n\nIn the third sample there is not a single processor controlling another processor, so the answer is 0.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACn8N2gC/+0cTW8jt/WvPGhRVOpqhaFdpBsjG2CxSIEFiiTApujBMrzUiJIIzZAKyYksLxbItfcCuebQ/5D79p/kl/Q9kjMaSWNZtuXATccLaUaP7/uLjzzsh86YO26F65x1vjUyF2+VE1kmUtfpdyaFSp3U6lLxXCACgqQai6vOGUvYy35HGzmVimeXC6PzBbF4p7MfBLiZgInOMr2UagqpHtMDcUaZyKGw9ItQEDI1PM/pd8bVtOBTBK7cTKuzoRqq12CLhTDIIF8UDl9m3MJICAWjQmYOpPJsviuMywS8TvlY5CvQE3iXSqFSYQfwH",
"part_2": "a5X5KlWVlpnCUV9+iX/9Msc3nz794jGTTqTDg0vjIAlSvIqcsMz8sdCLsSYCK28FqDgPz9BTl/zPthFJkkZp4ERKH6lSGb7IHg68+8k3nGpLIgrnroMNVWC5JP4osTE35BytFCgpLzIHFdCFxax5VgoJycS1UDlOEyNLhakkZsZgSoV+UgYCxMMhVc94yu0OYADlAGqqPphVSqxu5gDV2O/nuqsyNUuxnxAkXmrygCil21QQsA7H6030d1/tLDUZu5XyMveLCuQvzdUI9xAjuQYdQzrKmQNz9FacCGkNp2JXJx5p3Sv+rDqw3VvzaciRr28hO",
"part_3": "4VPAcW8fqBJECQjCwrmRCwB13UO9WFsaIP0puwwthghvS8jzANpAWlYSLEeMTTOUE5RhpjdR9xqLfSrlH1tXXevd/8gK5xWIxgdR69NzJ6LmCsl8qztk4vKCPJxVg/A3R+yB7bKKcPRqRCYm1WkrVBFIMQzCZMXmFyMZbcCevrynBlc+kc1WZJMoB/YGVITGXLV8EXXnfeh1Ef0p7PcKMzG8BjTOk+THpQejc4lEM6wzKgpIlevPwgP6L54XFND/SmJXu8DERg8Ao4odDLiJDoJfVOv/yw+Ig/xp6DfxWei39F6V0vmHw2EtiRYEFK+BIQaup",
"part_4": "mZfJ6pXpV/pMFsb8EdZcScWM5SOhK+AIWN+ciomDMfTBDe0K7UYvvC+ww5KZUGEWFPNKF80KwuCXPXmBF6Ymq1ZRdWYdN02dqnhdKppw6MtriltQJCceIHDWkSIVu9lcMrfecz+glV85XrkLjCT0aQSyNdMgwi3SvtwoN/VRihBAWxkvBbqcnk5AJY2lNsXAhUWP8a3VSBZ6sd0tN+JhTuKtg4vmushZHSpzVsslXUJlEGwmxm3DrZBuJiUZZG1aQ4r57TzZqJ1Jn0SY+oU2CPFQaigQ+hEP1gv7eKmxs/s3HldqVNNaFXlp199COqaKm1I+x",
"part_5": "34auOocug1//+W8P6eNPemdJ0vv0868//iskAZY8blG4TTW31AFEwdiYYZTpdG7jPtvHBLIYrFG5t6aFMbhfoK1Y0iW32K/LjTFySDWi2oWmzNfrreMGHcqq0Ga8ua8M4Cvq657pxlabewdZMhlLyeDeR8yRjd8HKtu9/guf3EjE4/4VpWFMc+78goobLziO80S5efpaqdu6m8qVmaIy9PoFFnWlVEm6IqgPagQEm2LdXA3gTUUx7LBhp8ba1z8vu7JXgmKf1giSJoKcZ+Ww5RNPiY0QUfVYQcOIQ+VHq40RQuDotfL61pP1m8LVsxVnO8wGD",
"part_6": "jR8ZVV6Vt6/oSfUKnldflV1qIx2ARna/d6OUFfsqyueL7AhRtV8UQ3VCZzA6VAlSRK/hooxFr9wR/TWIFqYPvz7KZwSyRot4t4OKLmxz2vsGOYxI+ms/FdHTYIF0YavtROVa+MwFHqB9cZ5wHKms6pF+GQutzx0WS3gPBtA5GFFSmUYsJdU5z6NT/o0VJz0vOuppiZ9aljR0zYObN7TlBw1mtMeaBomaiCGvZRycoP9iWe/0SpvFrHB8cQLqUklKb36lBiNip7hmCKxD2lDs3AqMFkm2kQRKN5QWoekL7Oxzg9Tzoxrji7ntFp6VwI2ejxXYe",
"part_7": "isVjGrQx/AYWdJzcZCMih7u6S0CClNw7jDQ4z320oXYGe6yMbIiIoKAThK4bzsexeWM+Jqyhn69zVuurY6FJVnIOJjBPk6Wj0WAzxcGTFBa3A4wJPUWGDnxA2l28OzEOCfxXHG69TtDfyRo9sLC+V+Qsuua8+TC4xweGXr15OLiL72zSs4vwgwcv8V9Voc+6aiq0qZ5dpqvZbX17b02lwgwmsitFsUG1oMOO7FatwlLbFRv3qF2bNGx/nhCictBS+AbXHxbe9v1KW35ONIT+MsgpMAyMk3OfwJ5tFhHqAQkM/X9sua/fm8biUqQdlVqXwuL7Z",
"part_8": "0oSyTqhBr6DOgE8MGDwlfohrzLVJcqDFGO/P5RYO/ntFWq9zugmf8BZDOnrjXQNwg5/kNctYWBSc+x3jsw9q2e62vkdNZs744PP8B5j3SmnRmB6vM9mm8GyXvj9vIDjf2NoPpbHazvXkw2Efp8CDN72fx/DEtfoYnp4nbSO0yol9Cclt6s6eQ3Q2eI5Kb1Dt+rvzWxfHwcn4K2Y0Ujx2iZ1AsdlObzMPmfWvvnj/t5J7/PpO7sQ/+nhv/farZz6rdSNkLw2mYL3Hw9PMkDp3OIAR/xzm1vdBvL/TbC/32Qr+90G8v9NsL/fZCv73Qby/02wv9",
"part_9": "9kK/vdA/8EK/ZGI7Z+ed9+/fh7PQULWX++3lfnu5317ut5f77eV+e7nfXu63l/vt5f7jXO7TGw6enYt+xwk8v3fOOucfhh23Wohh5wxPr34OvowTbqePED9vhcVwiAsHuPJ7GE5d5Xeg0eFUFYg89GMfDpcTTn6bjCP7w4E7iuBp8M6axEPjxqmxiXdyT9bE+dgMj6bhaZ3h5mPXuQ9mn+xjfy93nFbs2TH1rjNOjqsxq6X9kXSNLJOja5mwRzA8+f+prsdhWHbmR/97JK0Z/SX+Qz+S+BpfkiR84jer0ANuxaBcSMJ3xbZZ6xP2ELXZb/DXq",
"part_10": "PbnL++ldpJUhdF+ns7nWMW0J7xsD+y2lGANT7aHB9vCuQ3vEH1ZA192oC2H6LbPppvsv0mnbf4Nu/mD4tt+ntbnSO2ZorueW9pH+/ifexxlH9uuA9b0aNRhHwrbg3kA3QHSD9CF3b52uNYHSE/uadidlb+vrw+PWHJPeXcOFburCxowdzf8vzykENhdHdk+2seTeBxlMvoMXtZunZKEVRfQ1Sm8ukBiNfgW2gY5a2ay5sPWaCXnNXmArC/Ba3fi5VINjdXglZSE1aQkW1J2pe8YW0Ooyap/7zr/z58F51/Q/95jLwslvy9E58yZQnz8LwqUpXT+RwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/+1VwQqDMAz9lZCzhz49zV9Zxi4bbjB0aHsY4r+v1s6JaO1xA8H21fQ1TcgjbbmoK1Nezro2+sY5t8L38ml0I5zTURgEykRKBdhZOCHhlNLBptQ42w+OggkRStnj/b+n7LDDn8EgZHJS9rZ9/M4Y6pNR5jrStAX5RhRv/FTa1XnDElADArYtBWEBEfCBGWeLFxMvFvwiMpeY2EI5reW/FtPcv/CpL1Bl9OQJ+8okHVdqYYVDeNtf0HHCjX49rva1rI2F7g0MO94/RQcAAA=="
}
}
|
codegen__primeintellect___2294
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nOnce upon a time Petya and Gena gathered after another programming competition and decided to play some game. As they consider most modern games to be boring, they always try to invent their own games. They have only stickers and markers, but that won't stop them.\n\nThe game they came up with has the following rules. Initially, there are n stickers on the wall arranged in a row. Each sticker has some number written on it. Now they alternate turn, Petya moves first.\n\nOne move happens as follows. Lets say there are m ≥ 2 stickers on the wall. The player, who makes the current move, picks some integer k from 2 to m and takes k leftmost stickers (removes them from the wall). After that he makes the new sticker, puts it to the left end of the row, and writes on it the new integer, equal to the sum of all stickers he took on this move. \n\nGame ends when there is only one sticker left on the wall. The score of the player is equal to the sum of integers written on all stickers he took during all his moves. The goal of each player is to maximize the difference between his score and the score of his opponent.\n\nGiven the integer n and the initial sequence of stickers on the wall, define the result of the game, i.e. the difference between the Petya's and Gena's score if both players play optimally. \n\n\n-----Input-----\n\nThe first line of input contains a single integer n (2 ≤ n ≤ 200 000) — the number of stickers, initially located on the wall.\n\nThe second line contains n integers a_1, a_2, ..., a_{n} ( - 10 000 ≤ a_{i} ≤ 10 000) — the numbers on stickers in order from left to right.\n\n\n-----Output-----\n\nPrint one integer — the difference between the Petya's score and Gena's score at the end of the game if both players play optimally.\n\n\n-----Examples-----\nInput\n3\n2 4 8\n\nOutput\n14\n\nInput\n4\n1 -7 -2 3\n\nOutput\n-3\n\n\n\n-----Note-----\n\nIn the first sample, the optimal move for Petya is to take all the stickers. As a result, his score will be equal to 14 and Gena's score will be equal to 0.\n\nIn the second sample, the optimal sequence of moves is the following. On the first move Petya will take first three sticker and will put the new sticker with value - 8. On the second move Gena will take the remaining two stickers. The Petya's score is 1 + ( - 7) + ( - 2) = - 8, Gena's score is ( - 8) + 3 = - 5, i.e. the score difference will be - 3.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIACn8N2gC/+1by47jxhX9lYI27k5EgVV8D+BFFoYxQGAbiHejwZjTYncTI5EySY3cMQbINvt8QBbJj+RT/CU55xSp1syoY4+QhTGQY6rJ4q37PPey6lb882xVDmVfDbNns++6elM9b4Zqva5uhtl8drtrboa6bV415aYCAYbqZlX9NHtmQ+fms7ar7+qmXL/adu1mSxZ/addvKzPcV+a2Xa/bfd3cmZt2xT+geb2uNmbX84kkGLnrys2Gz+uyuduVdxh8GO7b5tmyWTbfNjeV2W3bxpRmgGrmu2p4KE3ZrMzXVVOauxJcumplytuh6jDe8vk9tjfQqxpqGqF5q+qmXmHG0JrtunwwfQu2d7BuYf7UU6kHTGl60HRm0/YDfnDbiKTnrNeVeQ2zm7u5py7X+/IBb7oHvq2bt1Uz8E3dmXY/zluY70l6X8I1bbOG1KG+eVN1vVTalB3v5+b1jjPLw",
"part_2": "ezb5osBRO2WnDYL+gIcxGzUkXe7rdnXwz349h94vNutKfV5A8PL9fpBunaVKXE1j9LhE87bgwSvOkQAnqnp7a7dL8xX5c39RCwhclaz27zG876rh6FqyKMeFuabdj/5A6FoygGK7rpmPoZs076F+27rrh8WPrKVxsB2u60aOKIf1Yfaf64GyEJwHpXemF/+/m/jTqou7yqaVTc3+/sWHn1TeZfc7LqOAaGsudli8mhFDZTfwYw35hbQBWcEb6NwDJr8xqyr20EIOMi86ipvB4Pi5006XAM+wqDih8FHFZpqP7GABjuYVg+UxneUYSoIbW/1DLfPpQS9W/XeuQcuo85zU/24K9cTj3634XTG8KAphoe2feO9VPcyf2Ho+K8JHEjs4aiqGT1c9x6WLaIyxVuqfeTl/qYF/aitdzlnn1Jo1LY/RspJJVc7ppPeTbr6jDF3LbiCVUUgPkpjqMqf6k39V1",
"part_3": "9pVvXtLcxgsXhdDfsKssjI66qQHmvOV+0WRQW4EBa/rt96TxxA0Rxm1T6DTA8LJQAMTmFwjsJyWzden67qd+th8hKTdm7qBQLwhLIcVpp80R9q2xeT/vUt6s0wmd/7qtVuUQ6Z2D6oyybgP88bwEt3U8FQwpk1FVNE8J7lbShrppxhIV4fm33lkGf/wg1/XRiaMAyv//PPX/72Dw9Cn/pHPphPHgJ61u0N0n71HmgmRfoKYldek4MCzSNGylcWwH/l5maxWPDu5+aduTKBsdJB+mCwfqc7e1oxReQQHdSxtmMZV6IKzgAOPlj3Puyj077dDcdewyewGZQIo26PQn4lco9wey9+pc/foyRXFf+VsB4p+NVP5WaLcj6qqCAvm2jZOBObXMVUJiwbG/NpJMC9NUFmAmeiY6Ig8rxH7t+0Q3Uw/rm3yKOml1h9OSbFfMm+bbuxqvtcZMFU9irNRvfrc1q",
"part_4": "OqTA/ysd9DUp8RA8lw8YfO+0jonBxpN8IplMKHuepr9X1B9/Ghfn22EpZ5K2RUBnjXw33XfVYD1WVSbHdDR/Wdf8Zfluud5UBZvODjFFTCdGK5VGGLxQbJIJWQ/v2yHXffwQrWGHNH5UR2fV4467NlxI3/6Bi9Hqdky7yJMlRAfJER2CenA266JCwvlZMr/phVfui+NDuTH/f7tYrLLOYKhjo8Eld77TEGmjGqiXQ+D+uCvrDinBaAJJPV3F54L/RWGEtsLLsqlEjLCMb6A3uV1Lj6vp6Cd99aV6EL80fTOMf1nU/XG3KLWiGuRkJF/12XXMCZhCnNcuAFjZXKDDrqrkqr6+xtjT4p3xRvzR//JJ/WWheUuESZYkjAR8/YNDQ53MTzk1gDzxEj6/RFe7mnmXAUciXfzh+DeOkFwwbOkQcz6MvLivmy4r5smK+rJgvK+bLivmyYr6smC8r5suK+bev",
"part_5": "mCcm/ezZi9kPP/zgF4LL5vNaPS8bmDZ7OZ/h+z7A1NmLn5ez4WFbLWfPzHImT78afTibY0TW+JfRcsp66KeXrc9qvUX6c/jd3Px2jpzyWCZOcQ2iT+dqQ8yJEmOtwa/LTZwbhxsTR8ZFRq8/luTS8BxRnBRHmckLiLGmgJzCRC7lVyIKY1NkJkaNSSCdY7hAFeXQLotMhIkW2pGBjSJS2Sg1eQp9Q2hemNSCLTiBhU1TkxbGZQmGwMdiDmUlESTAfzlF4H0RmjjDeA6rI2sgP3XGxfgbgQKjFprEYBY7zMKMCCKlRYqZNgfHFKrDUTFsclb0Dto5F4uHizCnAK+wgBXgASmWBoImiuGAEBomGIugAax0ecwQ2JDKxXiETSnEhNY7IIN4/AUHZ1MD1WMyjHllUDzETFCBSVTA1ARcaD4i6eBcmz4VTqj/6QH1GLfGnWSanIMQS5AD5QxpwFWNTQCXm",
"part_6": "IhxNAzeDOCCwOYR3uPGIQbwQmAd4xbjBo5FdIMULoAf6Z2cwwmcmaQTZ0bJIZXAHbxyysIPHJ+SNoW7LARY4DKwJAEWgwKOLMCyoFSglO/40lmEEQNgDeABrchREAlzwBqjHjiAL6XeBF1YeNbSGaEhI0BA76lmaDKpBVSHtIpaEw+xHwyYlibIU3mA2Mc75GzMSZjJexBCSCwVMY2GgzDjM1gCB5pr00xgowPkpIJWAGp0ko3IJuMI9LSFfHoaPtaeE2vCJqBKxDRkIVsChQK4Tlh8KBJOz5AovEe2BCmHvPJZTuMwxETCH2vgOzHBCPki/Ewox7ISwFKkkqATigX402H4E9FeUOQUG3GuShOhwcpA+5FNJqU8ZqWYIeNADZCgHmAWfG0K0gcxFEDEEc8AcARlQjcigfkLAstMBh0CmSt6tAOq0RRCC8oTMIBwongjcNTZ0hBQwyDGkhTMALEMQK",
"part_7": "ks10BRnAxSnGfnBIk5Tm/nAlchxSzgJG/Acyl9yPpH9KbEZlGoStHpFmFFCCxcEBHMPh99NgHlSKaASE+VANReiZoriSzqF9OHMAcIBWOOo85aooDloEgVaFjtaL3zEcoiL1nJxitwma8Y1o4TecNAsVhSo4I5YZUE/OSwjiN/bBF6TooEqwnrq5gqWJmqfcDUi4kYFKExiErTxKc++AVEQ+4rt3Thtyub6DPqA7/Fo4eJBH4NQr4kepw0jRVdilZuw2lQ7WSoc3vWQoDJzRJ5uX631xNf79TF5wSc6NHn4HL9nq/TO4gws2etwYkh1svL9bu/Tmc7difunMBnY3kPpnpyufnsbk4jZhz/RLzk49chmErR5ebzvHni+3JWkSnGr0swlbHLzed780Qz4BzgaC2jKhawkxawsxdwL+4S7uZi7ZNC/xj6fZsfdSRME79v9E0M7r24++TF9gr34aCj3tq",
"part_8": "Ls9PDDT/lxLm3JohGEt+t0S6VDDndcbvKzk/A6ZSnvTo3ltqzTbtE/KSHuYlvpPg7bKO5uSV7OxlH5mMDoxi7Utwlsks5TrfpZKgSlRthNqUyP9OxM8FNtyaE2j0Xo57sJnELSausdsVsP2TR6C51DjCqLSt7ROm09/Y9DrFJPQ0v3jp1zaBMlvjGHIZIHEp567tyjFUcTaFSB40bZHJNxov9utGW9PTudRr/RACxBSV/RIUPL/1EZeOx/8VNs7pNGBr7BnJTqt6RnEFfEEJEBb3HcJM88/fkpj5I6DsyslWm5mqvSTStZj9KvTf6iQRClvNworOJXPXaKGFsyolITa1QXRa2ocTJjYzUJonHhqTzvUuFKRuvSJ0S0ZGpADJZZsf4xz5SDImAM0U09w3FdMwNhltgoGB6kD4gTeI9xHdszzFFx0YjUZV6dWlaOualOiSjyWq4jeEorH/PZl3yf2sg",
"part_9": "q/PBJqrvr+bqVeU5OzjMbLiLbSU2UHNUsMJEai7CQAvsZjryCPEiNOxAgSSO1FhnG9Sq84VnMGECsLSwE8Vkc+PZBOlyf2xh2eGxudqOlscQXKBFaoBRXJyoL82RVAcfzDD4DZLV82YTF5BCbWGyZAUbbcxMKm6TQlLYWmO3ikO5OkrsQOMOUQfTjL1KdaATnqYkUqNgCykx7EdLeXYjjayITeTkmoiNslRNONpVqItpM6vzIJ4koM6wkrJBrCGer3ju1IhOl8/ZrM+eOP+KkiI/J7zsc8RqCRfs0sGT9GfBZq1jS59+gWsBPh9tNiAzNnEBVsIgNDpMYVMW/k74HiUYUzEDhmY8tKEVMC3TmVjKlz6qbNohYnRhRq+xSe1IFurgyrEnDJpcj1QLESwYYTgSOADQY/WFUaFTyYR+CgUb0aFEZRSM7wGiimJZSBnS44ViiGnkzNMrnhHpoCCTbIacA",
"part_10": "eQRVailHRCQCAcwFEmXpaMSUDGLpCugfzrx0rN2mOpG6oAqjXQBPJk/wHGCIsHOtiqTiS1jQJLnbwW1Il54DAZjeWSDOqgMTnQ44UKfUsShzYVQ9ZzZD+X5B/xChjxL49EG74nzzB8U6kQsVjj5L5Mo8kdJ1AiKIfDkzlxn2vNlqBgT2bEwn6krb6NYB32JT2lQ8OCNqWD9yR+bs6iFsFeHA/Eo27E7zKy1iFDCUCjVInLgB58taa5CqHA2asHMylQg4ABWDBhHzXjYFPpqFvszMdapXNL4yJMbGAQtEjWlY+VKdvrgD8man9FF0skN4Bf6b1x4mjmXCWF43kG3M4/8zWmUBmf0PFMtEsQ30W+s30i/7mDPEzuiMDzzfP09Xylv/8d12lgbnhknfHAAoTg+vVovsiQ5jy9XLqc3AOf+Xxu4GDCnzR8bGC/5nwH2r3ZN/eOumj0bul317r91ZjKtRzgAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2297
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA lighthouse keeper Peter commands an army of $n$ battle lemmings. He ordered his army to stand in a line and numbered the lemmings from $1$ to $n$ from left to right. Some of the lemmings hold shields. Each lemming cannot hold more than one shield.\n\nThe more protected Peter's army is, the better. To calculate the protection of the army, he finds the number of protected pairs of lemmings, that is such pairs that both lemmings in the pair don't hold a shield, but there is a lemming with a shield between them.\n\nNow it's time to prepare for defence and increase the protection of the army. To do this, Peter can give orders. He chooses a lemming with a shield and gives him one of the two orders: give the shield to the left neighbor if it exists and doesn't have a shield; give the shield to the right neighbor if it exists and doesn't have a shield. \n\nIn one second Peter can give exactly one order.\n\nIt's not clear how much time Peter has before the defence. So he decided to determine the maximal value of army protection for each $k$ from $0$ to $\\frac{n(n-1)}2$, if he gives no more that $k$ orders. Help Peter to calculate it!\n\n\n-----Input-----\n\nFirst line contains a single integer $n$ ($1 \\le n \\le 80$), the number of lemmings in Peter's army.\n\nSecond line contains $n$ integers $a_i$ ($0 \\le a_i \\le 1$). If $a_i = 1$, then the $i$-th lemming has a shield, otherwise $a_i = 0$.\n\n\n-----Output-----\n\nPrint $\\frac{n(n-1)}2 + 1$ numbers, the greatest possible protection after no more than $0, 1, \\dots, \\frac{n(n-1)}2$ orders.\n\n\n-----Examples-----\nInput\n5\n1 0 0 0 1\n\nOutput\n0 2 3 3 3 3 3 3 3 3 3 \n\nInput\n12\n0 0 0 0 1 1 1 1 0 1 1 0\n\nOutput\n9 12 13 14 14 14 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 \n\n\n\n-----Note-----\n\nConsider the first example.\n\nThe protection is initially equal to zero, because for each pair of lemmings without shields there is no lemmings with shield.\n\nIn one second Peter can order the first lemming give his shield to the right neighbor. In this case, the protection is two, as there are two protected pairs of lemmings, $(1, 3)$ and $(1, 4)$.\n\nIn two seconds Peter can act in the following way. First, he orders the fifth lemming to give a shield to the left neighbor. Then, he orders the first lemming to give a shield to the right neighbor. In this case Peter has three protected pairs of lemmings — $(1, 3)$, $(1, 5)$ and $(3, 5)$.\n\nYou can make sure that it's impossible to give orders in such a way that the protection becomes greater than three.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIACn8N2gC/+1a627juBV+FVY1EHujeCV7s52m9Y+i2EXzZ7tA9k9hGxlaom1OJFIjUkncwQB9iD5An6WP0ifpd0hJVjyx282lM1s4ERyTOjyX71wJ5EOQcsuNsMFF8GMpc3GprMgykdggDJaVSqzU6lrxXIAAW1Kl4j64iKNxFAa6lCupeHZdlDoviMWVzm4Fs2vBljrL9J1UK5bolP6AZpGJnFWGVkSCnVXJ85zWGVeriq+wubFrrS5maqb+wDK5W",
"part_2": "mNZGcFuhChEyX4UFp+JznOuUsO4YrzMN0wvWU/12IJbmwkGMcTUDNmfBNNlKkqRsrU0ntZqZixOM4nDEKEEo5Wq8oUjJNUaDmwJy1gv7tEpkuDWmVha2ihJvSG70rkgDR4cXOssZWYtRZZCj+94sm7esYQrpa2nyHVJeMEODT08/ZCM/wnM3EugZOEOKOZsP6mtkCZ0AhfCYnfIftLgmyVVxq1o0KVzcF+jG50LGflGEna05Y0mgq2YgsvS0FZjCwniFh",
"part_3": "KZqWCGf++2FtqutyYDTycY71mq1UltIq/NCtmiskQBo8gXLR53ElwaKjLoTgjHKndI/KDvmLSw2yI8CfaiFAUvKcQgRyyFSrwHpUpKgVg+YL7DKdVYE351MAH8lbytI8UHTbLW2oj9SpI4OgM/y9y5rhZi73TN54Ixz5a262NW10GC+FEC0bOACXIJ85i4l8YaxzjVwjj0OE43In+3l5uLwp/LbsgI2ss67ESiVboLh7jnic023joyyXnjkjxB4Ztkgpf",
"part_4": "w8B3LKSqcczyHNTfw4tJHtmhcRHnC3DKRqXDap0SeUwISXc7vZc4zdsuzyuHp4rzjR/K3oETq3dSJ2It8Ys5my5InH1RfncWDj6NeSCiApXeR0m2aWXd26+isqHW23fSR9ldk6kyd0c+lKirrvtHW9wh+66sGQLNcKooSqmkoPBLFcwVuVCn6vZjNZthU/s+bqDcId5Kumzrd7HZIX3mvPBRFnGspWPBrSYIiLwEr/yXuDYbscuneswmWTq7Pzp7snW2T",
"part_5": "1vlqm6CasvNOIoXqo1Fv2EHiz5XtQoF+oewn4LNTCKxtrGvUCmlpBWArtDESXaDrVb4k/Ds+UnBryOIQtqTaGvr70LuN/zqafXfP8yITptbNuWymzmcqZpH7jYnU6z9TERux8Se/PiEcQTwiovpk/eu/RV0+v2XxiMVjFn/TPOe/yMcDWUP5AzzTuviPWhlka+lbugt94aFum1THlZICWVrJM5QN8b5CMiOv/ipKjdovEk59vE1i1ya6OUAVVqND1E1z2",
"part_6": "ykQGw+Ium1yXwVzIdLRuol3V9loFDhUQ5E8yrUIsDIi3O0n2EeZDxlvdKRmRIX/YA/t9RHS40HP1WS3+GbQa2yg094G0zEC9bdpqttx6o6ji7kq5Hq5z4Xa0mUns2GZM5Yfaj7ohygMnzLqQraP0SHMOp3ArkshDkHzz3/8629/b+GpgTpvgRq7hQPqL7pyuOT8Bi6vmpLuhgOZt8WlUbi2CAi6uYUTdP7EjkMRmxjhTF2nSl+EnN5tlEsqDIi+LAM15s",
"part_7": "eUhkfot4FKBmELWApXDrFRMqOzynF2s2aqqVg0o4xpR+RmIiY+pbBV6V2NeVkMMWqX6JsldU7M1b929pWW6mqxochTxWamsJ3eTwxeiLSPr+GN2Ezc1K51ZoZJXlxbfY3NPr7eDwYzVbNZoMYntl3ysuSbdtUyaHdybtekv5rAxL7Dok/c+MSdHLrP/ok8CXNe4L0Na5qhKTJJtCA2ExTP95PpHJ9DXhRCpf0I+1QRJHmpxB1A9NUAwz9mJ2rhfCrnk0l",
"part_8": "cb9BPe1KexoPttpmY07jDV7m3+UR95ZrG11+joC8n02kc+R+2I/TNaDDf3RufR9EAyi6n0RwPab9DEYfmdNSoW2YS8k7jsz5UOZO1cqsnCqWz9Ord9pU8i0MSAtM6gBDR1ZZo522NY385vZpP381/X6uyS9Iwutkyenf6mLTuj7qd1GxP+zdn7wDzV+7vyMP96JGrydUpXxjQvYdrB49TraYKbG/mE5SHfrMI1W1Nvpys4Fr1iD86yuI95sl+rkIEgBlQ",
"part_9": "GBgfCGdLSJ7CUY14l7dEicCZnLCTAXLPhS3yzpaYurCuU/V4wz3ecI833OMN93jDPd5wjzfc4w33eMM93nCPN9wn33AbJia4mAZv3771k7G71h5vu8fb7vG2+7+47c4UMi+YhwHNL8jEYPphFthNIWbBBZsFrhBc1ykeYFQJXLD7l+ez7vyBnHEE2g8PjmLPIEKkH0P230vCvLJ/YHlM8P/N5PKzofJI7XNH9BTwieMefk/jFr8Yt5EPwRe0to60F+YYv",
"part_10": "6hHxk027OX5PL77dPV591S++/wUP5tv/Ao4xAfwfY6+MYteSd/4VeIhfgV84+hBOW8/HxUzQhOJv4jnyYbGrZHxAUPfMHSt6PM/zzCza+o+Mx905c/6PMufcdfcRw09Z9++2u8zcm7rn/0lg3w0/mX76GFx2Wuonwx/4543n/N5tkfb8vK4oTH7Qpz6zPLyH0M3Yl/I8yLlZf/Y9O2XV17ijurRAdXH7Jydv6rqc/pnZXNdKfm+EsGFLSvx8d9tSCSr7SwAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/81TwQrDIAz9lZBzD8k6xtZfWcouG91g2GH1MEr/vVqtOFp2Gx15xuQR4xO1x0a3Vl0vRltzxwp7wYd6WdMJVnAWZBJRBAQMs2fvHStYQCrgVBCjtQKO6+mjQ+miiVswK03ysWySM7sgfMprT7TW5AcrwWO/PZLiI5yAaXskQQf4naVNCIJlRHgp2eXDn+Cb6JjUAxbYmffz5n6Ttm4aRuKjQOJlAwAA"
}
}
|
codegen__primeintellect___2304
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThere are $n$ children numbered from $1$ to $n$ in a kindergarten. Kindergarten teacher gave $a_i$ ($1 \\leq a_i \\leq n$) candies to the $i$-th child. Children were seated in a row in order from $1$ to $n$ from left to right and started eating candies. \n\nWhile the $i$-th child was eating candies, he calculated two numbers $l_i$ and $r_i$ — the number of children seating to the left of him that got more candies than he and the number of children seating to the right of him that got more candies than he, respectively.\n\nFormally, $l_i$ is the number of indices $j$ ($1 \\leq j < i$), such that $a_i < a_j$ and $r_i$ is the number of indices $j$ ($i < j \\leq n$), such that $a_i < a_j$.\n\nEach child told to the kindergarten teacher the numbers $l_i$ and $r_i$ that he calculated. Unfortunately, she forgot how many candies she has given to each child. So, she asks you for help: given the arrays $l$ and $r$ determine whether she could have given the candies to the children such that all children correctly calculated their values $l_i$ and $r_i$, or some of them have definitely made a mistake. If it was possible, find any way how she could have done it.\n\n\n-----Input-----\n\nOn the first line there is a single integer $n$ ($1 \\leq n \\leq 1000$) — the number of children in the kindergarten.\n\nOn the next line there are $n$ integers $l_1, l_2, \\ldots, l_n$ ($0 \\leq l_i \\leq n$), separated by spaces.\n\nOn the next line, there are $n$ integer numbers $r_1, r_2, \\ldots, r_n$ ($0 \\leq r_i \\leq n$), separated by spaces.\n\n\n-----Output-----\n\nIf there is no way to distribute the candies to the children so that all of them calculated their numbers correctly, print «NO» (without quotes).\n\nOtherwise, print «YES» (without quotes) on the first line. On the next line, print $n$ integers $a_1, a_2, \\ldots, a_n$, separated by spaces — the numbers of candies the children $1, 2, \\ldots, n$ received, respectively. Note that some of these numbers can be equal, but all numbers should satisfy the condition $1 \\leq a_i \\leq n$. The number of children seating to the left of the $i$-th child that got more candies than he should be equal to $l_i$ and the number of children seating to the right of the $i$-th child that got more candies than he should be equal to $r_i$. If there is more than one solution, find any of them.\n\n\n-----Examples-----\nInput\n5\n0 0 1 1 2\n2 0 1 0 0\n\nOutput\nYES\n1 3 1 2 1\n\nInput\n4\n0 0 2 0\n1 1 1 1\n\nOutput\nNO\n\nInput\n3\n0 0 0\n0 0 0\n\nOutput\nYES\n1 1 1\n\n\n\n-----Note-----\n\nIn the first example, if the teacher distributed $1$, $3$, $1$, $2$, $1$ candies to $1$-st, $2$-nd, $3$-rd, $4$-th, $5$-th child, respectively, then all the values calculated by the children are correct. For example, the $5$-th child was given $1$ candy, to the left of him $2$ children were given $1$ candy, $1$ child was given $2$ candies and $1$ child — $3$ candies, so there are $2$ children to the left of him that were given more candies than him.\n\nIn the second example it is impossible to distribute the candies, because the $4$-th child made a mistake in calculating the value of $r_4$, because there are no children to the right of him, so $r_4$ should be equal to $0$.\n\nIn the last example all children may have got the same number of candies, that's why all the numbers are $0$. Note that each child should receive at least one candy.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIACn8N2gC/+0a7W7buvVVDjwBsTfFkGQ7aYz6/hk6oBiQDGiHYYiClLFom6lMuSRV17u4wB7iPsD9v0fYvz7KnmTnkKIkfyRpinT745C2KerwfH+QRH7uZMwwzU1n3PmLEkv+Vhqe53xqOmFnVsqpEYW8lWzJEQCnhMz4l844jgajsFMoMReS5bcrVSxXhOJdkX/mYBYcZkWeF2sh5zAtMvpBmLucL6HU9EQgODNXbLmk55zJecnmOLkxi0KOU5nK9wuuODD8BDKA6ULkmeISZLm8wxcZzJAqBHEApr",
"part_2": "AQQgKDj8ShmjNluOzDn1tPYDibIkqYM+QxYLcigG4QQ5rm/BPgYzWSQQ+mTGaCa8JMnAYiODULx0If/ug5WRN/mjODzFjiqljToFBIdI89+5zzmaEJ1NzCAFIBbYi7DBCN1Zaj3AfSwN+QEt/jANZM74CHgDBTlk/L3HJj1kWlJw1BTpISqUDh6Otv//nnrxanA4Bi1uhWV2gruS23+H4hlvjMDMwLA8tC8UZBCyaJNqH/NpxO8m9BGoLieoWuKD7zfNMnhfypUEuW55uwkkroHapobzFFFMF927j38BpE",
"part_3": "0AtBl9OFI0r2x1l2e9/SzVP4aMV94yYP4LOcvkFfq8xlCvtlMX885JANyT1rOeRbxu3DX+WsUKaU+ESq0DbcFKlxgQ64ZHJTq5LeLdBd5qhDSUzwmq8+vCvcYqY/atgUJWFBWvlq7OHppVJsQ3x5rgLIuOEKw5bDesENSUBYpkWJci4ouJrVO4HUOEWtODRnMz0tlEKD55stZ15woeAzy0u+p58Qgw10seRkLARcOgYyPhNSkHpQHRkKAUuBgfaR9+EtGtXYEFoVWgvMSSEgcAaktjXbWB3uyJMVKKsw1r",
"part_4": "CpPKW/t3JVGjuiqSsn7UwobSAnzRibvNCfGFDCwzAWmFnnqCvKBY1ryuo3jqIo6D0anELuuVC/RVzyL1u0feKs6FrVxSHkt0lINLPCaHqy3EQVF3k7C6Jz8BVT1gZ3G9ArhpFwkGJ4mGTj1Iooqy3Kapuy+jbKlfavStNW/9tZo29ZWCuiw2VociXuSsMfd8WicUTvRHve5yWpHTTE8oViwtd/XV59/Td01wLrVmngU1kYrntOTcTUWmjeAP/9zbsD0FDs+k8f9nXscGyblJFi2ZZiGSr2oAJ3nUtb76pz",
"part_5": "bkslASJto0SSKDXHqM52kjJcFla9qL9WFOqGBOKHOw78U8nyENAYVs/+rV7YINNYIfRs45gokCHadcDB2tyH988qXXvF8/E6VjHkOba1u844zyxwL0CaUpxNWbV726V2CeUkXeQl6aqVwioXbkfLmy9sucq5ruLFpq5UjlIZQQQxtiSViR3ihHVcG16pRG9NZQwDAoHYRppbO3RrEwKPLYq4ve7yqgU7cLBR/bOHv1pd80s+1cR2OzS4kyQE4dTrK2gT6hltuXB7MKAvO0rcqB3/+HiqjX13KjMLfarod0",
"part_6": "jWwt9RY7Vth7eZTlofJvpVUWqli7vNdihRSqySRh9w+9KIYN1jtLOtc5XTs0vk9ndiyHWD3+5B91bZ4S7SpNGBrZ8exuUF1EGzm7Q5sc7obXoP7QxbfBzwbuH8sbKl5hTkXhNUjtGxxdLX44dzNyYQPmWlrvbEw5bytss81UpvFH/csLYinjGqhsEWqkpQLB27crZ3q1YtdvHBWI2Ctow5a9x1e4+zpD2G3SVhJrDqwNNVO694WUmvJxr3WJva33zetGZBgq3022zsPHdVygZ8mXNihzKGdZB+dbxCNWEc",
"part_7": "wlogepRFm4yOMWga2gxWWFzVwQlVZxsSF2ELCmFql7Rjqk9+/qBHeBQ3pap2gkXG+3iCVHyG+pZTOlDKCeLuWia6vV4qf/cl3IT/CE0cmiQ0g8mSrfCtCSuIvl7lwkGySY6W7j4EgBB3T0KkUk+uo5vfWxkYPrxXJacxbYMFuZDCUynvyh4eRwH/CAY/VjJ2LW5eT4Qd39lxV56K07jnQDVOTeQpQZ3Sa0KLm1L4tOZdHd57jHmoJlEYuYcdsjmXXd3zkPSHSU+8vnenRsT5k76+vxlD/odJ3MDwnKB+2o",
"part_8": "NSNVRlEyTtky6uQLHGB7mQbQaIXSeB6DWzu2qZTPJaLZOJagDdiCi63y261s+6J1gSTnpPc+KgWwoOucwmJ0Brea752OO7vDrpoddZs6PHGcWExOfKSY9XFscri+OVxfHK4nhlcbyyOF5ZHK8sjlcWxyuL45XF8crieGVxvLJoriw8Et0ZX3c+fPjgDnypPF5fHK8v/gfXF17OVKLvdW7CDu6/DPpi5/rntGM2K552xpB2bCjcVk7ewa1QxzqNezlK26WzXTsRrwUuXIGz0FTksArCCOvoED9p55cQvp3Y",
"part_9": "MG1qbVNsDxHCqkvTz8I+SH1Zbn4fFmHwfPaJ1aj6PIQ4fi5Sb4Atzp/gfgS+faeKYsvp40QSVFDyXAKJEyGu27BuEYy2m4WkN/FOi3bbY1wisZHtr3wfbfUGYK8/V3mNeRLwMp7h6BwbzV6QLBEgCzF+uTbE2Qti64KWRRXHrr+CqNJNTOqJB9SteSxuInOBH9ccueTJ4KRltuNggINR1d1j7Ofd2M074KTdRw2SxAM/17GjOtrJkdpOEJPcZ9icyDHFYmy1cE52ObdtVGkwSagjigEuSIYV245zkgWSV9",
"part_10": "Rx9sLqG7EMkor0OU0mXt/ORheEziGPL3yvfAfJn1fkHYNnfi0uG1j07t2wcu3IHiiejFcUG0W2VIZnMPAdJ92A5uNm7PrQj91kvaqGrIGHHkMNXMPXSEZRBTP0C78j+8UPZr/vSdgeW/yiGOMXxZi4TOn86UWxRpD8EKzxI1h9Zn92lWpYjR/PPt9RMmrUTiMvqYuo1shLekP8Q7BGNe6X9rH4hX3M7xTjH2Ktxz03gf97Shg1u9h6H5vASwbyWXsf6EPDNqyUj1K5oX/F1relFJ9K3hkbPPn98l/KF9yGyy0AAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/4WQMQvCMBCF/8pxc4cmsQ7dXXVwEq+4KCpIKmkySOl/7yVpQtpFjiOP9747uIz4NL3T95s1zr6wxZHwrb/ODoQtXAkbIl3DUhtNWAHhvnQXRoZSoDIlWQkQIRXZTds5AU/IoMvtMhKbOa9Sl5zI9JqLTuet3tnivMvhzFEDqeLY8ZQ3FDKyiikFO+7/rORjVlE3YYWD/X0e/NXG8TPN5YJ+rYIBAAA="
}
}
|
codegen__primeintellect___2307
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nArkady bought an air ticket from a city A to a city C. Unfortunately, there are no direct flights, but there are a lot of flights from A to a city B, and from B to C.\n\nThere are $n$ flights from A to B, they depart at time moments $a_1$, $a_2$, $a_3$, ..., $a_n$ and arrive at B $t_a$ moments later.\n\nThere are $m$ flights from B to C, they depart at time moments $b_1$, $b_2$, $b_3$, ..., $b_m$ and arrive at C $t_b$ moments later.\n\nThe connection time is negligible, so one can use the $i$-th flight from A to B and the $j$-th flight from B to C if and only if $b_j \\ge a_i + t_a$.\n\nYou can cancel at most $k$ flights. If you cancel a flight, Arkady can not use it.\n\nArkady wants to be in C as early as possible, while you want him to be in C as late as possible. Find the earliest time Arkady can arrive at C, if you optimally cancel $k$ flights. If you can cancel $k$ or less flights in such a way that it is not possible to reach C at all, print $-1$.\n\n\n-----Input-----\n\nThe first line contains five integers $n$, $m$, $t_a$, $t_b$ and $k$ ($1 \\le n, m \\le 2 \\cdot 10^5$, $1 \\le k \\le n + m$, $1 \\le t_a, t_b \\le 10^9$) — the number of flights from A to B, the number of flights from B to C, the flight time from A to B, the flight time from B to C and the number of flights you can cancel, respectively.\n\nThe second line contains $n$ distinct integers in increasing order $a_1$, $a_2$, $a_3$, ..., $a_n$ ($1 \\le a_1 < a_2 < \\ldots < a_n \\le 10^9$) — the times the flights from A to B depart.\n\nThe third line contains $m$ distinct integers in increasing order $b_1$, $b_2$, $b_3$, ..., $b_m$ ($1 \\le b_1 < b_2 < \\ldots < b_m \\le 10^9$) — the times the flights from B to C depart.\n\n\n-----Output-----\n\nIf you can cancel $k$ or less flights in such a way that it is not possible to reach C at all, print $-1$.\n\nOtherwise print the earliest time Arkady can arrive at C if you cancel $k$ flights in such a way that maximizes this time.\n\n\n-----Examples-----\nInput\n4 5 1 1 2\n1 3 5 7\n1 2 3 9 10\n\nOutput\n11\n\nInput\n2 2 4 4 2\n1 10\n10 20\n\nOutput\n-1\n\nInput\n4 3 2 3 1\n1 999999998 999999999 1000000000\n3 4 1000000000\n\nOutput\n1000000003\n\n\n\n-----Note-----\n\nConsider the first example. The flights from A to B depart at time moments $1$, $3$, $5$, and $7$ and arrive at B at time moments $2$, $4$, $6$, $8$, respectively. The flights from B to C depart at time moments $1$, $2$, $3$, $9$, and $10$ and arrive at C at time moments $2$, $3$, $4$, $10$, $11$, respectively. You can cancel at most two flights. The optimal solution is to cancel the first flight from A to B and the fourth flight from B to C. This way Arkady has to take the second flight from A to B, arrive at B at time moment $4$, and take the last flight from B to C arriving at C at time moment $11$.\n\nIn the second example you can simply cancel all flights from A to B and you're done.\n\nIn the third example you can cancel only one flight, and the optimal solution is to cancel the first flight from A to B. Note that there is still just enough time to catch the last flight from B to C.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIACn8N2gC/+1aa47juBG+SsEwEHtH7Vi2+4npADuNLDBAsBtgJj+C9sRD27TNaYnyitR2O4sFcogcIGfJUXKSfEVSsvzox/Q6AYLYRssSVY+vHiwWif65MRVWGGkbV40/5iqV77WVSSInthE1ZoWeWJXpkRapBAGGlJ7Kh8ZV3O2fRY0sV3OlRTJa5lm6ZBEfsuQnSXYhaZYlSXav9Jwm2ZR/QDNOZEqF4Scmwcg8F2nKz4nQ80LMMbiyi0xfDfVQf5vfiemKxlkxX1gSmoTKyarJnbQ0g0YS",
"part_2": "NFF2Rd+Szcr7mw79Sc+y3BZawJBVxJpySQJ/OqOpymEazRIFkSaicWFrBIKSzFI2K997LXXx7yLgmPrxdzx+02GkHysRTd3cw/3OwVjRVC5FDlOgFK6mNEulBmFTjOJmxD89/9PHT6fTcfcQyCpFniu4FqzvqGlHollxJzA034aRbsHwYJ+BMfYwxh7GuAZjPEq3YdwwjPEjMBB0raVLHq9DGdJyDkQKSRCRySjToEJQC+MTpqmaJ3YRUNd95/Q6ii87FN4sUjNHlOlkxfeA+4WGQ2STGCl6Q+wu",
"part_3": "h+zPWeF04m8iE7YizYyl5l3lrQ69n9HKkzmS8CKikI3MrpElDFvZTi1P7wW7AXjGeKOBShiSIgck3CwzY7zp9wuVSKeCGWih0i0edmSdpUPfqeABFqekCXGrIaqFJWIPsPhsCSqRJKvSlkfMrL/OckqkMVXuAJMpJgu44V6sAAEKlHXBhAtKgIw/lwJkN4wAKiPMbQXjmiexd/xQn/DnvV4W1t2VeTJTOcxJlHYpY4XSUM6mgF3OZW54RkWcz5FP+yikHcebEbeaMUINEDqi1N/18DOZAmDc/csp",
"part_4": "MwSKu0CIjEhrw5CKeTEa+yfwXDbb//zHv/72d+dyXaRjme8vCn5aP0ZSm3Jlzrqw7fDvvAxZXeb9rvzNyEXwvlnybPsJFa+agkbCo9Mt33J9mipjFSr72scIMwYQQ1ebs3wKdc8VpcrxoKO3uPZwxQAcb9yz3u9QNtPU7N5waChNlQ12ofIdE9IXm/BMQatMGDsTxlsmgOarTAhhq5kQ0v6Hwtbz/r879X7g9e1eGRlevLSOlGVkt3jsg5aKB5Wqvzq3ACPLrXvg9w8iXcK84ANXB4Z6QKcU49sb",
"part_5": "6pj6eDjnmx5uL+FzB955DqOxc5xn64FkgK9jY7q4S70N8pM6+QDyWGbM5Jfhc1HdsaryM9R9yK0/1yCUg31vV7Ds+8zKKrI3mTaKM89WpU16yzv08cmM312MXeZywja5hrlyd77bCuywuUwf8OWMLxfNreqwi2MjbR/B0avAXJZg4u5uR7AfTb+CBB6+xjugHlmY7X22XrEYeFjT0D8khWsulFtxA9va6090EbOsyPd2EawB4jilw4xYCCfdijvfooSKuis8eiIm3nSnvZSTiC2IZcFnIVy+9jjT",
"part_6": "ua3j07oOJuRXVVGMwmO15KMg7E06hgOO36BVnKIRq8v1JXdbbJDnOizu3MquqPTq6wPTIZ5Cvor4VhysqO5A/qXgCaS5//eucBItKs8TXqzWDsXTn+5ZELorY7ELKe0ms8iKZBoqIgbyNXDIAG3GU56/32f3/C7saspNDMvJpS1y7zNscWQHu6NczmAATMZWCHHANgSF0S4iY6FoHil0yDbLEhPNcuGaYxMtpFj+GE0yt+dyI7mMkAhiFY1RtCc2MiuD98tV5LZjzD7UQXgOHFnKMEHUwS4Ou5si",
"part_7": "NxCToBrbVtz95pvzNsj1jK6Jn7hOyqXhp06XfuvGuISm2TRQXL5BFZ7y023rJI667ajVjWJcy/uTuP2JKXSdBD9xjXJNHzN9YHNknh0C5Iz+8L7VviodmWBNb6Vi2UJMsENggzhmHaxvU+4AWu2OWSawqt1uB/YN/ttNAcmaGnMei6tbtnakmpazxoEZ1aVBSOuhfRI75of9zGtIpYzv6iJmSSZYyNeJ+FAT8RS9J697gCHv4wikdWwe2hPEHzbkYiaVCpezllm/cjOohZ30LCnM4vpjXsiSTu6h",
"part_8": "szkGQYwt0HVQLvO87acac6Vo8aB5qAkfHaWRFZEdR3fINQ62HxcbT+ONJ3Qtd/S7a3T58Lm7S4M0/gQ0vj9wA2DuBjlqfc8BUxwwzLC5bN29ids1KRMQilv1ibeWYj3sd3YQ85Z8hRjfjkH0liY13qDpzTVVGAJsHqXW3Ylqb6PeQl4OWcBgFSWbwzPekJlDu92WBDZb2e/F5j4CPko+Bm3UM5dpqGU2xxCeQ/k7HvQcD3qOBz3Hg57jQc/xoOd40HM86Dke9BwPeo4HPceDnv+fg55SiGlc3TY+",
"part_9": "f/7sNzPVuczx0Od46HM89Dke+vzvHfr4IVS0xqeoYdE5osI1bn8eNuxqKYeNKxo2XO6MQulsRBhxqeJfrju9dau30etBvOPJfLflmND08fAvEb1c0bo3DM1h2R3uU3DyCgXrbvIF7eROP7nXzHVj+dVoYgpfRoO/3sHsRLzYb3xlXOccpguKL70v+3RG53ThYkcxTAT5GcXnB1MPsRB5Xqr32lhXUOSRUM+H4ZRfHlp/HJNL226Vqfy4tpuHPZSLCg31kIBIECTgKfXODgaH07qKs0tuoNkr/fSV",
"part_10": "wl2knxf/avBb8uHceH+y9nq/RkPvBRpeNx36LgCDejIMeXOJ6etm+AHdFftoV6ac/gfzKKb+4SZNqPJlNfKTKIZKOO9w+dQPsYjLWHDh85Vhf4E9+7WOOnUa+gcNwzrEgwPPt03/uHnR9QYcUMkpx/W0u2dK7KuVh58lAzoPU75f6Qx2YqhLgy6jO+vSeZcuugf07aDWyPRqyg9bjkP4SgWHTY5a6pWpffByX342biHskT4pfq5Lel2O+mD1qyYhrNs+QZ9enj/xv7WbUaHVj4VsXFnsZn75N66G+zUXLwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIACn8N2gC/31S2wrCMAz9lZDnCW26+6/Y4YuigkyZ7YOM/btJO2sfph0kzTknl2Wb8Tzd/Xg8uMm7C/Y4W7yOD++eFnvYW9QKKtANsDfWjjU00EqgGa0D0QEpIM2kZmkbYY4sFmCRgEDLE3gK1vxgK7aUsQbKwMasyAQPZaYxWQUZTKlYJhOVHAkSRd162nTrJGs9LAl9cyAbVhp8BhLLPSkphNWczLtR31k5jGvrVjjurU2rA+LSPGEJVAHVodwg9e7eZZ9ip1Oj7Wu1BaYXMX+yhwULfLrX7cS/wOTZLW+KfHaWGgIAAA=="
}
}
|
codegen__primeintellect___2308
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given a permutation of integers from 1 to n. Exactly once you apply the following operation to this permutation: pick a random segment and shuffle its elements. Formally: Pick a random segment (continuous subsequence) from l to r. All $\\frac{n(n + 1)}{2}$ segments are equiprobable. Let k = r - l + 1, i.e. the length of the chosen segment. Pick a random permutation of integers from 1 to k, p_1, p_2, ..., p_{k}. All k! permutation are equiprobable. This permutation is applied to elements of the chosen segment, i.e. permutation a_1, a_2, ..., a_{l} - 1, a_{l}, a_{l} + 1, ..., a_{r} - 1, a_{r}, a_{r} + 1, ..., a_{n} is transformed to a_1, a_2, ..., a_{l} - 1, a_{l} - 1 + p_1, a_{l} - 1 + p_2, ..., a_{l} - 1 + p_{k} - 1, a_{l} - 1 + p_{k}, a_{r} + 1, ..., a_{n}. \n\nInversion if a pair of elements (not necessary neighbouring) with the wrong relative order. In other words, the number of inversion is equal to the number of pairs (i, j) such that i < j and a_{i} > a_{j}. Find the expected number of inversions after we apply exactly one operation mentioned above.\n\n\n-----Input-----\n\nThe first line contains a single integer n (1 ≤ n ≤ 100 000) — the length of the permutation.\n\nThe second line contains n distinct integers from 1 to n — elements of the permutation.\n\n\n-----Output-----\n\nPrint one real value — the expected number of inversions. Your answer will be considered correct if its absolute or relative error does not exceed 10^{ - 9}. \n\nNamely: let's assume that your answer is a, and the answer of the jury is b. The checker program will consider your answer correct, if $\\frac{|a - b|}{\\operatorname{max}(1, b)} \\leq 10^{-9}$.\n\n\n-----Example-----\nInput\n3\n2 3 1\n\nOutput\n1.916666666666666666666666666667\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIACn8N2gC/+1b224b1xX9lVM6aKiYms79IkQFnDRpBDRpUDsFCtNVRuSRNPZwhpmLZVUR0Ne+9wP60C/pp+RLutY+MxQpc5SEUB4CkDKluZzL3mutfZkBfDOap01a62Z0NPq6yhb6pGh0nutZM5qMztti1mRlcVqkC40BuJQVc/1udOTYXjQZlVV2kRVpfrqsysWSSzwv87daNZdanZd5Xl5lxYWalXP+wZizXC9UW/OMQ3DlokoXC57naXHRphe4eN1clsXRtJgWfytblVZaXWRvdaFStdTVom1SWqTKc5XB0gtd1eocuytHNaUqLPXZu3TW5NeqLGZaXXOF5RKnmyaVWMqsg0nNZVavr32kltnsDfar0mKOlWt9sdBFo3Cm6sv2/DzXKmtqpeENrteW+rysFmmeXx8p9fXWqeNZWTRZ0ZZtrer2rNbftRr2HRjTc1pRWepZnqsPptPzK",
"part_2": "p3dFONCPVXOwe2Ne/tBv04tcGByRjBTwGkp9SfdqDfqWFXqECthzkRlFm7Q41wXF80lweLZ7LKsAWS3mHXP1h9H981ELU8d/nInyrIsHt28uTWGv/nNxgpbDH1xD2eFU5KT6TlX7+Hcbm3n1MYWtCVd2ZKe3uS3wMDpDvsrgkg/orobUd32VzZGFLe0qwEo9TloNbb9yFY8xCrL0/cuvDdDrgK0bbNxecAkSzEeToq3IESQO2c4pFlFsFbAjYuyUYWe6bpOq2scZReXZ2VbQfEH6iqDEIjrVVUiAiqdA0XEalnNNbR3AtJxt1JXuFBPZGTRLs50ZcSw2rkmrWluAmd9DM2BDdlEvT6AyGfcLW1Upj5WryV24El2q37Pv6/h0edIJbKEfrdEugHQW/aDQs4bWqW7ONar8NZrUUz/8RdrpGflW20RrWlxyM9JsWwbOeKlF0wDsLNReYYVGJZpxl",
"part_3": "0UsxID28heFWrsqB/+9V8c8Ldj28q27YP//eeHf/57S2it6dLq96k1lp/f26hQ86xGKpg1W/OXWf9+KNxfvXPtz22z7hvSN1INgak0CHqb5q2+s/dBlC2FXFuBpfqKYGeI5zMxus6gDkyalVWlafO5pL70rC7ztqF67pSkqwqn81LDSwhRv5tpzHTsv99A4Umn4a9QSZgoc918iHXqul1oI5TrNQuYGSYiGpreXezAeN1C2xhwZqkXkib07A3udsXEGN9bvrFo58OETvRp9vsUtp19f3sznRo1lRVr3c0ifXc7RgieHdyq6TTX34kfh8ntB+sEoNYslrnuGBClTQtvWrjKUw5HGYamhWMlTjj8iXrJZFxihX/doHAKCqxj9WXZ5nP4SZbFL+GgK2IYW3Inwbi84r2uEPd1l+tUummrwqTXcq4tFPRKn4NhFCNU7yfqa6m+3gpNrDwr26JZj0h",
"part_4": "TwMHmE/UJqj/YOGFTAK5fVFrzhrn5F9mMBW9B7tKqemlbljQQryxTDfoGQ8YbMdRGDcJ7VaVC9bLSMIh5jREOP2T8Mq2aDELHrLrbAMNXscMKVINP3Q0HlJ+c0MKX2B1X5vpcXejmebsYdzegDBp3cCQuKDH8WNnqCRzMuFX2D8ZW3eaN6ob0f5/A95QIUa0wFPuKTd2Oxul+8NVlhkwzlovIhzY27EBT3eeJejZH0LUQLLDvXLpbTwiHcWszePr0eNt+66t+ieRonOQSAJDLFlAC0TFgqL9m+mp9lhl+eNwd/FaNDw1M68t3woIVPfvfLNFYambWfv11sRipjI25B2YGWDedntloxZeJc3NLkpqM/hCHH0qimM9Nke59f2WqDWKoNNlKFl+xgnUbWbXTQCuGYvK4V0HRCWHC7To1vE8z1r9bVHYEZcaqbTx/fKyKIaLNLMZax7hAJnSvxZT5",
"part_5": "bDIMyjH3/VUN+ndUS0xJkZb114cCDwPBAPNPh5m/i3GTJDYrN85qRkxz2bnQRRzamE85fIyAnQgod9ZjulnqwbjryZAWAqk6W0C3fZQwZTIT1P04DPisu3fME+57sLHOpyiY8D8luKZREsNXjc5q4N1STx01/uwd2kQpuBmzokk0ZmDdQb7KRrO0YEqfZyxB6F9WI3FRpqZ1l326OzTlWL20X6mP1HjNBT4U9LPRoKK/gsPoVi8069W9gUf3lMPgALJbZxemJT2U7yoHbpACKXQZE2tNJKNjwcM1i/jZCKh1k/oZk7UJXeJYbSFNwj2hPJu/3WvlV6iVcWYs+OiRVFMcZg/ppq/HT9QfKhSLSlocXigUU1gzlu5qfHAwLVJcydGHA6wlLjeT7pZV43GUQ4hsLz91vJm1qMO7uxDn5gBR64RDmsusmj83TcS0eI+A4imgM2avRjLZksTM4IOj4",
"part_6": "lB1MP5OudNC2r/xyrRDtW7H7zBc5sgETndxtFr83u2DdcikHRPA5G/RVNlZy8eFs2u5//yyPbtEQ/gcvd/l+PkX33zyxbMvn5989ccvHPsAbaQAhxYSKs8KnHdd5/6V0P6V0P6V0P6V0P6V0P6V0P6V0K/klVC/SD06ejn69ttvTf01C+1fEe1fEe1fEe1fEe1fEe0f+/eviPZa2b8i2r8i+imviCRo0UuOXk1GqPkNesvRy5vpqLle6ukI8hhJa3vaNa2jCa4I4uamN+1baKwjN0vTR8vdH+2lOQkP0j99P+6zfS/bsh/8/Py9XO6l3IHdHnJsF89cQXLIt9h76PPzd/OMb8ob2M9/ZN6MTpyB/RzLjh/fP6hygL3H16XB0xvc75fxb0gvrhU88n6++OcPKsa1nOBxo487yn4DPvpW+Mg7OnYfFHA0UKGKVKwS5dgD+wf2L7G/DdUmMCKGGR",
"part_7": "EMCVWwHXHfikPvgZ+dAQixe4TdY+yeAIgBABxEUeA/8LODAV0SdLGvBzscB0ZQdkAlGsDB8y0/tqMwcb3tv3cILolmbE8BOAHDGjJQTqxc/PZhj4dYt5ULrkiSA75c5WJYQLggoUi50G4IN0LleXQIP2DUHQLT9QIrdBzfjp0kCX3PT7xo83xHN2B4SAAjmor9qWuH9ruUmLEVLkY0E+bDJWNuQkcBuysBYdMZuuQJCpiYbHfDiS3bjQPX9pPEsePI8/3N813ZYFDAE1gCQz3qIqBtAr8ASwNjQZ5c0VYK2e48pzOuOOh1dIl3zkBsxaEVxknsJUHkOokbOJ63eb6jGzArovUUl93ZBRtpuIjMFXgDMpPQcrrrShjCvcBo0RFFOeKPBCtc3l523Mi3Buw35/4uOYIChl1JohLYBAsiFbnCSqAS8GELzExcgnOMRELbo0T5IX2MYxUKMzHSG/7",
"part_8": "hFkIcfIIw+Cbh5NvK9034+7jsqcQlbAlZ9QlXFNH5KCCGCVYIiWSAnIGEhfDEagg9GIkDYIbjWMWG/IAQB1gBSyPRi6qwD1KOw4SPyb6KBXwAm4jwvVDF8BPcYQ9bBZHkI4mTUAqUDWeEqQCxBjMjFQ4l7cCzIjsJbW/guzMlZCIh+jASaMFz4AJ7YC1YgZ1wiukroKhgLRHxCFzAckciEhJBhcakwyVsQBGsgk84L6FG0kiqQAhoQuYT4AgFOF6XTjwJyVjyOKgChoDeF3xADMQAmhmYIbkldqAVpEFNYAzECviAEQgDSXDmsRwHogMwDjagDbAFFUGEUBQ4gbpAHbTE4LKpNAgS1MeSsEMRVbydEjR8lhc5UewOfXelJBS9+yId0TLYgSmBiJIceSKkiJgAbE/8BSnElSz57AVABfwHiEQtJnAUWUJcgBhIBSQABlBGZIi0CstkRpCPJEqB",
"part_9": "EZM+OWGksLOAPsAjCAV4QBeaAPMgD3SyrEk8+YIxNACCmGeFfOYjMOmLMpiDXPIfdWnNBEJCSYFYE1ggDLRBk650VonkYJASback8H08X6FeJEPfXSlJJJqBOuzypZbA20TaDF8cC7poYUDQ2UTiAaSw+LgdG0AllMxlpM6yz0aJOc3pAgPAJ8IttJwQOPAJDYC4UPK41FAiLIk8kdgT7ETXTEBkE5R6rApgNZQ0KrrxTRgmpBEyAHGMR180kAjZITEG/UyEtsSNK6lBYi9hiLmSQD3J1GAHCoUEwHk0kLi8BA/YjhegFxn47lxLEJn0h5IRYYS0BkCyf7IJJ6uNR78SiXuw54nQSVlI/fui+EjSWSw1weRxV3SbSG/GDkIAjyVFutLjuJI5IkJuRMzSIoyAaIfdP0PCVIqISciEq0uwICVJ9JJmYklnIm2fGLNq2UIo8GU8CNyxJGimyICig",
"part_10": "KoYy5KuWO7M0440CInkOYgM3HkDj1xBbFuuG9lusv3r2btSQhukWwJWQIGykIQh9TEiE5F0LGCFSnVpLrij5hNy5rD2gymg7XWNMnNYLB2DVPdQCnYo8jZZwiAWCZx9LMTkFAiTDMmVLts+kAz2PD6muAK6dEQSHyCZACeiZ1vYkIocSFZjFJnWUDBmznMkbnwhx5PWRGIolkc/qecQBSUose5LHWFyHUpcaOMD+4FSsnMtYV4QFE3rxYbHxLxH8yl6yRaBISUmxiRPkhKcS4zrodRyqR+xlB1XmI0luAQm9kqS7ECsb5K6p6TK+mTGF+rZ9UiFCfhAQXkLNQy0iASYCAUzbNik846FUEeI6bQdS7PGUhewYw8FXmbciMQ7kmXZO8hTBymQ6s86Ku1aRDGx8ZQ2Boj4Qx2Xa/lRHDnuwLd7JHnF/0RZn7ZF9l2rR0dN1erb/wOnV00dhTkAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2309
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nPeter wrote on the board a strictly increasing sequence of positive integers a_1, a_2, ..., a_{n}. Then Vasil replaced some digits in the numbers of this sequence by question marks. Thus, each question mark corresponds to exactly one lost digit.\n\nRestore the the original sequence knowing digits remaining on the board.\n\n\n-----Input-----\n\nThe first line of the input contains integer n (1 ≤ n ≤ 10^5) — the length of the sequence. Next n lines contain one element of the sequence each. Each element consists only of digits and question marks. No element starts from digit 0. Each element has length from 1 to 8 characters, inclusive.\n\n\n-----Output-----\n\nIf the answer exists, print in the first line \"YES\" (without the quotes). Next n lines must contain the sequence of positive integers — a possible variant of Peter's sequence. The found sequence must be strictly increasing, it must be transformed from the given one by replacing each question mark by a single digit. All numbers on the resulting sequence must be written without leading zeroes. If there are multiple solutions, print any of them.\n\nIf there is no answer, print a single line \"NO\" (without the quotes).\n\n\n-----Examples-----\nInput\n3\n?\n18\n1?\n\nOutput\nYES\n1\n18\n19\n\nInput\n2\n??\n?\n\nOutput\nNO\n\nInput\n5\n12224\n12??5\n12226\n?0000\n?00000\n\nOutput\nYES\n12224\n12225\n12226\n20000\n100000\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIADv8N2gC/+1azY7bRhJ+lQYvK2EVofnPHthL5OAAvjhBYgRYDL3jHqmloU01ZbLpmYlhINfc9xHyZHmSVFXzTxpZzkwE7B6kYCiqu36/+qq6DeSTs5RG1so4F84PVb5RL7VRRaEWxpk5q0YvTF7qKy03CgRgKddLdedcuDyKZ05Z5etcy+JqW5WbLZr4qSw+KmZuFFuVRVHe5nrNFuUSv0DmulAb1tT4C0VgZV3JzQZ/F1KvG7mGxXtzU+qLTGf6B2VUxW6r0ihWalK5Lm",
"part_2": "W1ZJLVpsoXprhnuV5USpLJWn1olF6A7Iptyzo3OYSSQzprVdVMXrkzeHgzNp/P8e2T/jxnr2+UZj+DfsEqtS3kQi1ZXW4UW0JmpgZ1cqubzTUaAcvmJq8HV9f3DN5qBIltZPW+RpNNPWNKLm52twCHqlL1ttTLmpmSqTtJGZRasaKsjXU5x8R/BLWysjjiX4fz4Pe9tti2YVZqI3ONC2OcyFamv8HPS71tDL3h0mssUF6B0yLXyqaFWIEMhKkNGKs76JhmE5f98dvv8IJPl/8n",
"part_3": "nLI/fv0v6RRKr81NZ6GLb85eqTsDCmi+7kxSqgo4oLTZ1yDA5uwFwtaJgFqd15BeqRGnVZet1MsHqL8qe7XayAqkVsBJq8H4nuEbWXeBk5SL9UjY4kZWUBMo9Ax5VQBTP6oxiN83ZoziS5uC1PUtwKTuMNYZsBqA64gzAjlz/v3ip8xhk9scGA5A4/6HBshdT/fw2jR1X4ddlA5SG2shcb3OocPYR1nl0iJMHfSPelQXqnzZAIK9TfJ2rQ71FOBg+n1TQaarstpAjxBsGNkaIr",
"part_4": "GFhVawLYQ0PEB/2Ie+hc2i7a45+7YohtaymUKHNIXZaefO/22VGwPOOvwKJWmw/KKqUgEFbDmgbWSFSmBlC67qsmgwiL4yUt+35NvMhyqCCvS1Lttq9sJdxG0JX33/pQqOaPLiTm7Add0ShVov036m00y7CfylKGrJlGlkhXbbHUERWQUPFFJSGoTB/yAQgoLneQF+pWn7KwINDp/2iz901al43qDiWVG3V3ndz4PbHKpE9AC0qffuy4bVAECxbFGChaoHGnsJZEt0iP+9Km9x",
"part_5": "rz0WulMA7VTKNJUtO5wRag7HS6VWUAqoOpwlS7WyihOonQEqzlgxhYOBwSdfsZw9f86K9jd+WnPfyaJWvVR9mb9BwcxJM2cknO/ZZv9k7sh+97HqzMDX7kbr7HXVqGFDFWDW9B7FjsfDIY6c6DtzicojT9Bt7B3OEmi9tZrkByKkHN8dzHGwj/uwzTPnAVxDBhQ9xfIvSuLifx7Hs/04HuKn4O2hwMHSWjpqiAA4OyFyT6awKmHlsoDh3a9RvldDvnoKNdmiGMUOP6BW8PMTjM",
"part_6": "zJ3fSC0Tf6sap3g6qYfkavuAqoyRx3FMw8VUmjJnLEZziQJtspYI8vMh/jS102sdNnOixfw5R+v6//7IA+7EoA8pJ/sTz9Nuy64+rsVb61faD4ZOF4/XuRMQWo2ro0bc1QBobvjPEZO+Ds60hgmSS164ganRqdwNPdtQzq48zflbnGH+0bjntbSxr8OPimU5hP9bbI8Z4LZ2Gu4Xc7zs433/PN93zzPd98zzff8833iTffvlrOxaXz9u1bexpk+nwLPt+Cz7fg8y34/+YWnGmY",
"part_7": "Ts6bmQPD38C0ci4/ZY653yrIFlKiYXnVjkFnBivEJ7vpZzjVaeLTYYBOUaS0Y5pkMDo8FjopQVKfZ+yvu/EyOkCsr4ceALZHmwyz7vzozpzuBOlOnf7YOZJUbwBPoMGA1+q5g4FHBeeiThD7SYIA+4EQnKP9II2DWCAaYeIGEUGSpIKHAuWEx/00RqBTH9ZCKkwaCS8KCH03CF3BCUvPc70o9Y6kdsg73/FOiSV87J2Td0Hebf6HvLvknXuPxyVpKYCq6DNof3d/4isEHOthRl",
"part_8": "iruNd7VCiiiyXFRD18i4aH6AlLYUVUCctin3ChyFPiTmqFCZnEWqRYCfOU2sULrDz5pLrapxdHvc209UdPjyR9fPfbdVzxQ8siopddJ6qlKXoM3JjWRa8bUIRpRJxKBvshj8nLyGOKkYQprocBp3cx7MakZXUFWRMWLJSMPN6jYSNJfaoO5dg+KX7L+IgiiUk+ppWYJksXz+A3HnmPCatWPkmG2Dh1EUcME8o6CSJ60ntI6xRDQnYsDgnFLyhaQYNPeNYv79GwdRGWAomVD4cV",
"part_9": "EX5tXBKzCCF6uB2zYk4598yyXcUHZkGz0VPYbiNmWWMDs7wRs7wA8fCoZ73Q7Znl0QTwEpJJUMsnZvk+p6dLzxGzaCYE3LKJ3t0Rs8hjQLqBjzYDyimg2ILE7ZkVUtahRys0UUNvxKwA7dgJE8b26fbMCmlC2elkmRXRjI4o2qhlFq1TplFIzAoFMYuQJQxjQskyKyY7MVU4pvhjshbbSlhmxXHPrDgRxCk+YhYfMSseMSsgZtEueU8EPgW3zOI9swRZED5aEAExi2onSEtQdU",
"part_10": "QSjZj1+CPn2IxM2jnp8icO2T0Dj4rO37k9uKe7Bvhdi9lucE9q2NpMOxenMexRhe1n9/V09l3qszQ4Wmra9YKnXG/cvXP7a3+nySywN7J+8lvU7PtpPLjWHn2OQcf5Ey+G3l4KRzzQ0/1bLo7ffbk9UZ6YRdpdkE/bcaPAPX7aprPnzUnDbXs32aXNyVt6z9XI/lGy/k1X8cEET9rNo/DbnnK/iOpfaMbDNnbK8fhWgrsSt//GpCvPl5N/g/83Vn3V6PxDo5wLUzXq859NcYmJziUAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIADv8N2gC/22SPU/DMBCG/0rlucOd46/r4okVhk4IIxYQIKG0Su0BVf3v9V1CkxRbOvvy3qce5aw+h0Pp39/yUPKX2qlzUt/9seRTUrvNS1I6pR4N1DvKndR2M6kgKswqsmt8F0JXnc4QAViWojeeuMYGNC7G6oVIYInzSEMXPXKvrmqWoxgdaWdYRDQWCbg6ao3aRb1aw/JQ29pM5owqz8HAF0n3VYDGE8YaObNKt1SJV+MJXGam7z8bM1859VDyAuHzw/4GUS8gTrosq+Feb3GEFUcpCbDkCMKRhCNI8xZHFI4wc3x8ai6FgK2U/9l3VHhXV83PVC5qq0759+ej/mJDqc/lCuf+GY16AgAA"
}
}
|
codegen__primeintellect___2326
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\n$k$ people want to split $n$ candies between them. Each candy should be given to exactly one of them or be thrown away.\n\nThe people are numbered from $1$ to $k$, and Arkady is the first of them. To split the candies, Arkady will choose an integer $x$ and then give the first $x$ candies to himself, the next $x$ candies to the second person, the next $x$ candies to the third person and so on in a cycle. The leftover (the remainder that is not divisible by $x$) will be thrown away.\n\nArkady can't choose $x$ greater than $M$ as it is considered greedy. Also, he can't choose such a small $x$ that some person will receive candies more than $D$ times, as it is considered a slow splitting.\n\nPlease find what is the maximum number of candies Arkady can receive by choosing some valid $x$.\n\n\n-----Input-----\n\nThe only line contains four integers $n$, $k$, $M$ and $D$ ($2 \\le n \\le 10^{18}$, $2 \\le k \\le n$, $1 \\le M \\le n$, $1 \\le D \\le \\min{(n, 1000)}$, $M \\cdot D \\cdot k \\ge n$) — the number of candies, the number of people, the maximum number of candies given to a person at once, the maximum number of times a person can receive candies.\n\n\n-----Output-----\n\nPrint a single integer — the maximum possible number of candies Arkady can give to himself.\n\nNote that it is always possible to choose some valid $x$.\n\n\n-----Examples-----\nInput\n20 4 5 2\n\nOutput\n8\n\nInput\n30 9 4 1\n\nOutput\n4\n\n\n\n-----Note-----\n\nIn the first example Arkady should choose $x = 4$. He will give $4$ candies to himself, $4$ candies to the second person, $4$ candies to the third person, then $4$ candies to the fourth person and then again $4$ candies to himself. No person is given candies more than $2$ times, and Arkady receives $8$ candies in total.\n\nNote that if Arkady chooses $x = 5$, he will receive only $5$ candies, and if he chooses $x = 3$, he will receive only $3 + 3 = 6$ candies as well as the second person, the third and the fourth persons will receive $3$ candies, and $2$ candies will be thrown away. He can't choose $x = 1$ nor $x = 2$ because in these cases he will receive candies more than $2$ times.\n\nIn the second example Arkady has to choose $x = 4$, because any smaller value leads to him receiving candies more than $1$ time.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5625
|
{
"part_1": "H4sIADv8N2gC/+1aa47TSBC+SsmKtAmY4HecQYOExErLD1ik5R9hoSfuJNbY3Vl3ezIRQtpD7AH2LHuUPclWddtJJuMMTHhIKyUCbFdV1+OrR9cPPjoZ00xx7Zw5r6u85C+E5kXBp9pxnVktpjqX4r1gJUcBJOUi49fOme8lY9eRVT7PBSveLytZLknFb7K44qAXHGayKOQqF3OYyoweKHNR8BJqRV8kgpR5",
"part_2": "xcqSvgsm5jWbI3GtF1KcTcRE9C57sORyWXBYMaFBS1DLItfQEz2YMpHlXMEF1yvOBSksh/Azmy4Maw1qIesiQz7M8ysSkMCv2VQXa5CCg5yZIyArEtGLSq4EsBVbD8n0G3LPmmYVB1GXF7ziGcwwUOj5PdKG7rmApuBZdcnQYK5s4HmldKt+CG9ap4nXOO22R1Z5UcB0IaVCOwJyxH7OK+hd94xiPCKM9zuK",
"part_3": "idfGjk4s8lLxYuYaCcGvbwkQXfGpRHVLXikp7hbVi7xqJY0PSiJc6BkwmK6nBceIUKzgMy2v0NU+Hap4yagwKjzONAEhpIYsv8pVjjmHizWZGthwO9Bu0EBXftItHOTbvOJMW60Cei8RFAW50Y/xqDwzKUEhnq2H8KxQ0gUL8laNqrEgGKiSoWnSaTxUsuRtkMapik854dyiUcqKN2af4xnsC0xal3VUjWVu",
"part_4": "U6yxkE08rwuOLYUJQ/xWDSKEU8mu87Ium3KiGmntbRHYuIKgmRioO4y/V6zIM4rB2JiIR/R7IZa1Nm9t2UqBFV7kWOLopsa8KOzFumqLS1H3uLZ4DaToI8XY7wUwmWCyhH343u8f/fQTSTWMy4ZPJN++v7xNem4fkwm29cc+Vpvved7A6CHpaYaV8bx9IZVzOj/45+9///zLVuY+OO4e2fal+xlEN03PNtWM",
"part_5": "XSmmBw+aJG+ld1PR6NzF/dda7wKPoxMHFBYDZgujb7DeBtWaW0plW+LOErAtv2luY/eV1LxpL1NPrMDuUVuFKN6W/MFi+fmalQidatw2tTMRgQcRxBCQmA1rIlL6aPihB2OU8Hf5kdXa6CXfNlC8EDvTiluLbXDNTN60OJxD1BvCL9x2oYm7F3UPuD16x1zrkNgdZ66dpx1S1B96sTv1jCSbY/cc8GcIr2R7",
"part_6": "IG+rrWN6BNvpsb0pmrrCVky3unOqVs2K/WzPNpVhUFMWtrhnZt2N4WU6vxf3to1DNlEBDcXdw+HBwyE8hBAlkq1fOPVWuBHQ88BdYkFuYLsJprpppBfuOUf4tIa6bgcqjb1rAb3D+1fIyr6jggs+ZbXiBsEFV3SCQt2P8I7sDHcKtwlwr3IXTO20WFO57sY0E2t7x2BPY+vVdEOyrC2YxgWzDN12wrdObPaO",
"part_7": "nNpug4bSWW5rci3rtoGWZtysaawrWdS0o5ntSGeSutNW0Ip4ze7QLl+kp+K6rmysuJrxIW51FZ/hbYbDEVc4TOqlCy9dnNLneI8o3S/Zso/2XOtZfzA0t11/MBhMBMMUn4M3ETNMSEYpqHCT432fzj8Ef4CbHODvAqe9kaMPLZf48ZL4lrBa5Ah1n+hPjejOSfqVOMvOoW85KDWAx49pYLX8KQKB/Awe4Tl4",
"part_8": "YOQfwOWTmxIPz4mxQ8TW6BPjKYhda1sXb4rzQvE9MRvWVszCgdO+j2+uYT+ADHEyGSPi4AnibQBErHWFEwa/m/ScFujTAn1aoE8L9GmBPi3QpwX6tECfFuj/ywLdKlHO2Vvnw4cPdgmbiNMy/Z2XacoU4u28cx3NlUb8nbcfJ45eL/nEOYOJY9L/vkms4yLFAG+Zm8mNagxP2vFsmKmhfnLhy/VtJn2Xvuj+",
"part_9": "+gIIwD+gzr+/ugj1eRTvuFNjfH+NtJvs/cAPY/BvEfGfbpTDIE6CKAr8NPST8DgfIAzJAv3txqqhHxkbHH49ZK75fZXVMIiC9AcbHIeRMXPYVvSVVm6Yw8c49LxoE+Xddo+LME1j6qPEgzTqbvXYO6Y5/QRrfYQtRW2VdipG3v0VjwJIEsDUd7dpcMRgCsYRzaUQut1Mj0B1DDSdwm816kIf96bggH/+URUX",
"part_10": "oT4cRf6BlH+jaXeAdnezfi/bdFsctntE3YTjIB6FqTdO/XESJ9hIX0A56MIt0ft7FI+SKPFGcRB6YRSEUZpCBymMfS/FW2UUROl4HOKfw07dlj2iGZJglKQRhjRKwtRPxymMAi8exePIC0fjYDQOE4jTxEP1eNFFHsLgjxC7OOmuzlui37Naf3zN3FWm3zHSz1p9R//FQb2vRf5HzZ0zXdX80395ayA6IyEAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIADv8N2gC/32STWoDMQyFryK8zkLWjyXlKnXopqUtlEmZzCxCyN3rhDLjdkINxvDsJ71P+JLexuM8vDxP4zy9p3261PQxfM3TqaY9PNUkBISgQFHrUNMOasq4WfBQu6uLLQpZcSlarLBnDwcjVNMQZAuy4ALqBTkiOwuSWrbWWctSQ61IQVNiZCEWd3ggsWZ0EjESj2jl+HeSjALUmHL+l4lJ2hGM7XnuQXsX8L34bS8ycbTs7Bieo/E2ho3SDedw8xznqZu6ri1W9s1olqst8OpaY8kPQx//T5/DNe3SaTp/vravMM7tuH4D9d/BmiICAAA="
}
}
|
codegen__primeintellect___2327
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA correct expression of the form a+b=c was written; a, b and c are non-negative integers without leading zeros. In this expression, the plus and equally signs were lost. The task is to restore the expression. In other words, one character '+' and one character '=' should be inserted into given sequence of digits so that: character'+' is placed on the left of character '=', characters '+' and '=' split the sequence into three non-empty subsequences consisting of digits (let's call the left part a, the middle part — b and the right part — c), all the three parts a, b and c do not contain leading zeros, it is true that a+b=c. \n\nIt is guaranteed that in given tests answer always exists.\n\n\n-----Input-----\n\nThe first line contains a non-empty string consisting of digits. The length of the string does not exceed 10^6.\n\n\n-----Output-----\n\nOutput the restored expression. If there are several solutions, you can print any of them.\n\nNote that the answer at first should contain two terms (divided with symbol '+'), and then the result of their addition, before which symbol'=' should be. \n\nDo not separate numbers and operation signs with spaces. Strictly follow the output format given in the examples.\n\nIf you remove symbol '+' and symbol '=' from answer string you should get a string, same as string from the input data.\n\n\n-----Examples-----\nInput\n12345168\n\nOutput\n123+45=168\n\nInput\n099\n\nOutput\n0+9=9\n\nInput\n199100\n\nOutput\n1+99=100\n\nInput\n123123123456456456579579579\n\nOutput\n123123123+456456456=579579579\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.625
| 0.625
|
{
"part_1": "H4sIADv8N2gC/+1a3W7byBV+lYGKwJIpOyTFH1G7DFCgvcjFbgvs3kWuQpEjmdgRqZBDy65hoA/RB+iz9FH6JP3OzFCiEsmJHGMvFiIkizPznZ85851zyCCPvSyRSc1lb9L7e5Wv+PtCciF4KnvD3qIpUpmXxaxIVhwATOVFxu97E8cO3WGvrPJlXiRitq7K1ZpU/FKKO87kLWeLUohykxdLlpYZ/QAzF3zFmppGBMHMskpWKxqLpFg2yRKTD/K2LCbTYlr8GaJVBVcYv19XvK7hCisXRn21",
"part_2": "Yok1j1O2SWq2qXIpefEDS4ZszpIiYylLKs6Ksrgq+DKROdzKsbUlr4DOYaORTPBEufZPXpX1NXtfQHVed6wNtZ+iqZVO/qlJhHhgdb4soIXDgChrec1+BQpR/I1BWpYM0rKsdBx2ypSBEnMV25RVVg9ZWXCW3iZVkkpMXlgXyspns/EFq+GtyNictlDzSvKM9lKyJXZVsBpu8SLlFJoMByJrVpewncgJYztNpB7urUWScjKivBN8IUluz96wI1Vv3VKOrEUuleDWqHJE3lZcB5uDBwhQM28B",
"part_3": "NQ6xqPNaUqB3HvYFlxdYQzx3jqyTStIJ0sQqzzLB1dR///O/f/3bHCstgXW3srOSDuBxq0i7Qot1lwxZCfck+SKTvNg/eUhjV3R0VcNV4DSzrhmx8L1aAjmrBPzhmQZAh46+xFkTO2rQAU5skgciEPZbX5P0tLii632xbqS6oymiyyKvajAwp8PWTkFLN4Sy0snzZfA03wQvlvK2zQcDz0oEnDbK71Py1bH/EXT9+Fsju47ooQ6q5my2T1ilHEymXKr5Ha8SAXKJhqoC4vZQNjjCApkMGiAI",
"part_4": "D8adlbL5cylNOMlAGyJptm5I3Z6I3IBGvFqBGll+l2fwhNKU1Q+reSmIhThlw4Ci9bgR0ljMoTnLcqmSds4XlH6b2zxtFeylkT7Yv2hK1BxkSeBp0azmRHiVg2tslZS1ua5cWSN1EP1fEOtUog7oGqecKXUkqSxhh5oaeWEqQLJaC675gIhS0Cq+KlGRdptTVtshfF2gorYhM2dLcmYLS45om/khq1GdGYqgwSlRMpwT6RjV9y4F/mrcMSRQzJwWjjvyfCcY71ih5izPj82sAdpR1MXYVhRH",
"part_5": "nWUnihzb3tNiRVFs5nbG9MfzA/3xw0h/PrOvP9YWF+8Bf91ucpMj/eeUBkhrFctOtDQ7MVFtuUtVGtiSzGiqbmjN9K62VZGeisum0geJRsav0QMrvkBOoLah4WV8wVZltqzKZt3/icXIuMvLyAqHcOyuwNgeMGpmkt/ztL+4uLhIRVLXJPP405NeAhLADz+j8N+wS/ZIkk9qYWEG7F3MXDYhnR+cG7JCyyAby4llqExL3neHBj0wyJyQ/T7sXOH79m0+uKRp3L/JbwZv8EtaaAezWV7kcjbr",
"part_6": "11wshqz1m9HwmkYFe8MMfjar+LqazTArktU8SxSKwLLqa4EBs9gF6b/QAgj/IbzCagT/1AUkwznWE7Ics3mLQX5/CZrNVDzhOsEtQg80HD3oa/CrDnzViK/BLzvwdbl5Do5lEhmSxJAiNzBy1GJQ375uijQY4Sv3aU/HQpR4fvgWJdvxNR081N0oFWCh+jXc5neJADU1JWmFKNFmSt/wt4YtlWt9JSrINC/6tRpBFONtHqg5lFNiNSb79oB43ReWM2B/ojqrqQla9OsPE3CR/QjYO2XmNseD",
"part_7": "gJFz9uTUkpakJMt3QioRhveUChzaqXTzPtqTY3xXzmhJdXPlkF5lwSau0h05c68jbLzQAuZ2T6RNGwxn6S1Pf+sLPGqIOb7p1iROZJgaiyK5GZobS8y795ZIbzQ+ZVcgO4xoi9v5Oc0nu/m5mTeHlxDpKU/SNhIi3dUE8fbtyJqXpeiLNyM0UIxdaxcWBZ8TvC9S8v7Kwd8rkV667W8HjVNP6NiRN7CBP/N2HoUKSz8yh2mF7V2q7iaqyedFw/fx7wigBdTtQRy16CNx/gLehhykUhGvEeNJ",
"part_8": "G/JaB3zyWdinUrUH8P8xebIe50/xY4ok+MEU/mmxSwSUfvUAjLIvKzyzYGw6xfnN5/zmc37zOb/5nN98zm8+f+Q3n20C9CYfeh8/ftQtSz8wnt+Czm9B57eg81vQ+S3oj/0WNC1Q+Hs3w556/sObz4fHaU8+rPm0N2HTnupDM9NhekPMqHzRi9teC6tqTT88bBfbpkvLlO3frJh68yGdukmfrM708oNetk39dKXP9P4j8XjmIeB08457ZENO7L5Ane0cUWfHzosifuBCnA9cR8/lwBU/o+I0",
"part_9": "hjnOEYY5L9pveCQJrDB+Af/9IAwPH69vBWEcvuCAXW8MqnpONAqiI2dNEEth4h3oJCMRzsIJgnAcjF3cO/bIO5wMLdAiZLwHPW1XqBSjUTSKfDtCyMaRPY6gEjnp+5HrjMy6N8a+XXfsjUf24bgeUmR1NcVHVZ3GuyN8t5FnL6Dx2PFC33XDMIioyHlhOLKDceCMvCBy3cj1XNfx/dDH2IfrtuuPsT3bCe3ROHA9zx+PQtvD0jcLjv3RKAzCUWBD3j+8mc+8sl7sVvx9fp1aAekiYqrfI/XQ",
"part_10": "RoHVsLiLO7F2211TRywpkLWz5LxoT7YypA0e25Gt7cQd1IlmaCfqq70+Ysi2lR1g4g7u9FPSgXv2hEzU7O8ImvP88bRhc77jfKJx5Lhk53CRRAly3Hi7/god+JWvw934la9Tng9e+Yp/vw2expsosin4hx86osjCcrxdPzWXUbhRZb0w8EBPtDtUZRfF1XfQH8e2N/Kd3xnk2rbve57nRr4bheNRgDZsB14Q+hAeh4E9Dm33m0DHCtMrOWq9nqr4lTf9dEP/3a+eNUX+qeG9Cf2bzdP/AatrPYEvKAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIADv8N2gC/72U3UpDMQzHX2X0trtI03wO+iQe8UZRQTbZzrkYY+9utoOb6EGGbJaU8m+TkqQ/ukvP69WwfHzo10P/khZp16XX5fvQb7q0mN11qQCgKmIhFTIvVlyhYq3KpXo1oMrln50QgJmI0BldrUp1AiFRjmBTAVPAi5y6btml+SzK9KkR2UyMc1CIQ8Yxj1bOJ1iJi9hpA8lii4pXcTj7WdTJGBWLRwYhtIKYlEriiI4UnWBWDs1OBsjmqlCiJyZIxFYVKI4uDjSOXopWgYhn+JrxaMQyGquPdvJhiac5qvuDXA39TUDJ17uq3QKVPMlKuwSWPNLSfuKSidt3YPKRmPYrMvnPzLQrQpNP1LQJbLJo+wRnn+Zp02/fnuKvWQ+x7D8A/Mu0kYMEAAA="
}
}
|
codegen__primeintellect___2329
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given a set of n elements indexed from 1 to n. The weight of i-th element is w_{i}. The weight of some subset of a given set is denoted as $W(S) =|S|\\cdot \\sum_{i \\in S} w_{i}$. The weight of some partition R of a given set into k subsets is $W(R) = \\sum_{S \\in R} W(S)$ (recall that a partition of a given set is a set of its subsets such that every element of the given set belongs to exactly one subset in partition).\n\nCalculate the sum of weights of all partitions of a given set into exactly k non-empty subsets, and print it modulo 10^9 + 7. Two partitions are considered different iff there exist two elements x and y such that they belong to the same set in one of the partitions, and to different sets in another partition.\n\n\n-----Input-----\n\nThe first line contains two integers n and k (1 ≤ k ≤ n ≤ 2·10^5) — the number of elements and the number of subsets in each partition, respectively.\n\nThe second line contains n integers w_{i} (1 ≤ w_{i} ≤ 10^9)— weights of elements of the set.\n\n\n-----Output-----\n\nPrint one integer — the sum of weights of all partitions of a given set into k non-empty subsets, taken modulo 10^9 + 7.\n\n\n-----Examples-----\nInput\n4 2\n2 3 2 3\n\nOutput\n160\n\nInput\n5 2\n1 2 3 4 5\n\nOutput\n645\n\n\n\n-----Note-----\n\nPossible partitions in the first sample: {{1, 2, 3}, {4}}, W(R) = 3·(w_1 + w_2 + w_3) + 1·w_4 = 24; {{1, 2, 4}, {3}}, W(R) = 26; {{1, 3, 4}, {2}}, W(R) = 24; {{1, 2}, {3, 4}}, W(R) = 2·(w_1 + w_2) + 2·(w_3 + w_4) = 20; {{1, 3}, {2, 4}}, W(R) = 20; {{1, 4}, {2, 3}}, W(R) = 20; {{1}, {2, 3, 4}}, W(R) = 26; \n\nPossible partitions in the second sample: {{1, 2, 3, 4}, {5}}, W(R) = 45; {{1, 2, 3, 5}, {4}}, W(R) = 48; {{1, 2, 4, 5}, {3}}, W(R) = 51; {{1, 3, 4, 5}, {2}}, W(R) = 54; {{2, 3, 4, 5}, {1}}, W(R) = 57; {{1, 2, 3}, {4, 5}}, W(R) = 36; {{1, 2, 4}, {3, 5}}, W(R) = 37; {{1, 2, 5}, {3, 4}}, W(R) = 38; {{1, 3, 4}, {2, 5}}, W(R) = 38; {{1, 3, 5}, {2, 4}}, W(R) = 39; {{1, 4, 5}, {2, 3}}, W(R) = 40; {{2, 3, 4}, {1, 5}}, W(R) = 39; {{2, 3, 5}, {1, 4}}, W(R) = 40; {{2, 4, 5}, {1, 3}}, W(R) = 41; {{3, 4, 5}, {1, 2}}, W(R) = 42.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5
|
{
"part_1": "H4sIAET8N2gC/+1azY7byBF+lYJgx9JYM8smu/kzhnPJJsAeZr3wBDACS5E5UktDiyIVkrI0mB0g19zzCHkH3/0o+yT5qkmKHA0niXUMJGM5ZHd1fVVfVVdXA3vfm4VFmOuid9n7JYtW+qek0HGsp0Vv2JtvkmkRpckkCVcaAhiKkpne9S6FsNxhL82iRZSE8WSdpas1q7hO4y+ailtN8zSO022ULGiazvgPZG5ivaJNzl8sgpFFFq5W/B2HyWITLjB4V9ymyeUoGSV/STcU",
"part_2": "ZpoW0RedUEiwktI5JaShRydFTsYaPaM58ElQkVJyQX+G6q2OFrdGOjovbusFFOW0ndxHD4dCebrSlG9uKoSwguRPLJnpJC2AEub04kP/ekBvf73+dTSaztKCRqN8s4JKvEQJXT+U+l90AqzDrIiYT3r/BCWB7cvKhJxBgfQeSDXAdQnw/oHYghfUz/Q0jGPwGBbQ1Kh+av6euAiaa4R8M70tF+svOrvbMwQxDk2j4EbHabLImVu9C6dFfEdpsicLJu2hBxcctD+E8XQTh0WZ",
"part_3": "BbCdVZZE5MY4GL1fknfyUOMsKUmTc43MuqvtHlKYzJA4EQezoFU628QpCeuvAb0mD6xv07Z2zp4pXqKZzhDAWTSf44XXzo2fmNa7KC+owLp9Vu0MyF2LI4jeVUwwEcazkFOmpIAJqYhrwEtTId2glrFFKiOfAN4IG+ZGyTn/fkrWm8K88RCn0TzKYGIcJcaZIozgGRsMEvRCZzklBmpJfUG//eNfeOFnYp72t69gRw3ot7//0xiYbFY3gIa5e3+NnY+m9nmIvRaChL2hQ8p0",
"part_4": "vkZ1QMTiu4vawlzDsNmBiUljoNkUtXnlB79x3AZsWCs/9lZVhMKONjvvNkWbnl9MJjD/Fdbez6MyrzPjinAJmcNUa9n0x124Wsc6r6wyARwlkuxRYpND+I9FS8tHiXAt/qykFEsJliFJqi3nSlViVCg/owY1fqd5HqGcth1CsIp9tuTGpEui+3sxJHtIzsOQ7uUDnlVhcb597W8nAs5sJ7Z5OgP8Ed++bicS87Z806yWvNpprbbdetapZu32bLPWLGSR1mwbmTHLAccMSCNh",
"part_5": "7bUb1Qfr97OymnU6Zuupg7Ww+78QWCXzUwYrPNVSJ9WbRwLqkGXpt1msBNrmKtEmshJoc6lKLu1HAqIt4L05DDNLtSLtPonkgUBbg+qImOM/ifaBhraA6oiZE+xj1gi0eZBW203j4wFE0BJQlYDs1CAbgUcQJdXOI4E21dLeV7SItydtI9SMG6REMYvKInuHniS/TTdxfQphIMPxHm/M6YsaAtmU9y//+znd8lzVEtUdEOvJdLHJynxDf6Qv0Fpl2hwTU+60UGiXMCjG2dRf",
"part_6": "hes+kIalTf3BRb6OI/wdDBji6t2PEBTW2Vnw2itRZ3pO8zAvJivuvL70N+tJkQ7paoCuivB79eoV/QnzZU0LMyhGD5BrUxPFxYWRh1xV8q4ueEW5tNQIwI/nAi1eRhPeNRmaN13CcAUZjNvCH8WYDSyHeMmuWYJYNasq61ord7yyf96/+uGH3YDO6uGrl7vx4OVVKV4RWU6x96twl/BGP2NOFGtGvd3b3eaFJUHLux9B5Bwtx5D4WfknxkN+YAYmR43JSBleV1vLKy7C9Von",
"part_7": "sz6/g5fxWUQvK7W1CJS2pdgLFqwcisb7BXX8rosow3G66HMmtALHuVnPtQ/ssmYt0RBTvxnGaVYeZk2VG7SiGc2RZb+npMV8RadVk5tv4gJ0WE34PjdcLF8/ilol/ZpjJlh5f3n+efA7gTM91wgwImgoWo6rN/b9c/tjSedkBtbptv95SFV4SnaeAL182wxXQ2dvG13jRwlSrymXjJIP8Ao9wn/YXbWs2ef9/uOIIK/6Caw1XjVTPMLTgzP6UMUUO9uoxK4uMjRG+K4Kwem+",
"part_8": "dLovne5Lp/vS6b50ui+d7kun+9LpvvRd96VaSd67/Nj79OlT2QmNktPd6XR3Ot2d/i/uTgyGnd0bD3uFzgvs9N7H+1GvuFvrUe+SRj1TaCZVCekNMWJMKSe5o2haCugyAmnZLxgJ7i14nGvb/6xWGbVND9KlmJuR71YssNOhuNvSo9VZ9a9b7+Pp7wKwDYBrSZt83+8mwg58JY9RzRz7ti3JF47/TPAc1/5+1Y6x2pYWoqc8B6e9163fEcFx+k16+L6FU9720LCobv1KOrY6",
"part_9": "Rj/nsrRcw7qPfsd+Jrl9x3O+X78s08Z3YbrrwQlPoisT3eFVVmDJYzBs44MMyLZti1wpPQQieCaHXFt57jEo7L6jbJeERKQDKVyyA09206VcZYljUFhfEFhwQzkK8fADEr7qDorteJ53TM0xW82TFglHQb/rOuRbCI1yfbfbH+G54ujy5gjhkCtskoC0oYncwOsuISrwlO0fA8QUBb7vkSeQzY60AvIDhzOh2nhPt7wIvMA5BssEyXElJxweCBAFyDwPQX9m99u+ZR+DxEks",
"part_10": "lDRJ5xFqCHlWoNiz7sSzLUscsYdckxIOCjj0S598x7Uo8KUiz7YDUo7TfZLYUknPPwbPnKbK88l1LEG+Cx5dCxz6SvDmeiYPkUDCcexjAE2h85DuCj9C8gPVQt22sVFhhOwuF55E7I452F2TJL4Ee16A1HcF++r7cE4EDtXV4amDAc7Ao/DYAS+wXMTNM1WQ9xwShhNHuqqbUE9YSM1j4Fif5/gS/tjwhyuvjxKM3YeKooT73EZwq7I45v8BKJ9skuhvG927LLKNfvg3w0lByUEkAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAET8N2gC/02RzWoDMQyEX2XwuQf9W86r1KGXlrZQkpLsHkrIu9ebwO764gF9npHkW/m8nOfT+9t0maevcii3Xr5Pv/N07eWA114E0vspRQzJmkP38oJeDDw0Z1R4VIJWgyX7DtCh1SXAVhXNOCCt2krEw1q8JkKJkTFCgoSQzsuDjJXVh5tRCHIcuImuRX72sjNetDIRKlkiNQgtzVFFGlx1zy4hVdPQWBQuS741VI4Gdn72cFzY8zztNsOhIauPU6NtNPZw2kLMiFU3mFPrrv1VibnVbcfKEs/i8V5eynX6+/kYX3SZx3X/B1jrFXW6AQAA"
}
}
|
codegen__primeintellect___2348
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are a rebel leader and you are planning to start a revolution in your country. But the evil Government found out about your plans and set your punishment in the form of correctional labor.\n\nYou must paint a fence which consists of $10^{100}$ planks in two colors in the following way (suppose planks are numbered from left to right from $0$): if the index of the plank is divisible by $r$ (such planks have indices $0$, $r$, $2r$ and so on) then you must paint it red; if the index of the plank is divisible by $b$ (such planks have indices $0$, $b$, $2b$ and so on) then you must paint it blue; if the index is divisible both by $r$ and $b$ you can choose the color to paint the plank; otherwise, you don't need to paint the plank at all (and it is forbidden to spent paint on it). \n\nFurthermore, the Government added one additional restriction to make your punishment worse. Let's list all painted planks of the fence in ascending order: if there are $k$ consecutive planks with the same color in this list, then the Government will state that you failed the labor and execute you immediately. If you don't paint the fence according to the four aforementioned conditions, you will also be executed.\n\nThe question is: will you be able to accomplish the labor (the time is not important) or the execution is unavoidable and you need to escape at all costs.\n\n\n-----Input-----\n\nThe first line contains single integer $T$ ($1 \\le T \\le 1000$) — the number of test cases.\n\nThe next $T$ lines contain descriptions of test cases — one per line. Each test case contains three integers $r$, $b$, $k$ ($1 \\le r, b \\le 10^9$, $2 \\le k \\le 10^9$) — the corresponding coefficients.\n\n\n-----Output-----\n\nPrint $T$ words — one per line. For each test case print REBEL (case insensitive) if the execution is unavoidable or OBEY (case insensitive) otherwise.\n\n\n-----Example-----\nInput\n4\n1 1 2\n2 10 4\n5 2 3\n3 2 2\n\nOutput\nOBEY\nREBEL\nOBEY\nOBEY\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIAET8N2gC/+1a7Y7bxhV9lQGrwlJCb/glUdzW/WFgXRgIkqL1nyBM1iNxtBosOcNwhqtdGAb6EH3CPknPnSG12vW6SQwtigKSYYmcmXvP/Tj3zjXgD0HFLTfCBufB3zrZiLfKiroWaxuEwaZXayu1ulS8ETiAJakqcRucx3EchYHu5JVUvL5sO920pOIfur4RzG4F2+i61juprthaV/SDM6taNKw39EZHsHLV8aah95qrq55fYfHObrU6L",
"part_2": "1WpftA9451gnHViJWpWC16JjnFVsbthq4Wccvo0M5Z31h2+0XVPdjOp6GQHE3plu7sz9rq3DlrcyJr9Vd+ITjVCWVjbQ6vGLl/Rt5Mi5cbBIT7DUq+k2ToR6PZ+dg3TG0B0nXDR4rAUWrqz0YemN5a1XCqybiPUWrDdVq63kFFGGmtIfhJHP3+Io+jjxOFeGwew0zhU687cw41h3fE7NjV922ojRhEKieqblehExTZICmK2sRQcZGpr/dIkms",
"part_3": "zOGWNy4zS6jJIFLiWkh0nDKnkjjUTC2OqOTboJQcHiAWfLb5ygXAtD+kI6gq8EB128NNNqRhpdAg4jIC0SVP3pd8Gvfh1+5eBXvwV+VffiMf5DSG23o9ukjvBJzZortt5qijdJusRQbL3mvf3QDQWi20kjQidYafXCMiWQlE+PMw5a1DWbEhTMgyng1EpWFawnWrfENi9ElLazM0bMetN3hNLoDiik7YDOHMKgsxL0JAdSdsLYTjqKkt6GX4t",
"part_4": "PSL0D1cQZ+1bYF4bV4KYzzYFD4RD+IVmeyeAlN2uhXI3rDgV6PoSWKhd/J9cTR3SxRk3e7Km6kwgyqTHoLUMsHcelBw59+h45tpMwB4VuKQXcFSXbcFlTZHHS1Z3LmbglPOcgk00jKgmZGh3g7eYgJfep8M7wNcq4GvqJLzfEhyMfguAROQDBGR9T47PrbOI1SLcSI27liv8dNPzSI+yuF5lzf5RkcJIT1QBDmE0Ll7cHLkzp0aIdEx2UBiua",
"part_5": "VneWKztjRLrtiOQ1s17xGy0rp3PsjyPfhFnzVow0W2s0HGddqV7S561qe+ueRpM3skPia6koL8oiRoZR064p21ZcoQdP3qEkJzErSyy+8z9oXugs7N///Jezz/chRxZEAMVjhNlHRYlb65QQihlhWAVbO9m64D6UdGqJ0C10ktAZu+DoCPsT96babSf2lpqhM7n+cH1gdBey1Wj3z4XrHv71+mD13hvX3k2rPc/XWmw2ci3BiQex/L63h8HEh",
"part_6": "aq8m6ir6ikf3iCZ4qEfrRP6+8Xri2/Z1K3AKYGLgqpnNratz2YfCr9/ffHDU6L7rnRo8sUtB/vEYLMjQ6myUsUsZkmpEgSC4XXOEpaWKsVPQrLeU/wCq1TO2vHFf/s8S9LnaQ/KG1tRuxj4aba6r6vBX9eIzHhvu9u80gRAf77TO9obJotxkCA9nbB9p4YMVeIME0onNmg9qGaMI+6+Q2+p/c1shjICzza8r2HN2oaVQImWatgxdybcCt7+Eq",
"part_7": "4QKGw33G5DaUVnta5NSC1UXYUQ6UW41u1dSFVaKsidYUrACNB3BlC1bKSdxtFXXy1nCOt3b9grtqk1t9MXUm1eYK3RFdboRPF1XirRmuH1Jd5gIMVuiot6cBFBmjoQiuFZh1GIGDSdzfaH64PT1EGnDW+nEAvZU3JnBj3HQv5AwSW8e6zkv8r69JD41bqa8nA1o8HNYrqha9Q9lxbL8GwVMv7HFa0M2rnjCHacn6VCk2WXdAV0GAXF9B2pwpT",
"part_8": "CIB5e+2M1nRvWsILB0WGGuMtu3ROppH2F3dEiv/IH5o1S7M/OML/mz379ioy5X1mDj1iL/Rq9vWIvp1P1cjX75hs+OM38BEW7f3nFrgeV9HGEnpaBL4pgMEDURjxxyBVLMANvXUzBWduhi+F9oPlpqD4N1aeh+jRUn4bq01B9GqpPQ/X/ZqgelZjg/Mfg/fv3fqAgNacR+zRi/1+M2KQRzA1+CgPqC2By8OOHMrB3rSiDc1YGLgWXQ4kEIVZc",
"part_9": "ofnNrByrd1++Y/2OBQwAJ6V9FTsxhz2W8lDF+58y+Biy327C3JsQjR9WDJ/l5zaKxxv3j7Tz1Lrz4+mdB8Kfujr6+LSvX+ZyDJG9M4+t/Gy0vxwkKcbYpflnMEb3vgDkqQyxNHoWV/J4wFgWz+ZIuk9J9gwg6XKR5ckyY3meFHkU5aiy+NggSZoV82KZpCxbIP1xEheuoo8K8gmB4+NH655Q40P+TCDei2dwIc4iKE9TlF48T7IkOnZl5EleZ",
"part_10": "EmGkiuyKMtYnKeLpJgfGSVbRnmUL9lyWSySOQpjmS1S16OPibKMsmRZpCgPqC/SaLnM2WIZL4okz4+NVczTJFoUbL5I4xhxW6ZpksbHbsHLeZKn+Xy+RPazNM3SHEhxHmfxInuebv/wSvmV6+3L0Z5s+8+GlhWLxSLPQEBq/vMoRm9exBkCGx07jHHCqCk/kyP3F/H95XzUnuMnt3wY6bzy3w/6+BdG/ET/T8Jc9kri3zDBue168fE/uEN/ZWghAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAET8N2gC/31RzWrDMAx+FaFzD7akxFaPhdwGhd3GXHZZaQcjHal9KKXvPgenpgmlusj6fiTLvuJhOKX++ysOKR5xjdeAP/1fiueAa/gMaEPorRgFy8wObENCxmQw4AoKrVOANSUsUBXI6IeCUFbACDRAwDlzzjTr5cipkAAbFSMC1nFL2sw00xiuA0UXXcp9nIVy8EtevHHGefBeW2oy66Vl9c+m5ACtG3LZfDeKTik+vNN2031U/3u36d5qNVF3cCpnhhfup70Wxe6GKzzHy+8+/+CQcrr9A9Zi7pDZAQAA"
}
}
|
codegen__primeintellect___2350
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nArthur and Alexander are number busters. Today they've got a competition. \n\nArthur took a group of four integers a, b, w, x (0 ≤ b < w, 0 < x < w) and Alexander took integer с. Arthur and Alexander use distinct approaches to number bustings. Alexander is just a regular guy. Each second, he subtracts one from his number. In other words, he performs the assignment: c = c - 1. Arthur is a sophisticated guy. Each second Arthur performs a complex operation, described as follows: if b ≥ x, perform the assignment b = b - x, if b < x, then perform two consecutive assignments a = a - 1; b = w - (x - b).\n\nYou've got numbers a, b, w, x, c. Determine when Alexander gets ahead of Arthur if both guys start performing the operations at the same time. Assume that Alexander got ahead of Arthur if c ≤ a.\n\n\n-----Input-----\n\nThe first line contains integers a, b, w, x, c (1 ≤ a ≤ 2·10^9, 1 ≤ w ≤ 1000, 0 ≤ b < w, 0 < x < w, 1 ≤ c ≤ 2·10^9).\n\n\n-----Output-----\n\nPrint a single integer — the minimum time in seconds Alexander needs to get ahead of Arthur. You can prove that the described situation always occurs within the problem's limits.\n\n\n-----Examples-----\nInput\n4 2 3 1 6\n\nOutput\n2\n\nInput\n4 2 3 1 7\n\nOutput\n4\n\nInput\n1 2 3 2 6\n\nOutput\n13\n\nInput\n1 1 2 1 1\n\nOutput\n0\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAEb8N2gC/+1ZzY7bNhB+lYkusVvZ0Y9l2e4qQJqmQC5tgQYFivV2Q0m0zUamXJGKZQQB2mPufYAe2mfoPW/QV8iTdEhJlnZXgROlt1obyyY5/Gbmmx8SyCsjJpIIKo2F8V3GtvQplzRJaCQN01jlPJIs5decbCkK4BTjMS2MhW07tmmkGVszTpLrXZZudwri+zR5SUFuKKzSJE",
"part_2": "n3jK8hSmP1hTJhQreQCzVSIjizzsh2q8YJ4eucrHHyIDcpXyz5kj/K5CbPgPAYHiW0wG+Ko4wCz7ch/gxzIWkmxvAsjclBQR7uo/Z1KoGg1u2OSqbMH0MLTabpC1xeZ2m+g3SFduIkQ6fXCAXEhNCEvQkFDCx49+ZPCOFCjS38KtTP4S17NF61H/75bQydVueCQsyEZEgokB16TqIN",
"part_3": "Fbi77QwSgd40u5iAn3Eazc3oOk9IBuv8MIYnuBcEjVIem4A8ijyUGYmkgJQj8RgL2ODWEngMTzmkyE0G+zSLhd6xo9kqzbZCh4EIwdZ8S7lcQAQBfkZgH/1AIAIi3W2U9RGRNL5jRC16RC3ZRzcgxTmiYmBCTEWUsRD3E1Flh1gAWyHD7978BYVZ779lFK4H+BkpCS19oX6hDG827F",
"part_4": "PUyNGaXLKX7c3KlgA/6NEXb/9QSHv8PSjwFQ7HKi1+TPM6aUrC2klgQjSGryhmGSYphb1S2oRnTRX+hpJYJVLNF5qIdCuSBAhJMlmbWaf9kRPcLPWMwPICicWHrAuRq8EGl1qaVErfVRTpDCXajyUfqecp3+VS/1JTz1QhsgxTKFH2I0eSMNTbke/oKgzsElC/nbd/29ZPcxPKyb1+",
"part_5": "25ZlqWLoqoxaMmpvH7aN+zaXbeuw33CV3KohJPRYRO9+/V2zgoSxbb7VxOBilWyiRQunNNY1hJG4zc8YMLIQEa7azMuKUQXb5KFgMteBAJLsCYYrjaIcSdkzuUF9VYtSTeu+QAK3TIq2N08KopJcVP5o5pd8Ag64yMRUyZUOL7mjBrcE/LbApCVgawHnJoLt3pBQMvhuS1h1wJkSQi",
"part_6": "eSBELMLYndV3ejA/IhNmmexOiWYv6gWp9Ik1xzgDSibKqg1N836V6tVd28bt4KJ6Myz0p6sLXTMZ4KGV3RjPJIHRLEDM29WZhRkGDLGGzJboDKTG3VYDgWu4Th93C45ISLAK0OwyDEN+V0xaSa+IFhZGgcXH5NEkGvPsOkQ+8fH6KEPk6FDEbo937DEjqwh3hQAD5sNYguAlIP1RNm",
"part_7": "lLw4rlaYl+HVvUDDtkUbaDRp1Ihe2le3hL6srKysbctad2XxcMTUVt51GNVsDQYVnInqh0eTw4vihj/BfjQoRuGwmULxzwO7HNNEbXkY3NwzCopucb1aaj3OKYDKvyAadZG55CjTsIWRqIV0Rg1K+ynSW01Ho5qqchyz1Uphl6OiCNTEgwdtbo+2FMW9wGobURSjtvnanaL47GhPs6",
"part_8": "RQR8e1G8BhcCM45WSZTWrXwxsa70bhPZHoordFQ3c8ujY11tu3icU608WDNYbHPeM4rsryfPE6X7zOF6/zxet88fq/XbxqEGEsLo3nz5+XTRyvVudL2PkSdr6E/feXsEZIBQIrzrgyDUmFxAo0Ll8tDXnY0aWxgKWhG8B1VdqGiTO6/MrFplshjl5My3aiVx09+9qEjwf0OwEnHw/Y",
"part_9": "dMMuQGyLPRDr7tmFaPUBtPTBCPP5HByrfroNntdPLfFxqiwVLECWu+HdfpguYnrgvsdk2+8J6qGx7wF1vH6YmAy2A76jCe8215n5vZLCQlAHU80Hx3W6k8OZ+z1qokkJsL15mSoz3zqVKtYnaAJ/PikVYfROKXIsd+ZZnjWf9tcIzqwqAsf7AH2WP507rt0jTsf6gYlfKvSckx66PR",
"part_10": "WBO5lWNE7sk265zsyZehNn2iv9JmVOw9R3T2ma2vbUsTDEsz6aZp6tO5XvnHTJtzFPPcv1ejVuz5qgohnMLesDUgL9nmBS9DsiPNV8ffBO5x5S5/sYKLf/UXRChVdnqNfvKNFnk2pBrtPtwmSKOeb0AVdhL9P5dECs8p/9SXqcD9AzsayZZVdkXan/3BPXOWe/5NRYyCynr/8FQQBAoh0cAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/3WRwQ7CIAyGX6Xp2UMLYx17FTFeNGpiNrPBwSx7d5k4Ns1sSID24++fMuCla0NzOvou+CvWODi8NY/ge4c17B0yWGuBiQgYFM3hXONwB7FOoBVoViDqjeXKAgObj0QltCkClOpTrz9NwEQDev2mMsmcqG1nwEWyBKXoTcLOAYUk0ij5JQ8T2ga/Gkok0uJFS1WSL1stvkZj8lE4zsSQNkVOlcylIrFFlVM6ORlxh71/3s/xo7oQt/EFpqS9ScABAAA="
}
}
|
codegen__primeintellect___2360
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVanya smashes potato in a vertical food processor. At each moment of time the height of the potato in the processor doesn't exceed h and the processor smashes k centimeters of potato each second. If there are less than k centimeters remaining, than during this second processor smashes all the remaining potato.\n\nVanya has n pieces of potato, the height of the i-th piece is equal to a_{i}. He puts them in the food processor one by one starting from the piece number 1 and finishing with piece number n. Formally, each second the following happens:\n\n If there is at least one piece of potato remaining, Vanya puts them in the processor one by one, until there is not enough space for the next piece. Processor smashes k centimeters of potato (or just everything that is inside). \n\nProvided the information about the parameter of the food processor and the size of each potato in a row, compute how long will it take for all the potato to become smashed.\n\n\n-----Input-----\n\nThe first line of the input contains integers n, h and k (1 ≤ n ≤ 100 000, 1 ≤ k ≤ h ≤ 10^9) — the number of pieces of potato, the height of the food processor and the amount of potato being smashed each second, respectively.\n\nThe second line contains n integers a_{i} (1 ≤ a_{i} ≤ h) — the heights of the pieces.\n\n\n-----Output-----\n\nPrint a single integer — the number of seconds required to smash all the potatoes following the process described in the problem statement.\n\n\n-----Examples-----\nInput\n5 6 3\n5 4 3 2 1\n\nOutput\n5\n\nInput\n5 6 3\n5 5 5 5 5\n\nOutput\n10\n\nInput\n5 6 3\n1 2 1 1 1\n\nOutput\n2\n\n\n\n-----Note-----\n\nConsider the first sample. First Vanya puts the piece of potato of height 5 into processor. At the end of the second there is only amount of height 2 remaining inside. Now Vanya puts the piece of potato of height 4. At the end of the second there is amount of height 3 remaining. Vanya puts the piece of height 3 inside and again there are only 3 centimeters remaining at the end of this second. Vanya finally puts the pieces of height 2 and 1 inside. At the end of the second the height of potato in the processor is equal to 3. During this second processor finally smashes all the remaining potato and the process finishes. \n\nIn the second sample, Vanya puts the piece of height 5 inside and waits for 2 seconds while it is completely smashed. Then he repeats the same process for 4 other pieces. The total time is equal to 2·5 = 10 seconds.\n\nIn the third sample, Vanya simply puts all the potato inside the processor and waits 2 seconds.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.4375
|
{
"part_1": "H4sIAEb8N2gC/+1ayW4bRxD9lcJcQsUUPftCQAGCLIgBwTEQIxfRkVtkk5xo2D2e6ZHEGAJyzT0fkEP+IXd/ir8kVd0znCFFWTsSwKRksdeqV6+W7gb83powxUqurKH1qkgX/IVQPMv4WFl9a1qJsUqlOBZswXEBDqViwi+soeP4Tt+SRTpLBcuO80IuchLxk8zOOKg5h6nMMnmeihmM5YS+cM1JxhdQldSjJTgyK9hiQf2MiVnFZj",
"part_2": "i4VHMphiMxEj8zsWRQLlg55yXkUjElIRXA4IwXKh2zDLXICckZ87KUxQC+VsDZeA4LueBCgZyCQpu0tjlPZ3MzRLpX0mokRgJMJC/FFyjlYsz5BObAxGRjSQPoFMaoA8UrXpQkt5apAZR8LMVkAC+0uoIDw38ZCsAuExt7C75gqUAa+mZ2UhWGo7SsBW1Rz7JMA1ttrvUPWurmrAQBecpxawuwv4WOdF/NzUJAnfxdhdyiKez4fXo5",
"part_3": "gB/Q/EoRdPRfTdk68yAFh5Ol/ioVQ+8gnilGheFOCxbV4oQX4GhKpwi5nNOq83Slul4hBvC9LBZo4LLfZXMjruYsz7kodahASzTiZwqpZqXScIzo1j0dsg1LV0zbZlUfKvRX1uoQEoNEyGqG6HI2JmCF3i34hTJKBwCvbh01PVzza4WYOQY35oAJALQEdaWiTCd8bwBkKoo8w55hIxVTYoqSFNiJrJQxgGFakYLGvRvOamK6TH/TzG",
"part_4": "iOu/lVyPM+5u0CqcFIkeeQSe0pDLkUVbBTY24TgvVW/D1BR2G+GWMnOhRHYp8+LwQK0y0aek2g0gLNzVLBV1FIa1CvUOghMlvxGbEk+nUinkLPgY9//I1RTX8d2wbbtvtgBk/133k99Uuy9+Gvj7//aZxiIovovkU2XEMXW8jKFJXa4BNOXqqN7UZqH6OszLGIpmc8Ww4ai+sw1iavrBStnTrdGhNNR1vUMcQALVdlTFvT5fnHSnWJ",
"part_5": "xpqOkLGKItKMN6q2EWPAUTF6V6UFxZc0pm24Gclrc7CTLjDh5bhIT3Bnm0e64mNBUJzqcRfndxdskWNBrJHq8BiJAELw6MsHD1xwaLmxCAeps7mu/umuc+yrCx0SRj/dha6BUwN6KRVf0faN1ClnMtoEaqnxYk7D97q/XjyulBls1UEVEOty45SiLRxjofZjW+BMdZEiW3birZbkdoq9qQkI5yWm562x+LdRfkWv1+pFhdcpWy020H",
"part_6": "TasBkzwVCfgNoub/vhR2V7Ddnq9FspndJtAyWsKy/XKCK1zoqeT1nbyfrrrgPdw9BDGN9+6mRu0N10Qm/eKerDEPMYTOR2cZqw69/EetBl/ZylqtQV2l2l9fk8pfzX5wlV9gzZX2FFhrE+CdBgc85qJai7AxLF+SDJl03ZoU3IjCJ+6JrVZcv98E8AB1iHGwSDjm3IX7FpWplir3btxsFSm7bumtZQd03F69VBos+rE7qQTOhUw/VL",
"part_7": "WUE5l1VGbqPCiAN4NMus0icoVTw1kVQb6Icyq1xdaJtqRnIKrqrCmIK3Wz7Ai3HBpxjkYkz3ZDqv+ngcHcARKuld7GnyLii8NLLe3qDMsxS/34zE4cFtFqGsw6PhcN/BTo4drHHKfBnHHg7pEgSQTuFQQ5zv5/AVbcIt9Rx98mcHh4Nc5r29dn1nGos/1Jv258/ydiIVY5zo4fy+s/f8+Sk8o1razCp4dkBLOnpgX498edoZO1iwi1",
"part_8": "7et/eIXdSc15r19l7elYxWkoN6ag+51Twgr6rAPMJ+7Yrde2P33ti9N3bvjd17Y/fe2L03du+N3Xtj9974bN4bjZDSGh5Zb9++NffYkdi9PR7x7UFt5NZ607cULxVybR29H1lqmfORNYSRpV19XDvR6uOI5s9MmrOge7qgPL1ImhPBrNKjl324j+DmONomGM+le0tuz69tkt27C8a8pNtTTJiiEKIAIg8iB6jt67YNUYzjj2ZKozEm",
"part_9": "c9AeD8IErUOdTgBugMb5HnjRY/mkUUeMUSOJIAkhifVvAM0Q/ibbOb23ifUHPB8luKHrh1GcJOAnduw5QYgcJ15sx1EQgx/Yge8lngNe6DtRHCEVSeA6bmSH4PguzTuQuLYd2ugiHHBj13NwoxcmbuTG9jXusSPXRmEPNSGkoHZs1/YDJM8LEZYb2BGEXpBEsee54CKw0I8Qpeclju+5MbaiyPejKI4hTjzbs2P0bhJFDgpyQwh9L8",
"part_10": "K1sQdBFIRhEEThViNwq+0iLfcxos6U7dni3EtgS0rbNKHVdp5A1y1UrE/fSVd4vS64X3MrxPABEF370TH+f5vXVKIH0Bc8Dnvbq/IDcDn/rVtvyKR7GOQ/wJ6taPxHZTdpPvBkre1VvPncwwrvrpRuReA9pPgEn1HxedSa9cDakKwH76r3ZK3twfuQ0LlV5NxQ8J8uZz6t2HkExXevFW4zax4Bl2/o/7eVx5VI31XcGqqi4pf/Ah2rew0gJwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/9VTzU7DMAx+FSvnHWI78c9ehSAuQ4CEOtSlBzTt3Umrda3GdgMhkkj5Yju2P8c5hpd+P3S7p9oP9TVsw7GEt+5jqIcStvBQQgYBLqVDIMBxNlzCBkpoOM5jEi/HxSbeN4Lfh1d5gJ0zAFdwAbdpZZhFbfnlzsw8QwIe2d9hxakpSCiJmjskj8aYBUGdLZpmg5RjTuyMwJJQTTG3sISkUQATjXoEpxglaotHiYwY20UWJyVbmFD+04r+C3gplvx4rSbXj6Pv/VBX34RWzXGj+77LaIF5bagUW3esnvsGq6tsTmETDvXz/bl9335o2+kLR4DZgtYDAAA="
}
}
|
codegen__primeintellect___2372
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\n\"We've tried solitary confinement, waterboarding and listening to Just In Beaver, to no avail. We need something extreme.\"\n\n\"Little Alena got an array as a birthday present...\"\n\nThe array b of length n is obtained from the array a of length n and two integers l and r (l ≤ r) using the following procedure:\n\nb_1 = b_2 = b_3 = b_4 = 0.\n\nFor all 5 ≤ i ≤ n: b_{i} = 0 if a_{i}, a_{i} - 1, a_{i} - 2, a_{i} - 3, a_{i} - 4 > r and b_{i} - 1 = b_{i} - 2 = b_{i} - 3 = b_{i} - 4 = 1 b_{i} = 1 if a_{i}, a_{i} - 1, a_{i} - 2, a_{i} - 3, a_{i} - 4 < l and b_{i} - 1 = b_{i} - 2 = b_{i} - 3 = b_{i} - 4 = 0 b_{i} = b_{i} - 1 otherwise \n\nYou are given arrays a and b' of the same length. Find two integers l and r (l ≤ r), such that applying the algorithm described above will yield an array b equal to b'.\n\nIt's guaranteed that the answer exists.\n\n\n-----Input-----\n\nThe first line of input contains a single integer n (5 ≤ n ≤ 10^5) — the length of a and b'.\n\nThe second line of input contains n space separated integers a_1, ..., a_{n} ( - 10^9 ≤ a_{i} ≤ 10^9) — the elements of a.\n\nThe third line of input contains a string of n characters, consisting of 0 and 1 — the elements of b'. Note that they are not separated by spaces.\n\n\n-----Output-----\n\nOutput two integers l and r ( - 10^9 ≤ l ≤ r ≤ 10^9), conforming to the requirements described above.\n\nIf there are multiple solutions, output any of them.\n\nIt's guaranteed that the answer exists.\n\n\n-----Examples-----\nInput\n5\n1 2 3 4 5\n00001\n\nOutput\n6 15\n\nInput\n10\n-10 -9 -8 -7 -6 6 7 8 9 10\n0000111110\n\nOutput\n-5 5\n\n\n\n-----Note-----\n\nIn the first test case any pair of l and r pair is valid, if 6 ≤ l ≤ r ≤ 10^9, in that case b_5 = 1, because a_1, ..., a_5 < l.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5625
|
{
"part_1": "H4sIAEb8N2gC/+1a227c1hX9ld15sYTMCDy8U6gLtEADuCiSAi0QFBlH4WgoiQCHnJAcy4IRoK997wfkoV+ST8mXdK19DoeUPCM7stuHQiPeea57r73WPrTfzdZ5n3dFPzuf/aUtN8Wrui+qqrjsZ/PZ1a6+7MumvqjzTYECeFTW6+Lt7NyYMJjPmra8Luu8uti2zWbLJv7aVG8K6W8KuWqqqrkt62u5bNY8ocyqKjay63jHInhy3eabDe+rvL7e5dd4eNffNPX5ssbf7JviBZtry2ItXVOVfd7eob36qqyLTVH3c7nN+6JdNXmrfeT1Wqqy64ta+2jkT7uul1e1/KHI3xTtnI/qRvI3eVmdyTeF1IW2vCn6G9Yo3vYtGj5bzmz/fy77virk91VR53Ld9OhA8rbN7",
"part_2": "yTvJJdV2fY3a9xt26LDcM7OXM2/YXa23EqaK0H16/5Gaik7aVZ9jtGv5Qo2UzO4Bu8V5ET620ZKeOO6aDup9FH7808nlfzyz39Lezox5GhrmPSyWO/aQg24ujDyUlYXvh4DPYY4emd8+2XTSl5VEmmDpR7rcxEUelf+yGJSXknOm7k9yULMeOmPl8F4GcrvpNXBroYq2q+rM7kOJtcclRl7Nk/r+bfOTL+2Z2/seazawLLtbdkVQmP9vdnBUYVcl28KhwEiQHt7QdfRDx3CxPnwTL4sP+zDuXS7yxvUzQGt7ba6GzyaV9cIrv5mI+uiu2zLFQCTrxoEw20Jl92VRbUewbiS4oddXhHdqxfq21f9i04QUG2OzlFXe9CG6+62aAF0REmnRZf1gr9X9XbX69UA4KuyRf",
"part_3": "BUACvnV/I9Y4/w5dSJPsSGmx0we2KBVOvReN9Fpz//9Ms//qXdOmCjncFmZ0M3XYFG18f6qaXb5pcstcVkekxlb878ApBAyCkC6h/lhG7zvsu0fwsKN5JsMpKiUubodCz7QSD82/UjcwUFwTN4VcvlDQZyCdbp5izSwZDunadTM4f7wozlq6Yv9q64UzzVIJVxbqs7O917nvl6109dY2+PIWtqA4ey0Qo64Kum3Th25BhbQKds3TgfgM1CSbHdFjrcza7qyy3cDjbeURpghMYOKK/vXBxsngjBP77NN2i7c1NVRC7raFkbRG+ASMWlh58ZzbCsYzGRdmdLGw+NGU8WmSxSWSSyiCWWRFLJhO+0Pn/etJFFJJEdiBsKPbW3OPSj38dDX+BwCcXUCW/zslXitg6w92D",
"part_4": "5N3lVrudksfigK/CqthbRplYXEVlvLqviMt+x7Qm2I/LaHqkWm8oCK7ihh+5p33cgqO6m2YEXtgBrzwft3k30Nso2nCz/vmpu+c5p9SDNOoei37V2whDu4gya3xZX8H99yRSgxjjR+okO4+T0dAlhfKmae7LJt3jcz8W9O+u2UGyUQaGVVtPHy7rlXL3ht6wr3C/aJZEJGcJ8AJnr4iScS30KHROacfVtSWi/lt+85PVrfT68eS0vX8oL74V7KMIeAPITKD5PuVYOz9H6F2jjlC2d2rJF1RX7ahzIJn97Us319F61L7Sampdl2lMYRycJw/QtuAL3zpbPudBzLvScCz3nQs+50HMu9JwL/f/kQntfz86/nX3//fdWopf1c140zYtoVhhn9no+I0ZgrNm375az/m5b",
"part_5": "LGfnspypry6cF2ZzPFEr2JfRcgrzAefMQVjQhpgtGU/txQLQyI/vx7DOIwFyL0IOda+h8sRuU+010145BO6puMf7zu0ADneefNrk2arvx/L+Pm14eun76eE3U0sdMRVbxf7rx5nRwosMVspoGx97IFkoWSyZETzLIkkjyTxJY0lDSQNJjSSZpD6PSYAKNLTRirYBNIYqi5T2puvxHJUXCZ/BDQmxEGIHGnyJU4kDiUOJ6Sw0k7AImnH3USBRIrEnEYrgNUraHa1E2FF5gVeLCFUivI9QPUTVED0GOAcoE/q6h6mEgLyRMJIQ1QIUD/AqwDVsvwhQ1cczgwn4vMaADeESKHAURj4RhQpByA2NogHUQ1E/Ez/Q6ym6HvzM/d/47PG3D555R+IFIAjMEyMGVgEnLCwxu",
"part_6": "IgxEtybyuFej2H2SaPwwA0pOCLGWgEmxmjMdAj/NZ76QMdHSCL59I45dm4AJv5iHUMy9myO9Jx9pp4xTe04e9CxOdax8T5Hz0593u/YHO34c4nRg/3+9hGilEn2aaKU7NkkGTYy5T2WP9z15zLBqImwPDzAY/y/i/QsUM3JnHSQZT1mCbETIc9qCF9CcVQzqB+qI9SNzGmI53QE9zHeR5lTBjQYJ04RBnVIrDqEOIP9F6R/VYlIlQ5G8PUYWtGgYASxU4fYKoOqQ2aVwg+pjpBA6BxFERCOuWGovEBHPrmUM6OrY9UQahyOMHUkiU1HOAoHAEgh5AxzwHCxQWPRCOIEFINuBG0YvYS+YWIYexjcQ8xjvwdC8kCOjorQQRBgjMETXJ6py0Pn2Ui9yzQj1TRDE4xpBq",
"part_7": "IJBVFB6xraFZkEtsQaOGO2kDhssKpiw+g9zewNG0Ybq8kiPUIfYbhEt5RGDKiYKuYpj8xJxiQk1jNEHUkBPE6BZ17iO4ihS3SxYFISxS75CG1SQiiGnoVZ5M6KqcxmG3q21/QqfJspGXsWcuxGz4HumD/IEtIc2ASE+QnPviYkD5ONoy4+lIp4xwD0sMgRQiDSn4CGRNEw5ItDvMdj/qjEkNj8kVBQHgjVxyjOkPUIHOUNckHqksaEfBpofhorcDIe1Wd0qdKDUbpASRYMuQFM8CiDc0hGR48GzqOhJqsWSRqnTCIzTShDJqkEUKBbRJAxH0+ZFtrk0JJNYNNS3SMBNQBYOIIn4MqI0R0SBrGyQiweHE5EkJQidyYyEiUgTU/99CAJHA3uj4XE/WeHnY/AMeEnUYE",
"part_8": "LXrfiCNSvuu1fWWEwljJSBwguLkj6ZIVEt1T52ydb0PWhEoavDsaW6hapA5PR0/Ch86eviwJdICBaeTHQQGKXLaSCWBkCUU3OiOhpruYiZQZffawCFFgxUqQhdA29C8dyc2SgJOH0h9BSoohHkgiZBgZDSuJ8bqz4cDVDQSJDOCGy5/ggDRz19EfQxUH5OLLuSOUpaUC4X3qGzsmDAAxnxwh0uLKAcedBtQkPi5hUxZsQSDX0I5cjRMoHNofwCAKuXlO3kiUaQm6kAd85LrBry2GNqZlFZKmeDmYmodfTbCIZA5zeUY/6bu3pFpLqxcgtNAMljYTgQ3/gGhzRCFBBPvGVW1K7GJ0uSE2oCQXoBb04tklFMWMVITjOBse9/UjOcK/YY4khBvIUHYgVAYPkWyRkmlvR",
"part_9": "q4FuU4UIHTYsPvhRIlWWjzQ3iHQLNAuzvB4rtat5ccFUINZoD9TUNhUwjPbI0YzmmcM3i9QiTvPNxOmLTRk8x/KBBj55IFXGz2zmuZcaKzu+JYFYLzAeXflgfqK5n9EEkJzgAJZN1Mc4WkgsRWguMWTvPCfvfWr4UMw/ngYeKnjk25z3NPZP1eWec+YQ5IP0D3uoz5gjJir1mikuUn8UAJcNWK94LgMINOr5jSpwoKAj+SVJQ9lzIZ7op6tYiWAQCg1spWTPqT7tPqVn7oYigi6ZwuuFXRK4nco8LBf8xH08Sh1DR25BEDrXBe7sadIfKx0Eik5fQZnpUfPWRayrhXhcMzCN9VSMUiawzFEBxeS98D/K5J73aMEjzGEe+faEqHgqA1iVzwa5j4Z0IFTfqxPJ6faYD",
"part_10": "T6zy6396tEtJRU+ZlxJDqtG3SMle8NlBFO9lCTBbC7hp0XyhPKxyv0eW6Geyc4+3USycBKhYe47bGVKCYm6RZPAIW20gZztdy4jQnIG2ds4AfGdgAwfL93XyH3qZyapn++EwXPAMgO1BEwjrUZ81BfIR1YDD6nkADKOJIVYyPhPpoXM+S1S3zH2bVIY6UIxnZBGNnpa08LBy4nlbXpeeTuzrKH8HWt+4Ku8GLeCsJ+ZhyVdas/DEk6/Lcfu60HmaCGyLlOvKnMwo4gUVYlSQ6Lw8vRodDFBN4Zm3JUnMscVLmeYXAM0AAHJwGj06zJwSPqG79YKM6dflgYyRZSnW+hWtpaCzKF1onc42D+cB5iDCHn0uzSWru7fJl7zPzl3F7u6/GFXzM77dlf8+B8e8c0rJS0AAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2374
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nHasan loves playing games and has recently discovered a game called TopScore. In this soccer-like game there are $p$ players doing penalty shoot-outs. Winner is the one who scores the most. In case of ties, one of the top-scorers will be declared as the winner randomly with equal probability.\n\nThey have just finished the game and now are waiting for the result. But there's a tiny problem! The judges have lost the paper of scores! Fortunately they have calculated sum of the scores before they get lost and also for some of the players they have remembered a lower bound on how much they scored. However, the information about the bounds is private, so Hasan only got to know his bound.\n\nAccording to the available data, he knows that his score is at least $r$ and sum of the scores is $s$.\n\nThus the final state of the game can be represented in form of sequence of $p$ integers $a_1, a_2, \\dots, a_p$ ($0 \\le a_i$) — player's scores. Hasan is player number $1$, so $a_1 \\ge r$. Also $a_1 + a_2 + \\dots + a_p = s$. Two states are considered different if there exists some position $i$ such that the value of $a_i$ differs in these states. \n\nOnce again, Hasan doesn't know the exact scores (he doesn't know his exact score as well). So he considers each of the final states to be equally probable to achieve.\n\nHelp Hasan find the probability of him winning.\n\nIt can be shown that it is in the form of $\\frac{P}{Q}$ where $P$ and $Q$ are non-negative integers and $Q \\ne 0$, $P \\le Q$. Report the value of $P \\cdot Q^{-1} \\pmod {998244353}$.\n\n\n-----Input-----\n\nThe only line contains three integers $p$, $s$ and $r$ ($1 \\le p \\le 100$, $0 \\le r \\le s \\le 5000$) — the number of players, the sum of scores of all players and Hasan's score, respectively.\n\n\n-----Output-----\n\nPrint a single integer — the probability of Hasan winning.\n\nIt can be shown that it is in the form of $\\frac{P}{Q}$ where $P$ and $Q$ are non-negative integers and $Q \\ne 0$, $P \\le Q$. Report the value of $P \\cdot Q^{-1} \\pmod {998244353}$.\n\n\n-----Examples-----\nInput\n2 6 3\n\nOutput\n124780545\n\nInput\n5 20 11\n\nOutput\n1\n\nInput\n10 30 10\n\nOutput\n85932500\n\n\n\n-----Note-----\n\nIn the first example Hasan can score $3$, $4$, $5$ or $6$ goals. If he scores $4$ goals or more than he scores strictly more than his only opponent. If he scores $3$ then his opponent also scores $3$ and Hasan has a probability of $\\frac 1 2$ to win the game. Thus, overall he has the probability of $\\frac 7 8$ to win.\n\nIn the second example even Hasan's lower bound on goal implies him scoring more than any of his opponents. Thus, the resulting probability is $1$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIAEb8N2gC/+1aUXMiuRH+Kzpurha8wDEzgMEbP1xSSe2+3O1mtyoPi+OVZwQoHqTxSGNMXK7Kj8gvzC/J15IGsNdOZX2+lwRcC4zUanV//XWrUe1tK+eWG2FbJ633lVyJd8qKohCZbXVb81plVmp1rvhKQABDUuXipnUSx8NJt6UruZCKF+dlpVclqfioi2vB7FKwuS4KvZZqwTKd0wdkLgqxYrWhJxLByKLiqxU9F1wtar7A4MYutTqZqZl6yw1XrNDXwrCy4BuSW8ASw7jK2ZIbVolMKFtsWC5NBrlK5",
"part_2": "Iw7GZZxeJGzT7r8mOlK9Nk7hU2lYUZnmah6hbwUXhKmVIJx/IvKyG0kKsNy7YwWcM9umFlqbXu6tqbP/iKVEhWDKnJCK8HWS80M7eKHVtpYt18GYJmeMyuF6TpJeoCE1WXPLcBGa1kU7EKwXGQFdw54LWu/TQVf9QourqVdMnFV88JByS9kIe2mT0B9WooN8ADyf6uNZXOppFlCE6lxLhJeSq+dk2suLbk215UTgNV1AXt/X1sPxSvgC5PVpgnZdwwbQHW+gINumwIe+hDyEjbCK+/+d+xPurK14uDQhgSCWQ",
"part_3": "hGVhcYzZmpVw0KAbILAVOEl14I65WTxbww2plp9GoLXROfnfJKrMTqIsQenINBF7rGeq3YEk6v6mzpxd2GeZ+9hRDI0nUKpcIWK048ZxwLvWNOg6Egl5W8huVdWME8I7WCcwsNQc0uCVailVvgovFThm0c5TFPuvg1lwUHkoxyrcswRMvIB27dYmcYbYbnQnD4H1WRw+BruCAVmSjEvfZcmVMWMmNhZyMdkkARtSpRYiUyBRBJRZA6pQZsEipzS4j6EgILwjbi53GX8fOky2azXFtDDxBoRwMMwA9+LqMO+9c",
"part_4": "//hnC8Sq4gOzwEEkTZpiqKTYsiiOHIKmGDiR6FfXZT0Uz9Jq2w7vfzz2W7JTBUfZprb1rxvE308rI3IU7l/M5vijL5DyksbiRxhrPmFIb6cIayQhAOhZwH95rXtTeb3IlKDIEDmaRtH6/PiOUfyGI+IJL1Q3e5VoY9cr64JM6ccMz2wSojYF7EhThPQlK8DVqbKfPPmoiQ+MRpDiMDAHci6khJiGOLvuLTcj/guoIwwoJMjs+vBVFGUzE6rwpsk2tIM1LuXKVBfR0S97ZhiQocWvlEZKWAujB2LIlms3mFc9u",
"part_5": "39/dfriLUPMI7ui9p2n0IXLBUVr1lFggm67Fjk9eArFFBRyAB9F7T6MPiO6fRYmS8SAoNJ+BCOzDX2978R2eypXO2e10OkmGw3SU3vkEmKkevd6psrbuW6iGPkULqRy4FqGjPKnEnk0gfJcSyRtXEbljb1XpP+KBMzUwvvIfxn+MBpj0CUCGB47D8lCdfGUJuRtogW8I3rZ+0bYuVE3udKkSlzh4AV2x2Xfvl9ru+4djGoznjM7RYuvR1pgHAfd0+J8L+R9v+KoshAmoOAbMVMLGLHU56yCbqTgZHk8Go+HIO",
"part_6": "e6FRiwZsDi+J7Y3HQ9YivnB/vxkNE0TBN0bEEz4WVuxDcq7gJysULyFNy5gT2D7xI9SQmJIb6OI4WCLxhEOEpxzaBfmbFfjIePHSWjlT0do2QkYW8mMGp+9ScTP0V6XJVoNZR/qTCMyMQgGGX/G7klsaen6K/6QTYERLGZJRNVnHRhDpw0qNc4j9Dk4WonpGF6GXuYJLcds0mjp74FoBJI236KI6qa2qfLgfCeQmISYpNYEtY1coaN3hwtXofDtvDaNqbv+p+lQGyvplI2bU5Z4DR5sWzVjcbw7qDa6piyqi5",
"part_7": "z6BOCJAepXitodPJZOrlwThejvZxwGZtshNw0x6amErSvvPdpl0UenXQl3tmXUeF+gkTzdZsKbGZpw1BqCon3TZZsO2mWGl5y3N6eng+aRXkFx7Efs6W7Rjz8mnWa0bY9s5wfaZafoh2Rfj5O52ZdpTA7WSIWwG9G+aVaF+e2GtLJHW85PP8dnMyWv/Sc1eJIqDzrdhWij8Rjh1WiZ93mJJjxvt+efZS8+O5LehmC6vG7mm/0hdtbpeJv+0MaRffnAIEgoqLn+fOneVe/yrHGL1iBb8829dd/70Pqxe6qg//V",
"part_8": "lDxbjLWyZgZn2nNKhfdllWAI82PeXu4OBEIE2OtItL/Csm04pc0kHctx4kSb3tyG5fBBbDKkHQ1+HnF6iMOJxoYEf5cqchq8PwjGAc6/j+0xQvZsjuRto8JFdAAKnZadzz0b7u69MvKgEv7wnJO/TrTGqjbde0HrkQ2MpDPtEfMLDZvnrJ5eze8GE6EyVaFJxEJ+idzC2veIleIUVLv3bnb5BocEnOeh+iMq/i9O9iNPqXkXith2LeHJPriFoM4A5B/sbnwJXO8yhweww/zogJVHKNZSo9hK/UTWVSUcdVz6p",
"part_9": "83clfT9opteWUHp09Y2xaaJ7Bbe6+/Que5KoD3SuOp03uwV7uJckQMg/vuqogeKowYYsbELrt4WiDoqhAx6F0Fbo5fAcaufhxuFw43C4cTjcOBxuHA43Docbh8ONw+HG4XDjcLhxeO6NQ6PEtE4+t758+eIb45k63D4cbh8Otw+H24f/z9uHnW4qqCiLrbNuCx2yRZlsfb6dteymFLPWCZu1XJU+D/W3hZ8yLRc6P+k7BehwE9qf825m1zLQ7F2X/fdKm87iUbXfrm7biTymb9uSPEPtgOHvca3JZDRMJnH6P",
"part_10": "LXxb6DWNdtP6I2frW84nU5fSmXitD1hIqbiJImPj79d7yRlhBmLk8eZejyaTEeT0WT4vGA5HOjt5fgalKZPsGA8GAKLafIrVP8G/HpRcsUvpyx5Utmv4NQQNSqNRwyxeFR1MhqnKWL0DE6Np8yxdfp4AUzHx+k4bfb9Js1TJEI6HqK0TpJHdU9HyTgdJPH4GSjHwCJh6eT4cc3xYDQZDMejZ0E9mYxZEk6Sr5BO0+FolCTPj2EyiCcvRbYQvNH0xTQ2QaO3/6TzjP4fozmvlbyqRevEVrW4+zfoA92xCCkAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/11QOw7CMAy9iuW5Q2zHadKrkIoFBEioRW0yoKp3p2VoAovt96T3kRe8TWMeLuc05XTHDpeIj+GV0xyxg1NEAjXGgIlxiNhAxCDA4iwQeT5IMiAGyFTEpqlUDFQhq5sHKXj3q/hG7aOwh67f4ZhT3a2UUnZimNzBeA3CWjl59mrZk5QWIRAztW1pqU6EOdiS/3f1KzY4p/fzuv1qyttaPwkpGVpDAQAA"
}
}
|
codegen__primeintellect___2378
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nDisclaimer: there are lots of untranslateable puns in the Russian version of the statement, so there is one more reason for you to learn Russian :)\n\nRick and Morty like to go to the ridge High Cry for crying loudly — there is an extraordinary echo. Recently they discovered an interesting acoustic characteristic of this ridge: if Rick and Morty begin crying simultaneously from different mountains, their cry would be heard between these mountains up to the height equal the bitwise OR of mountains they've climbed and all the mountains between them. \n\nBitwise OR is a binary operation which is determined the following way. Consider representation of numbers x and y in binary numeric system (probably with leading zeroes) x = x_{k}... x_1x_0 and y = y_{k}... y_1y_0. Then z = x | y is defined following way: z = z_{k}... z_1z_0, where z_{i} = 1, if x_{i} = 1 or y_{i} = 1, and z_{i} = 0 otherwise. In the other words, digit of bitwise OR of two numbers equals zero if and only if digits at corresponding positions is both numbers equals zero. For example bitwise OR of numbers 10 = 1010_2 and 9 = 1001_2 equals 11 = 1011_2. In programming languages C/C++/Java/Python this operation is defined as «|», and in Pascal as «or».\n\nHelp Rick and Morty calculate the number of ways they can select two mountains in such a way that if they start crying from these mountains their cry will be heard above these mountains and all mountains between them. More formally you should find number of pairs l and r (1 ≤ l < r ≤ n) such that bitwise OR of heights of all mountains between l and r (inclusive) is larger than the height of any mountain at this interval.\n\n\n-----Input-----\n\nThe first line contains integer n (1 ≤ n ≤ 200 000), the number of mountains in the ridge.\n\nSecond line contains n integers a_{i} (0 ≤ a_{i} ≤ 10^9), the heights of mountains in order they are located in the ridge.\n\n\n-----Output-----\n\nPrint the only integer, the number of ways to choose two different mountains.\n\n\n-----Examples-----\nInput\n5\n3 2 1 6 5\n\nOutput\n8\n\nInput\n4\n3 3 3 3\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn the first test case all the ways are pairs of mountains with the numbers (numbering from one):(1, 4), (1, 5), (2, 3), (2, 4), (2, 5), (3, 4), (3, 5), (4, 5)\n\nIn the second test case there are no such pairs because for any pair of mountains the height of cry from them is 3, and this height is equal to the height of any mountain.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAEb8N2gC/+1bzXLcxhF+lam9hLRIav4xw7J8iJKUnSr/lOybVqHBXZCEjQXWAFbkylZVrrnnAXzILY/gmx7FT5Kve4BdUl7JMk2nEhe5Wiww09PTP9/XPXCVv53M8z7vin5yPPmsLRfFR3VfVFUx6ycHk7NVPevLpj6p80UBAQyV9by4mhwr5czBpGnL87LOq5Nl2yyWpOLzpnpeiP6iEGdNVTWXZX0uZs2cfiBzWhULseroiUQwct7miwU9V3l9vsrPMbjuL5r6eFpP6z+V3azKYVN7TPJtIXJ8q6bvRHMmVnXf5nVX5X2RQ7FYrupOlDVrfrLqujKvxfOi7WA/idNw10N4UdT9geiaQWUJZXUhFg3u2yLvIH3WtGLdrETfiKrI23qj7nifzHpSzr4",
"part_2": "WeT0XHzdtvxZV+XVBoucNXWmbtpzDkQ/L8wvxuF2zulm7Zi+b1bxav/r+x7//c7s9FBdX8KVpEaccC4rZRXMknhQzWFqtSXAt5ohFA3eKOcmXSFJbdD3pzGfNCnczMbvI23yGiZIf2WeoZ2uORXkmXjP8tEDyRsu6crGq+rwuoAx7niGh2PPsDNvUPaKDaOdl3R2QNSX7Iy6bVTWHFnGBINFNf1kUHP+u2K4Qq+UYF6w8v+hF8c0qr3jgtOwvSwh/+oSs3S4hj/8AHM2qcnHKHuNbpTVbqWsbLo4EZeaPW30UV+jneDbLos0Jx+Lyopxd0Ny8QJwAPCi/CdbLfH0kHjd1V86LFoBYIsyIQFoOI+sVLGo7ccVGrQlwwy6YQehnolt3AJnYI7wDmIhT2V8QkJ",
"part_3": "gFL4q2Kbp9rH8krk6+/frl0dERbtTViRw0PhLrcXx9otYn8kh8cQE3X9CKV99/9+r7dfLgjM2/YfoxS70Y1784US9O5AHcJqhhuHyJaXVAYLganwShfTtFRoySUjSEUorpkfgoUYtHkPt2DjDMwf+ewnIzk/1lswkUZ7tjv2lbUt/UiArueTXy1KNEtIjzsqlTpWi6kuLdkZ+n2HCXsiPxFxheXOWLZfU6kkZxJcknqeSJ5o0jP0qFx0GTUkkCQ+zhrpLUiccPHz948PCv+fP84WdcnhKztri6lo+8E6/+/d2rH1IkAY/P8m4GvPN407764YiQ+mFRLV/nI6RmKypnHOfkA3mDvCZKQKIWXUHFmUO8pQK26VZAdk7CkEVIy7O0BjWv7UeWM61fJ+g1Rpcg2",
"part_4": "YbQ+WmTavkN6ZGLb+Lhx1RIUfIWEFpzGe0uuFAgPPNrXi3zEhmqWF8r9pT48R//wuP7eKC7ej95xL7czG4qI9wDdhuyUVrWswrt5nmxTxmq8vYce0Njfb0ckZp6vVFDcOTsco19nlecr2l9SH8f1ctVz3c09AVVDnjRoweghcyaTTb6gnaqR7dqvmophZRy/+C1/N5I46Z/8LafF1A6f019PW6AZDBR9yTrTw90p+Tf4rDNtWDd2Af85VgAIampzgC8+U8tGBz/dNVf9xwnhbpP5YC5nOw52AncBo2paZA9guyOlnJ9mz8nOnfDRhzuae2mtREalcoLR6LJmGkd6GGQsSTDn+sSMuketH/S9MXGhaGcpfz16KVgF4wc2wzbTpFJOL0RPi7oW1c7sZduNgzD",
"part_5": "gWL/eA/F1CIL9OvoVx8IM/za4ZfHzfBshmdLv9dM7BIItjZuz0J1k1iSjDwtZvmqY/YxpGn0J431GuyJ8mNFWBBDTCpaDP9BrOzGft28hTRHIx1KysamjnT9nAhFbW1bB5aMHQy0OIRVK66fUA7ZhlJGn0+aS5obTpLjwZFJXfSrNoUFx8riCCfStmBEzeiAWqOaQ/sem7G3jyjmGHnKQ/scl5IgPkwfdcuqxO+zaV2x2FYCJ8vzYq8q6r18n+bbn5nfPUGn2B5nDjSo6mn57INHKpVP3H+XP6WhQ/Xs/Uf0zKLTnsawVTVOTmuBv6T/q936S5Ln58OvDtV2xxYa3h8mbuxLEw/GfTcTH2wmBlPaZEo7DlNiZpTvR/Kt/l7xIlhfPmBr6ERTHlashJ5Zx4N",
"part_6": "HV++tyVpGw95e/d5efaj29x8+1IcssI/McnqQVZyNyxrPAxDuXzPuXzPuXzPuXzPuXzPuXzPuXzPuXzPuXzPuXzN++9eMUUk3OX46+fLLL9MBclrfv3L8bl45pjXyOnl2MCEOIM+Tp99OJ/16WUwnx2I6YZidDACaHGCEk5om3fR69cCmLNCkAsESgUdfHoh3V2qn23KzS6X85SrVlMrVHSpTd6pMjn93qdXflTKtKYkK+VAiE+lXOXFzwCjxMxLeiF+tQ+lM/E8Yop0Tv8eI3BVmHK3Biey3/tyVvYEY47TPEIXoYyaMc0oLYwPi67UJuEqnvLDGOim0jlkUyhhhdTBBKO+0EybLoqaMOC1slnknrAuZFd7KgHGbQZdTmQ3C+SAjNFp6dkq4SFqtyWhnlW",
"part_7": "mLUyYu0ZNsdNIIB+VIlAw+CBM8bPM6eOjLpPa4h0HIa5AeK52NIvMeCrMYUEWlxL2GDVFYr6AAag0MCsrCaI15qHeOzHLOCmMyXLWKDtsGY6HShAg3jMLexgEt3jhYY1Um4WO0MhMIXSRvlItCR7zzwRuDV0QfLAzDpgHBULBAq4DtpCVLtc0ctpAaEQghRhhDPkEHVmoXFEZM9EBsyKDXW+U9coJAwm+Tka8RsVE+wnitvcOItWSBj3DKGIk4YXO1uzfB9fjLoeIj9ydECF+Hq+RrwIcgiehi3PA96gTmAjMN8cMIDMSz5VUk5TBCaw0kMpYwrEHzfdqBxjzrJznNcxnuHa3f6RhCoX+5Y5HWUEkYzSYnFbuSDY4iz/ia4Zrxh1xOc5ZdyNhcPZhPJwPPb",
"part_8": "qR1YTA+8KxmjZpXOg6I5TWazxTpPrDuMIQ2afEbS1QKz+78enOLUpBRfm2IjqgsHQyzMhKcY4AjATz3zgCZAX8gggE8wVsNk2MAtK1G0QAktYSBCswAgi0mgwV7wGJD0h7A9oAfrt5aETzVlIhCoEFThCEoKhtOBwRFaapJARXIeq5AMkCrBamhVSoyECQFFCCNcS1Rd1CUuB4QS2EW2IQyI5FRK0FqnYH9oEiAFZm1IJ8JqDbaKKKLAUOF99HzfqhysAgrM0l9xMM0sDSDFuyAUgK7gGqYCyJnKHGoOaAybQcWOktqY0Z1w1KFMwocBo99oJqnyd5MQtygPsAYxBt5NRYxxhyMsahQQAoChsBGB/ajclDrTX6jCmVUoynK0AY9CoUF94HquAxkg/WZ3o0O",
"part_9": "GdQtGgUhSg88NAxayXeGeR2G31QJFEM00Yb46oa6oJksaqgIehi3A8Ala08aqT44vhrWmmjph4qgBiqZoW5IptTuU7OOMbsFGegwjmqvqWlQ7pB75MXhTIgEUoBRbtHKLCYBAOQU2QLUAQBPPRNohKNRE3WkRxcEACPRhhCgQgIfQAjIOzrJeEU13xGELBAK2iHTgLkGN5RBjyEAROKQQpMD7DVBMwIG2hrYgT6BIPGtZdoqoDmjZqZIRIM/Bggna9CayQ+wQkUDLgGajH7qjy5SbzFE52iQw0wTkF0E1uEiOqIH6pAlmREVM/RgOO+5DUrMGgnEIlRwEzWAWYKNlQp8PIgGoTJRoYDiAOAVURtMs2wOiKwAWaBCRvLTUCVAg81AA3Q8S0RUJIn+qbWjzul",
"part_10": "SIQnohDHaN2QfsbzFmxghxnJdVkM7Cww+NQDTMnQT8LMBkpavjiEeGKAZS2cM5LTOMAncG+o2/UflWxw5Db+laDZUchtLrUxyM5FDU0kjaWwckZs148h29TiuhiPnoHG34Trc4n03uCHKluk7Gphibjelxm5MkNeMlBxxPRiYOqbdlBA7aJCbDJpNSMzgYJJJ2gyvGbtq2stuZO0bT9wGp8RbvKXyC+/9a9TPRyidhtJvEDefqbK8VcBo8Ss1eCvuzIadoUFvv3V0/gtvmeL/6E12hMzv4nP3POLuRL2ZQY3Tg8ZLI73q308qfefc3JVUveNjd3zCjg/VmTf/gz9v+eft2/5RFN7lS5F6ly+F+h2+uyPuhv8S/PIZ/b8H3cmqLr9ZFZPjvl0VL/8Du7+P4rwwAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/+1UTU/DMAz9K1bOO8RO4qT7K3TiAgIktKGtPaBp/x3npbSbQOOwHWnUxB/x87PT5uhe9rtx+/Q47Mfh1a3dsXdv249xOPRuTQ+9Y+/7fsskFKkQKwUhjcRSSJJSYqF/J4v1qHcrsn7Vbvnv59I8a6U6hIIB1jkZrIcUDL6maKu3Yekom+5tFtOSjQCPmMU4kJqspjV7jVbzeKA3xGSWhDkANSGD4m34BRaP3RXDImeyXS0u2zZGkgIQniglszVqGQnrnDEq9eaL9io8CotMtNXWNMU10gUxETgCKaM5NWNE/noKTS7ALsijE4rOTBjF6NL/+TPmCYlR+rlu53p9QxC6EUEj3Y3DXFuVAo46/Kg34HjbyokuDYHpjx0a6GYMlkx3JIISN7XG3TicXVSxS8vv9pskXZdnJWhYPFdDNye3cofh8/3Zbsf9aMvpCzCVGzI1BQAA"
}
}
|
codegen__primeintellect___2381
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nUnlike Knights of a Round Table, Knights of a Polygonal Table deprived of nobility and happy to kill each other. But each knight has some power and a knight can kill another knight if and only if his power is greater than the power of victim. However, even such a knight will torment his conscience, so he can kill no more than $k$ other knights. Also, each knight has some number of coins. After a kill, a knight can pick up all victim's coins.\n\nNow each knight ponders: how many coins he can have if only he kills other knights?\n\nYou should answer this question for each knight.\n\n\n-----Input-----\n\nThe first line contains two integers $n$ and $k$ $(1 \\le n \\le 10^5, 0 \\le k \\le \\min(n-1,10))$ — the number of knights and the number $k$ from the statement.\n\nThe second line contains $n$ integers $p_1, p_2 ,\\ldots,p_n$ $(1 \\le p_i \\le 10^9)$ — powers of the knights. All $p_i$ are distinct.\n\nThe third line contains $n$ integers $c_1, c_2 ,\\ldots,c_n$ $(0 \\le c_i \\le 10^9)$ — the number of coins each knight has.\n\n\n-----Output-----\n\nPrint $n$ integers — the maximum number of coins each knight can have it only he kills other knights.\n\n\n-----Examples-----\nInput\n4 2\n4 5 9 7\n1 2 11 33\n\nOutput\n1 3 46 36 \nInput\n5 1\n1 2 3 4 5\n1 2 3 4 5\n\nOutput\n1 3 5 7 9 \nInput\n1 0\n2\n3\n\nOutput\n3 \n\n\n-----Note-----\n\nConsider the first example. The first knight is the weakest, so he can't kill anyone. That leaves him with the only coin he initially has. The second knight can kill the first knight and add his coin to his own two. The third knight is the strongest, but he can't kill more than $k = 2$ other knights. It is optimal to kill the second and the fourth knights: $2+11+33 = 46$. The fourth knight should kill the first and the second knights: $33+1+2 = 36$. \n\nIn the second example the first knight can't kill anyone, while all the others should kill the one with the index less by one than their own.\n\nIn the third example there is only one knight, so he can't kill anyone.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIAEb8N2gC/+1a/W7bNhB/lYMQIDaiGpbkjyRYNmzDgAUDumLr/hjizFVk2iYskapIxTaKAnuIPeGeZHckZUuJ7cVdsWGAI9emyOPd777vj37wJrGOFdPetfem4Bm7FZqlKUu053vTUiSaSzEWccaQALe4mLCVdx0EgyvfkwWfcRGn47yQWU4sfpbpIwM9ZzCVaSqXXMwgkRP6QZqHlGVQKnojEtyZFXGW0Xsai1kZz3B",
"part_2": "zredSXI/ESPwiUr5g8IPgs7lWIKcQw0+yFBN4GyMrv3nyRqbrmUQ09hQmLC/4I5vQqZAPPOV6DTFensd5vgYtYcHTFFiczEEinKID35Tavi8MY6RUoGSGoOSSFeZyXJ0lsbAMYmFuV/t8auikSNe0nnPlbuNiVrBY41LP8bKxgDlBgI8cDZ114HvceGSFD/gtQJWIZSNxSdK0LDImtOGbSKESzkSCplASkN8GlJCQyYJZSW",
"part_3": "eLM6hjVB34OlXS362rKLMHCyqRXBDtlDDHhrHfNEDOkwWUOcQo0qpwrtw1cuBruWzIyCVGT6GuYY4HWSzWlrZCPo8xdtBmxna4RwJVE/lXxPZXWYKayzJFdwi1NAZFc7wvmaJoxdAr6mINlJF4RX+3Ii+1WdHWW4pTXigNKReM7KljwqOXEjjmwQzBwpk4Mx4lK561AhiNMLiE/Qm6v/V96NqXhf0ZjTCgW+JV4AfddvsM/",
"part_4": "vz9D+PrrV2dLoZr7YQETDGRzJ7SGCnk6U4FVDHEN3mClMBtkebjwId8HIKPSCZSKz8fixrqfMw3uK8cNBOCJoVIbC1AUuLHUXcMowlHy2It2IBBgxeHsSSEJaljSSwWZ61kB5ammWxsPInRujN/LHXdm1i+MDEaKCqmWbziWZkdZL6NQH0oAusAvlvFWZ4y5SCY4BqJHoT01YcrGI5EACEEAUQR3bKIaTOC3gCiAWxu9SGw",
"part_5": "xHgC/cayea8PQ+S8uRdAdyRQYIN/BDWUr6VmGyN9izWDT0zKVLHPrBYdANgmRFXNlCFcsniByVUrM+e6qn5rKfDu23mMWcTQfpjOPMNipefmqjElWZsucsE1x2KxNq608lxcPy2r+ikUU30nE1f5kB9WcFrLpaCEddxsYDbRK11IMTP4H7DCNxWol0m4gfBZqbw1fGSOxS1ON21Db5FXaTyVZaGrcMIidxZeBMFFFCHX3uD",
"part_6": "M4WsQVVXsicIVw4ZliGEUXQQXIfKLiB+581bUKZ0nn9vumcN8WM45UsZOsNFZPcODlFtPmtaPPlYKHtbmqOpjvCAvdGqArBtqeNDIZEUKBrppce2Pp6rOcApy2/keyJE4SRjzrLctIDdpjxsFcktL0wHQS0grKRWqPqQ2k0k1iBCfgumysJBxTGEdnHAKNkW02FRxnBF+htbO4ryFMnyLptXuqByHiVa7TbyTNEaD2EmEph",
"part_7": "Y9YVMYjynSx+OWYunUJ0lcYWXGgtg2NCNNB50cmSPjVt6ubSZuM6lvGg7uwKybh3RkLxMkYptixW7tBY63k5cQrZDo7n4kqKNyJIACxzTWElaLVQcnKSYmLat9i6OKd/wetcRva51VR8lCtxZsfZPG2cMkhtU1rDqksK3Au/m/CqwEHAZSJlqGtA1fQOasZ0cMJ32F0jqVteyJEWp2WNrk8SV0HQ/umsBd9x45WybuyLGhk",
"part_8": "xt30jio8cfTi+DeuOACfVBmTtA+5Vedyn2k84J0XhmpJoxbC+KEg5mY3JzDeRvD0XgDQ1EX2GTx3UXvadY+zdqnWfs0a59m7dOsfZq1T7P2/3PWrpgo7/rOe/funR1IRuI0d5/m7v9y7jZSRfVgYHr3vqexqmGgencfRp5e52zkXcPIM3kydhng+bhj/GkPqT1t+1O9QSFfQyxtFzHUtU7lffTh5WKon9W7WHO9W5BrbccJ",
"part_9": "ogZIHZBa4C7G0bEMhwa5w4qILuEK37v4Tuj67v25IKIIuhAMIOhBgFwuj5ccGsk9GFi5yI8M18V1z/zr75FNci8hDCEcmO8IwuHRhgycuMpPNRQYIQZI9Qf/6nKPyhvKcLuMtsvedtnfLgfb5XC7vNwur3YhIANs10caNrQRChSfEeyL0k+I0+ipt6yAxvsuUQPyKQZr3wXNkYIjo09EdaMCsCelw+O16htmPVcLXNhB7bM",
"part_10": "v/kNyPjqdPkfK7BmFXl4S3enndNilfQ45bGgyG5l8osMqR/VR9O4abE6ON16zn4QHjUfFjfrJ0dVp8NR45m3zHAjAnnmOLYbdZs96UpHh2XMQAF2vnqN9F9Z893ei/lFgVEl0OMM+Q26hSQ6a6+iS0Xs2arzMK0frEjU0sPmyL5eoWvXJaJ9UAevqDME9OyUNad4Ikf6SPijsnv5PhBqXgr8vmXeti5J9/Av+viP5VCEAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/72STW7CMBCFr/I0axb+TYCr1FU3IFoJhSrYC4S4O5MhZowaqTs8C3/2jCd+z7nSYTyVYfeVx5K/aUvXRD/Db8nnRFt8JAowKQ0BERv0TBYO1sJ75kQrJPJS4af9Oa+5ICx7CEwREk3e/dOdV9ZoD67s0GPN9dZw6ZQxdeCt2Ij4a9FDbjXINcawHjFqlmfEjSV1tfY15OTndPRUcvNOT+cwN5aOD47iVYQzzyR/rIPv6lr1OUWvGBSjYqfYK64VN0u+Tc+m3N42LNy9daYGG3CjFZ3z5bjnX3YsPN3uWRr1D8oCAAA="
}
}
|
codegen__primeintellect___2392
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nEach employee of the \"Blake Techologies\" company uses a special messaging app \"Blake Messenger\". All the stuff likes this app and uses it constantly. However, some important futures are missing. For example, many users want to be able to search through the message history. It was already announced that the new feature will appear in the nearest update, when developers faced some troubles that only you may help them to solve.\n\nAll the messages are represented as a strings consisting of only lowercase English letters. In order to reduce the network load strings are represented in the special compressed form. Compression algorithm works as follows: string is represented as a concatenation of n blocks, each block containing only equal characters. One block may be described as a pair (l_{i}, c_{i}), where l_{i} is the length of the i-th block and c_{i} is the corresponding letter. Thus, the string s may be written as the sequence of pairs $\\langle(l_{1}, c_{1}),(l_{2}, c_{2}), \\ldots,(l_{n}, c_{n}) \\rangle$.\n\nYour task is to write the program, that given two compressed string t and s finds all occurrences of s in t. Developers know that there may be many such occurrences, so they only ask you to find the number of them. Note that p is the starting position of some occurrence of s in t if and only if t_{p}t_{p} + 1...t_{p} + |s| - 1 = s, where t_{i} is the i-th character of string t.\n\nNote that the way to represent the string in compressed form may not be unique. For example string \"aaaa\" may be given as $\\langle(4, a) \\rangle$, $\\langle(3, a),(1, a) \\rangle$, $\\langle(2, a),(2, a) \\rangle$...\n\n\n-----Input-----\n\nThe first line of the input contains two integers n and m (1 ≤ n, m ≤ 200 000) — the number of blocks in the strings t and s, respectively.\n\nThe second line contains the descriptions of n parts of string t in the format \"l_{i}-c_{i}\" (1 ≤ l_{i} ≤ 1 000 000) — the length of the i-th part and the corresponding lowercase English letter.\n\nThe second line contains the descriptions of m parts of string s in the format \"l_{i}-c_{i}\" (1 ≤ l_{i} ≤ 1 000 000) — the length of the i-th part and the corresponding lowercase English letter.\n\n\n-----Output-----\n\nPrint a single integer — the number of occurrences of s in t.\n\n\n-----Examples-----\nInput\n5 3\n3-a 2-b 4-c 3-a 2-c\n2-a 2-b 1-c\n\nOutput\n1\nInput\n6 1\n3-a 6-b 7-a 4-c 8-e 2-a\n3-a\n\nOutput\n6\nInput\n5 5\n1-h 1-e 1-l 1-l 1-o\n1-w 1-o 1-r 1-l 1-d\n\nOutput\n0\n\n\n-----Note-----\n\nIn the first sample, t = \"aaabbccccaaacc\", and string s = \"aabbc\". The only occurrence of string s in string t starts at position p = 2.\n\nIn the second sample, t = \"aaabbbbbbaaaaaaacccceeeeeeeeaa\", and s = \"aaa\". The occurrences of s in t start at positions p = 1, p = 10, p = 11, p = 12, p = 13 and p = 14.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIAEb8N2gC/+1azW7jyBF+lQqzwEhZSRBpy5414AXyM4vMIdkAmUtgGZ4W2ZJoU02G3bSsmR0g19zzADnkSfIo+yT5qrop0R7Zu971IUgkQG6yf6q+qvqqutXwxyhTTlntorPoT3W+0m+N00WhUxcNonljUpeX5sqolcYEdOUm03fRWRyfHg+iss4XuVHFVVWXq4pF/LksbjW5paZ5WRTlOjcLSsuMG8yZFXpFjeU3noKeRa1WK34vlFk0aoHOjVuW5mxqpuaNSpekV1VRbrSmci6LptFvCnWj6Z1Ol2VRLnJtpx",
"part_2": "F0rCplNhCuLSmylU5zVdBKW6sWLF9V1XbpH9CrzULX02hEvy4KkWtdM59Tkd9AgFvmVlYok3mRuYMKY50yrtiM6PflWt/qekC2XGnKV1VZ8xDNG9fUjKDWtMotWzqib8qa9J2CHXpAq4CytrTmFa6kmSYFz/Cj1aqGzW5Zl81iKbi8CZoAyZU1dL91WAkVRa1VtgFEUyJMOsNs5WSJ0Wuaa8VQaJ3DPpgCwZSbMAx41lFTIfSAtF5qQxnsKcqKcc0VSxPLHHAAmvWyS1NsaFM2MGJDS11ULG4luDnsI45Z684A27ui",
"part_3": "1hU0ajArIyXxcTVcY8WnsIsDhPCKfJBG1ykYSW/MosjtkgrtHHDBckNlnemaNdY6a1Id7HHrsr7BSpVtJT9UG2xvicF8qZkGGYhar0b029ABtsO1CzDbLVfEci1D9my2Z0E+gR+fGQVjUjjUKE4ZtsfQrCjTGzsgzUyWF57lVG7EZLZX/7VhPEtVq9Sb+a3RYS77GezItE3rfNbqqVReU6+4+ph/GlDKTV+CCIulk8GxrQU47pZt3uRD10JgVqfdmWlZw5SqNJKo3t8jerdsAN3nhhhtW0BreAeGMhwZhg0aFGRVDM",
"part_4": "7SF9MpJ3ShGWbsYcaAya+Jf00YNaZlpbPSb3y/+dRHdy2rvxBK/aVsEHJlbwRuKdp1t4AMPD0X+S0wgQvd6AboToxGHFG/OHcKKtO0gdWAbRm3FYaM6He7PLgx5XqbVJzQ3njJYNsgoB0RXAl42sYHlcFyogAta/Q0bVYzcNeHA4z7YylWQHzVxgH1pZZkqEqbtyySRNyp2oGlfC5WiUY8u6uP1Sf5Q19SPBqN2ufv7Hc0pJjOybZEcd3wCzW2DBQFwWvi/x1QnryGFyT/Avu7BAGqB4klTjOlY8c1JgdP7tXDduE0",
"part_5": "Uvigjgcf+1CqLpGOB6Q6zBh0ho54aNCLH5+R+BnJ/RlwEds3NUP+vDVV4+SJu97xFgYqO2wJZrv55DynTWErXMtRABZMFyPBWFEvpu///i8yqPXykIzHNB6P+//+5/d/+8cDJvj6sC1OoXYFsg6IkxI7MZyBTadFZTX0Zx7WDsmyLRMV88b68lOBTrYbz1YThwbxnEZSMIZSDOD9AN1XEX6KGfkD9HvKCusRzHuKySPl/PnmrD4zx/6XmROI9G3jukzCqQpZgj0vZ9K1fNnHhv0lqSP5jc8aG2QLY6dmQkdTczRUlA",
"part_6": "xndDxMyT+nU5OEzphfpsYDm5p4u/SEYr/0BLNO0fLy10ONVUoGustOOhonkDJcQrDGtwjfkjvX/IBvHTqzrohxxxguK1snvQ2BlIyz4azkULGkMsxmKT54SNNpNPDZ0VLAT8EMPswxoaQcPqiXHb5sU0GKLfYCt6u2FaQlow6eQM49gPij/Iex6fDhIhYAtnO3uPZF16PogrCCArVMmnFo2/cktEeiQx6Pt6nkq5Oc+GZcTcBYmcY7kV2WTYEVQsYN76g4szViNZ/fXFZyfHy5X/vzXLvFyqmd5dQaR0oTsiLTI/wc",
"part_7": "qPVci004+2d6Th/ySmc91efzu2N4F5f8hASlnA1WMjB1dxgCkl4+slWRu96r4av+xfiy70c3PNodiS/9AHY55Guv6tPXNPYuuBjGlxin83PaBOHQLL3jS/rynO58py6s3o2P+Ehsst7F3YA2Xm2wrmIfsCnig54a0IxwMPEWKcNhZRa3UGZ91hwHyWynK2+wd3VslblpT/ohjc3cjniRQCmjjHgoMwQ7JydPCcgwMyx7qD7pqBc38waHsxcmYL/D1t+/D0Vd5JcBiT8Mcg/rk164bg/AJ7Dcwiezi5jOCEsh5uIiHo",
"part_8": "8nY3D31S9fXXKP2tIBdv1KkN/27xHDIwbN/VgL4BprKmCDDYEC62WOKnq9JcAtbKFfnKO9vtyi9suuO8tgt8w8/2zmzrZKJtD1zrI9Dr2951CIrYLYEI4hJcGnt4Kbhx84+/YxZ3ddfc/RRk4T0IEfS72VqnrInYHP914/JEq/D48qTPI5+HBwamZPjEld6O0ojzio1SxTxPlxRndthnHLRtxxIL/mDpjVRyEQUSgCrsYGjvdQNw5XAocrgcOVwOFK4HAlcLgSOFwJHK4EDlcChyuBw5XA//SVQCvERmcX0fv37/3p",
"part_9": "3f+mPlwPHK4HDtcD/2/XA4wQhSC6HEQOvzJRGKKLj9PIbSo9jc5QEqUuXYWKg2I5jQSCH+S9bP9mdn83gxZZWvqNRdbG0wg/IX68Lt78Ht/9/Pa3T8/JM/Xwbrl/u9y/X+7TOX6mzq/Ej63OxOuj/do6oy/i10nQvYLEHLrrVmen17/9fF1fUSJSW2awnptgG2tS4M8M3w+7WXv1Js/UG4+DkTPaKVfUvh9v31uV8W7GXgBHzwRwLIafBgORIDgjtKyF+pdh7rEY+VoUKGQIe9LrmLUmv4w3JRPj5OjYI+enySOyxz",
"part_10": "9J9uRokgxv+AGih9cvKPlkcnwkqQy55X6vT+KfJjoOtP3wQmnZMobL3QnaiQ8jG+HD+yJ6QmqcCtlTURZLXVWh9cqZshNROQkjxy+Umz414rFsHikUZaw8WPlY/o2frST2Snzyv4YSJKCWeKUvoiF5TaehasXBhzFrkT1kjq+jx8eunxhbPDqWDBdPaly8ZO1MsBkdo1B320loT9AeoT0aFmGD4t5E3n5+7YwnwbOzB5740e9Pr35pkMkPgEqeBJk8A+RzQ5lst18vMfmBDLvkfyq1V/4mMDpzdaM//Qfl90V7lSoAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/31S207DMAz9FcvPs9Qk7Rj7FTKhkpYyKC3KEiGY9u+4cdSFh+3BOs7xsXNyOePg5zh1z8HH8IZ7PFs8Tl8xnCzu4cliA8baSdEnKDqCJs84c/iClZXFDVh8BJ0qLWtfsvaDYwRRt2CYN/R7Va29CtTCalPX1OasSZnUxYvJs2tyILljVq87uuu8KjVo+mbxCCU2GbeMhtHQmJTC6rSSIbWYqvL8HXWgFPXJvitUWlSLJ8fKjpWL8y33qeKMegcP+ehK7HLwSOo5XjkC3K6936kNN2uahrs7DsncYXE3x1C8vcqWBap8qQLmH1mtysMFN3gKP2PPn8lHhssfncCEfGQCAAA="
}
}
|
codegen__primeintellect___2394
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nSince you are the best Wraith King, Nizhniy Magazin «Mir» at the centre of Vinnytsia is offering you a discount.\n\nYou are given an array a of length n and an integer c. \n\nThe value of some array b of length k is the sum of its elements except for the $\\lfloor \\frac{k}{c} \\rfloor$ smallest. For example, the value of the array [3, 1, 6, 5, 2] with c = 2 is 3 + 6 + 5 = 14.\n\nAmong all possible partitions of a into contiguous subarrays output the smallest possible sum of the values of these subarrays.\n\n\n-----Input-----\n\nThe first line contains integers n and c (1 ≤ n, c ≤ 100 000).\n\nThe second line contains n integers a_{i} (1 ≤ a_{i} ≤ 10^9) — elements of a.\n\n\n-----Output-----\n\nOutput a single integer — the smallest possible sum of values of these subarrays of some partition of a.\n\n\n-----Examples-----\nInput\n3 5\n1 2 3\n\nOutput\n6\n\nInput\n12 10\n1 1 10 10 10 10 10 10 9 10 10 10\n\nOutput\n92\n\nInput\n7 2\n2 3 6 4 5 7 1\n\nOutput\n17\n\nInput\n8 4\n1 3 4 5 5 3 4 1\n\nOutput\n23\n\n\n\n-----Note-----\n\nIn the first example any partition yields 6 as the sum.\n\nIn the second example one of the optimal partitions is [1, 1], [10, 10, 10, 10, 10, 10, 9, 10, 10, 10] with the values 2 and 90 respectively.\n\nIn the third example one of the optimal partitions is [2, 3], [6, 4, 5, 7], [1] with the values 3, 13 and 1 respectively.\n\nIn the fourth example one of the optimal partitions is [1], [3, 4, 5, 5, 3, 4], [1] with the values 1, 21 and 1 respectively.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIAEb8N2gC/+1ZzW7byB1/lYG6BxuWDc4MOeR4o0MPNRAUm22wixaFpDq0NJYGSw1VcphEaxjode99gB566yP0lkfZJ+nvP6RkxaGysXoKYHNEzcd//t9fgu8G89zntfGDy8GfKrsyL503RWFmfjAc3DZu5m3prl2+MgDAlnVz835wyXmqhoOysgvr8uJ6XZWrNaH4oSzeGuaXht2WRVG+s27BZuWcvgBzU5gVa2paEQh2FlW+WtG6yN2iyRfY3P",
"part_2": "hl6S4nbuJ+sG5m2KZsWF61SG9M7dlfqtz6Jfsjrg3ZK/vz0tkN+y5f5D9bxz785ztbffgvy324MDPO4255y/5sndv42ubM1ljfmorIBuRsbutZ2Th/QVT/2tFb2LfGsRyjqvINoICkMG4B0rQ9pyMLZS1MxWYXjK7+CIpv86IJBOtyZbq7N3t3fyL6xFrdrGjb+poZ6AWMYvJ+ZtYeuqsCyDeTSXFblFhNJrdVPrv76f5udo9FFXa/YfUqh61qf8Gu",
"part_3": "AGTe56t1YYbh7o4PWrRsjOWQ8SFTQ5YMmZiyd6TGGRsxQTxJdsYUPgk2eBxU8ftVCR2BBFuXdW1hPrbOK2/JJ0iJUAo0UMLCzttFUzY1pLoJxHDc+HXTWmHL5gOaTvgdo3W3qs0DhsDCxJ3T30sHXGG21fOtrYCwsM4E8rkFR5056s5AM3bC2a+//Ju5IeY04VHEoig6vdhiqQ0uzx+hcQ+I8us7e79F0y5aPH/Tpx/+9es//vlgO1LHPsvfB/l3PL",
"part_4": "dLaIzcHxrYuk6L5bNaOqihnZvtrPIJF39ofaLu+Ah6nDjJkonjsLt8YG3iFC06CC4gJMHgiR4PvZvuX9di737KsAJ+uFQMl0oZ3wfl6R5oxmIiJANgEr4/AhaylaeT6FXpzU6rL12bbIIzdP4P22/2NLKxppjX4CPfxd3F3tXOA7Z3S7cLmnLtLUyy7/IIkzEiiE+H+I4w6fno/WUXZHt+LoJr6ohVpl4jzSLLFJt9hvzSVk/hRwyZJH4Q1nGI7DRw",
"part_5": "9yllin4ZqPODxG/LpsKtJ2iDiMktaQyaH2AAmhP8EAMUjZYcAteQcG5gGY+6EcApS9fLsinmqBkIHNqo4PlFEyyMDATYknyFnlflOzrr6tC27BCeyvimagVFUTIXqGeVQSUwqDMoXrWvRoGFk9OLel1YfE+cw5Y/wdE4mmKJLL7b4LSRj8bTiXsd3lfhTdnbQhZWoaaZk2jozvgpFTSfX+TrtXHzk+iUlq8/Xl7tL+GlI0TXcoRQ8DTrZe4RKb5Ham",
"part_6": "ynO0bteWB14oH1bERHtPhdq8sTbIbDd0sLky9fjHxQ1uvxcvpiZM8hccA48cvR8oz3QBLCF0D7euyn0w7Wj/x5gMXkjH9LRyP7LW3YW3ZiXwDrKetgr4hXSiXoPJDe9nfxIgamZ4R9OQ18h4NV/v6EJsOrB+nwuCATiXR+NXbTU1g4KAvW9WgbHNadQzw3K8/NynOz8tysPDcrz83K19KsbJHUg8vx4M2bN235OdAbPDcuX3PjQr4BCw+mw4FHmoXF",
"part_7": "B+O7ycBv1mYyuGSTQXC4686VBkPsBCW3h5QytzkTmMJxW+LacxV274fsy1G2OfYLkmwfPWTbJxOkpPw4K/fhRnp+Mm7K4p+m8T7sQh6hqqRVPxSVMK6YiMPImIQkEYs1jQQ2SphSLJVU6XuJJ/ERshFZQpdkTKdMS5ZCRk0jVd0EQ/ZTVCo5gmLQXb/+ouPVxz7z9HuCOIpY0Bb52aGnn5rUx1Nrva7/6ad2lF2AjK7FKYuzLxoi6See8uNl1THLUp",
"part_8": "YKpgR5PPk9Z0kUKCICNcUGp/AWBwTX/4cLqTSkq4gmMu7eGORE25lK+4Mvyp5OWHfeFLEE2BMSG28MFZOoMu53pewIUttsCz1Cv1rR+/FQveRSzY/P/0giKTALeiO/pJ+MOOslmsXHRKfc+ZBOfmOk/cJyLo7JQXFX7VQQ9bMj4yztD9pMZ8fHjeRMHxr642V0IB2KY+yMYKHYoZKIQoUWQoUkSHOKFh0e1RZ9FBeqy211ZsgfXRuQhEu0iyKEd4Kr",
"part_9": "KtTZFiJs03HAowJ6OoUrY1MGgCwQpHsCT1ulu0odBbKqQxo4oYyqA4MEjZRDAR740LTXq6D4uLCLWPAozWMyQwwfUBn4SBUoZSlncaLArUojliUIQqXQwUhKPPg9EQukIJVlYLC9iQyUpAhhjd5Awtu0BP4UWJSOsBISWDS5P9ZwMyRQLVHTlUBVlzyD4iTQxApKVaj8CkZHjyHpPmZJjAYDfEK7QlPnESE+FTqOBIUe4RtDYSoSTGdwo0wAi5LIzr",
"part_10": "FCm6LBCkASiCbAqkwTQbEgBSUW5GyVIfyTJIUSIoRflhFXIJykMoPQxC76F8Z5OMxgWFxlWSzBswBSDjCZQhYRI7cI0oROkSkhdwRlAZPQgrI0MimAUThiuFHQlVAIOY0kC10gfcekV0GZB1lQJxx4BRKRSMESuIZkSYq9RBMwSEsdg74CRynuax0lKHxQIySmHg0HKqM0x7k60JbJJI6PdJ3fbG2+nqe/1e9+W0zpn8X1dePs3xszuPRVY+7/B5hEcEptHgAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/3VR2w6DIAz9labPexDk6q8Ms5ct25JFF4WHxfjvK+qAuJjTlFNyeqFMeB/60F0vfgj+gQ1ODp/dO/jRYQNnh4wDq5zrGBCqvdlESeLwBJQg10iAPATL6oXnuAa5NONQlxXlb4Ij/LWnAoco1NvrtAKtwfDorY5+Z8KkHLs1qEAKqCVoHj2ZotBCLRZlG6V98MUqLU81lEw0b04VY+WF2ESNKK7NOlA74wlH/3nd6O+GQMf8BfZ8kcDTAQAA"
}
}
|
codegen__primeintellect___2396
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nNowadays, most of the internet advertisements are not statically linked to a web page. Instead, what will be shown to the person opening a web page is determined within 100 milliseconds after the web page is opened. Usually, multiple companies compete for each ad slot on the web page in an auction. Each of them receives a request with details about the user, web page and ad slot and they have to respond within those 100 milliseconds with a bid they would pay for putting an advertisement on that ad slot. The company that suggests the highest bid wins the auction and gets to place its advertisement. If there are several companies tied for the highest bid, the winner gets picked at random.\n\nHowever, the company that won the auction does not have to pay the exact amount of its bid. In most of the cases, a second-price auction is used. This means that the amount paid by the company is equal to the maximum of all the other bids placed for this ad slot.\n\nLet's consider one such bidding. There are n companies competing for placing an ad. The i-th of these companies will bid an integer number of microdollars equiprobably randomly chosen from the range between L_{i} and R_{i}, inclusive. In the other words, the value of the i-th company bid can be any integer from the range [L_{i}, R_{i}] with the same probability. \n\nDetermine the expected value that the winner will have to pay in a second-price auction.\n\n\n-----Input-----\n\nThe first line of input contains an integer number n (2 ≤ n ≤ 5). n lines follow, the i-th of them containing two numbers L_{i} and R_{i} (1 ≤ L_{i} ≤ R_{i} ≤ 10000) describing the i-th company's bid preferences.\n\nThis problem doesn't have subproblems. You will get 8 points for the correct submission.\n\n\n-----Output-----\n\nOutput the answer with absolute or relative error no more than 1e - 9.\n\n\n-----Examples-----\nInput\n3\n4 7\n8 10\n5 5\n\nOutput\n5.7500000000\n\nInput\n3\n2 5\n3 4\n1 6\n\nOutput\n3.5000000000\n\n\n\n-----Note-----\n\nConsider the first example. The first company bids a random integer number of microdollars in range [4, 7]; the second company bids between 8 and 10, and the third company bids 5 microdollars. The second company will win regardless of the exact value it bids, however the price it will pay depends on the value of first company's bid. With probability 0.5 the first company will bid at most 5 microdollars, and the second-highest price of the whole auction will be 5. With probability 0.25 it will bid 6 microdollars, and with probability 0.25 it will bid 7 microdollars. Thus, the expected value the second company will have to pay is 0.5·5 + 0.25·6 + 0.25·7 = 5.75.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIAEb8N2gC/+1a3Y7buBV+FcI3mUk8qkiR+pkivWkXaIBgt9i2KIrxIJFtzoxQmdLqJ84g2Afoe/Qd9n4fpU/S7xxKsp3xZDfuXloIxhTF88NzvvPxEMin2Trv8tZ2s+vZX5piY9+4zpalXXWz+eyud6uuqNw7l28sFmCqcGv7cXYtZRrNZ1VT3BcuL9/VTbWpScVfq/KDFd2DFXdVWVbbwt2LVbWmH6xZlnYj+pbeaAlm7pt8s6H3Mnf3fX6PycfuoXLXC7dw31bbfJ0/tnOxqdpOVHcsVcDBxtlO5OsPtumK1m6s61qRN1a4qhNtl3fFKi/LR1EW7l92",
"part_2": "LbpK5GJrl6KGgUC8cW1n8/VcbB/yTmyLshRLK9qHautoKXtmm7ZyoqqtI+d20qJoxdrCATgNzduieyickGEoNtADX1aVW8OXOyxhTfuCpM6uA/H3tif3sK2+7Iq6tAjRps5dYVseQT/C1wibrx6wS9GW2BbcOdTnRI5/PScoEN/QWh+hjWjsyhYfoC3H8Ifeth17Sp7nRYnpZdV3rK5vbTPfKc3dejJIYyx5FA85pbSCqrbG7sZNI02tfbp1NpSLZTFIb6u+XEP7I2+p7ruOI+oO0+e3l3ej9UD87WEMy6P/0vb399hJy34/FPcPtC0yA5D5ySEY7Pm9pZWV",
"part_3": "qMt8hWARPvbtAQUcK2CGcNNafMvLvTx0BdJLHn9mbe6zUDiHBLORulgRyOBhA8PVJiDo/rnakkq/+mAb2yGRo7PrCtYIt2OYKVS0wH7MV4jHpuodY5/2AAcIvwf1sEL1okRy4TNwVTfFaqcesEOO1xRPDDc251jlPvuD8jpHFJePB75iMZCDkAwVsck/Fpt+Q0aBXZ6qKH7kUuujPMaraKcsUije2u4F4dq1xRrrK4dw9wArBIkXONNDGtyTQiCsMG5gYMKNB0dx1Y2Ib/cryBc0doS1xBX3MOr6zZJs3wGrq6Zag5vyhndYEC3lS5CFzx4GKwK2E3fgNN4n",
"part_4": "PqA0lrbbWky/ffep+JEh9j2N5rCxKsFpH5hZ9gKzrZp16wHwIS97O/EX+T2GmfxcwdEl1d7j5O9ntm/eelNs8daXGH1tQcvCb6Aoi+4xEBTwP438NMCoBpkjOd6JKfcDhDla+9AjXjkKJU7mwl3R88ahkHlEU5SNu6IBJEuySlil75Rz8A0A9zQTTlwo8d9//wcD+msuA4xIuh0OjvkuViOrDer49NhWg6b284SIC8kq/TSNvp9GIKswvAQNtqumWI7H0H5CXnCNIab2DqB0K9sGfocA9XiAUcW6F0PBtv1ymG8D8c+q9wEFMYhU1FVBB9PIIquqATETkS03",
"part_5": "Rdt+FtLv+m4/pv7VV6lrt5wpItZlW5U9zgfobGyJkw4+2KbBq6tACw1nGCeSFVci29f/zcd8g6OmHSxwBhcuWjgtkoVLEZuFM8LsbOM1SEw4PDS/k1G0MBJ64aSI90WiYJIIvfHB/LdVZ6fN/XEkg25CjvXu+dL2U3s1wicZ1+cvlTTgO9SMnovk9ve+ThjOhwrHek4ZOjKcjwceMVjz2WJzYMQ7+ZlSzvuWzNv7vFkj0u1Y8Z7Jff0VfIqAFx78CTE0QgUfUl4JVeHaoleA4eGwmAjkIDIvhgPhH4SMPRoQYWD2QnvgIRNj5w+Qw13tAjBU/3jqee+GvWwf",
"part_6": "qnJ3uozNkznqhDLTnshsfMTc9helkieh7wdWfcJsx3NyQG4txebnn4x4xZZ+/imeRol4LQjxwUhpnsSm/rBbF761eESVo1vktqYBHGmiEVyXFBOYwtqKqmFoYunb0BWPHEJ6Gtv1jRuoYW0DdNcT7aCVXts7Uau6vKjlvFbzOprXel6bS7TGAg9pCuHyhbyq5eVL+lH+J/I/2v+Yy916ifW1/NJaRGOx8ALjU6uXezZ+jUD08qlTXxTQL5/dxXEB8/IL2/Zrh+jKqwve+SuO1yVlxCEKSNsF5/fiEnMryVP8GrQ1gHjxQrwYP9zQ4pW8CW8v58NQ3l7ekqqV",
"part_7": "ek5QTYJqJ6gmweIO590fXotoyOYqekbR9NEri3bKokGZLVu7r+UmnIcHNvT4VX/Jhp5s6J0NfcSGPmbDjF/Nl2yYyYbZ2TBHbJh9G9SyvhY4Tugg/Tgx/IWc03kup4KgXKHtwTyaVZ+lq4+v5Dy8/N3wxkl8JS/HklCHEupAgt84e3sS0aFEdCDBb5yiPQl9KKEPJPiNA74nYQ4lzIEEv3H4dhIUoFevj5LFwjFFXWDJJfiFMwJu6Ro0Ungf6Oh8cT9f3M8X9/PF/XxxP1/czxf388X9fHE/X9zPF/evubiPStrZ9c3s/fv3vhleuPMl/nyJP1/iz5f43+wS",
"part_8": "T7EEv8xu57OOLlW4ut98Wsy6x9ouZtdiMWO6ezcQ2WyOGc6k/xgtfNsw9A2+cYBKXlf5VoAXHnQQtABN7NeZUayZWg3faxyzctB0fLUVw5rlIPxrR0+9iOM4CWTsHx1/vSOKDez+PjUhcVCdvlGvOZr+HtNvxic+NZDJXtIyxknKAImfAUhmojCWSmlzosVEZHholNFIHaQpZh8iLXjFEfthqIM4UYmJE3mqC1GSpCKTCRlUsUkE8s9bDyPMJ4pciqJMiUQZWq/TLBRpFsvjOMqiNNCxSpSWcOw0l5TMtIgzzdkIYyVSxWOtUylSHZGrURojLjrkCCWpFibL",
"part_9": "jmcpjhLUWJSFWJ1EJ9aYysJYxIojExvkKkwVB0ylIo1j5hSZZcIknCsVU1CNSY97hD0FMo2wQMb6RI/IizTiUlWavcg4hRFSaJKUPIoMzZs09GuMSDL5nEdJEkQySZM4TuWJ5YPwolISw2wXKtROElOQTEiZyggwUsJr4CvmrBngLjuOI4MvQQwgqCRKlTzRIewHWYhIPJIRStpkCVed0QRtXhNFiItU5LRWcSaSxBznryTUcaB0qNMIbp3K1akBhNOIiQxoFHHk3chCKbKIK0ajmgU2nrLbMdxO0uMEkMhUBVpDGDDKToW2gYk0zVJGCSKWZIrRg50KE/FY",
"part_10": "atQ/qpKDGsPr8Jn6N2CQQEVpGmoDCjjNoywBSOLE4yglHHEhqTCMxMDuSK1IUk9OMWUzVsdPBZMoGVBg0xgbTU8EEkoVBJPEnv8QFaZCqTGU7JsG56HsIvbTIHBx/EzxG5RGEBLrqgQ1fCppG6A2ZXFgF+MwpXkDngbV8TGiUlrix5ryl0XP5MxoQwQpU5mmp3M2QJtIhoVOYS6NmSG10ahBGfrjBcSpPDWFEROBeqYb0TjNQyqQTMfy5LZo+qu4J4mE7/30M41YGP6//cnO4rH+5DfQP7VyQ9twZBt4gnh8hmze0v9abd/1rviht7Prruntj/8DUpWMw/YqAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/41Sy04DMQz8FStnFMXvpL/CIi4gQEItancPqOq/46Sl23LCB2fk2OOxk2N62++W7cvzvF/m97RJxyl9bL+W+TClDTxOSadpi+DhCTpmaOEFangFCz+lBzjniVeHpow9DzlStfVKdBVoTiOHWcGRpGOyBu5KdywYHGEdtY5oKMASFshGfw6+dq3ioah3qpE3hOm9MG4Rat7lSm2grKOTBETto4hYzOfcMalUMBvxG1lXCf9F51r6c3uZbSUmNYZa22gtsUFv1CfiEjKUB0ahWFobS3MrYMVwkDx1lt0y375YjieIeyJZt+BFLJMEJWOjVZ2WItmcXM3xJl+za7nYGsRCubB7JTddpzAzz2hnk/VPcFi2X/OVx9Qzca1FlOQyyCk9pMP8/fkan3C/xHH6AXzgMaScAgAA"
}
}
|
codegen__primeintellect___2399
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nBerland National Library has recently been built in the capital of Berland. In addition, in the library you can take any of the collected works of Berland leaders, the library has a reading room.\n\nToday was the pilot launch of an automated reading room visitors' accounting system! The scanner of the system is installed at the entrance to the reading room. It records the events of the form \"reader entered room\", \"reader left room\". Every reader is assigned a registration number during the registration procedure at the library — it's a unique integer from 1 to 10^6. Thus, the system logs events of two forms: \"+ r_{i}\" — the reader with registration number r_{i} entered the room; \"- r_{i}\" — the reader with registration number r_{i} left the room. \n\nThe first launch of the system was a success, it functioned for some period of time, and, at the time of its launch and at the time of its shutdown, the reading room may already have visitors.\n\nSignificant funds of the budget of Berland have been spent on the design and installation of the system. Therefore, some of the citizens of the capital now demand to explain the need for this system and the benefits that its implementation will bring. Now, the developers of the system need to urgently come up with reasons for its existence.\n\nHelp the system developers to find the minimum possible capacity of the reading room (in visitors) using the log of the system available to you.\n\n\n-----Input-----\n\nThe first line contains a positive integer n (1 ≤ n ≤ 100) — the number of records in the system log. Next follow n events from the system journal in the order in which the were made. Each event was written on a single line and looks as \"+ r_{i}\" or \"- r_{i}\", where r_{i} is an integer from 1 to 10^6, the registration number of the visitor (that is, distinct visitors always have distinct registration numbers).\n\nIt is guaranteed that the log is not contradictory, that is, for every visitor the types of any of his two consecutive events are distinct. Before starting the system, and after stopping the room may possibly contain visitors.\n\n\n-----Output-----\n\nPrint a single integer — the minimum possible capacity of the reading room.\n\n\n-----Examples-----\nInput\n6\n+ 12001\n- 12001\n- 1\n- 1200\n+ 1\n+ 7\n\nOutput\n3\nInput\n2\n- 1\n- 2\n\nOutput\n2\nInput\n2\n+ 1\n- 1\n\nOutput\n1\n\n\n-----Note-----\n\nIn the first sample test, the system log will ensure that at some point in the reading room were visitors with registration numbers 1, 1200 and 12001. More people were not in the room at the same time based on the log. Therefore, the answer to the test is 3.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIAEb8N2gC/+1a3Y7jthl9FVY38WBsw5Ls2c0Uc1MgQAdotwWSuzid5Vi0za5EuqI0HnexQG97n0fIk+VJej7yk0zbk0V31kB74UlgWyR1vr/zHZJIPiaFbKRTTXKb/LXWlbo3jSpLtWiSYbJszaLR1jwYWSkswJA2hXpObtP07WyY2FqvtJHlw6a21YYgvrflkxLNWomlLUu71WYlFragL6x5LFUlWkdPtAQjq1pWFT2X0qxaucLgrllbczs3c/MHVWO4EO8kOSFL8Sf9WMt6",
"part_2": "J9bSiVotlGnKnXhUyojHVpeN0MbjLuRGN1hul4IhxuLeCFkUmoCG3bqS4Xa2xTsYkx+UkGZHL3oc6xOhCrG19QcX4YlSyULVbniAQ25JOCZ9vLW11ZjC+MEWcie2mPRB69I2CBepXRMi7Mq2sZUkO/G74kk73djafSPkYmFb09CM27lGVb8TPwDKwWmj6s7dMCW0Q3wO8ZcAlI2fQqZqaRaojPXPBz6K+4ayaesieKiesNx1qEtbV2Ke1D5gAlI1OYoX58lwP1GqZcOjY/Hdk0I6",
"part_3": "eAb+SOf0ypA7GFxpB2eoEMK01SNWFG3dUeJgGvxYKEyqLowu0b/+62ehm28o263R/2gVIm7UClBLEFGkFGY6+dvNGGlquUicndKuXBzh1voI3a1ALNeifvioP80Tb6FLFGC3ulm/6Lpf32fFv4Ec/J7ARq8E85nskMbCM4jqoGsX8yaKaet559rFQjlEqxvRNS58QnTC2QrEU7W2hX8VbT4E8Yphl1gaoRmNrLAJYvkLs27dNoXdmuEJj0QFlsuShqgVIAMdgX0XfA8G6KUGZb17",
"part_4": "RU+wx7ZYqSZuLv+yb2u3QWqFDe1aKGKRd4wJHrJ3kAwqOWqBqBGij7trZvT+P5XpzXYiYewWyBWhgjXqeVNKlgejOH3NGhzmXPt15LUyakkJadbIEv3Q1QbyBn+DV1tdluKRiD0W7+x2yCE8qdKiEu6ohN4W7Lf1KqjaglxvNx1ZpLNwnZwhU+oZ3FHoZ5/ZP6pyE2NFRoC41OwxZFZXbSU2Ft0IJaYMSGSll7uDYg6QhK5+V5Fmo3+OXJdPUpeSAGENUup9mpsR/d2bTdv4X0c0",
"part_5": "1obkFblCJcFd+ITyPO372IhBKn799y/4QZ/pZHLVtxF3C7zoVIsLtm9xpFw9N7wHAYMb3qtDtPLvtq1pX+H3gUV6hdqtNTqAhrbgEohdKIiaxJgH8g23rXWDGhA50XtIT6lCWH57sPYDyd6BpqB4kSoMYYXAQ9OTSJrfULHhqTLuU0BTXCcxCFyEBBRYqiEBfQnRmFu5c6G1+tkXMN2Vr9894QjsyNg2Gs/NdafBIACmDDYxKmANzixgYTcUvXWiqfJbQOeZV5HdRrmw43nKUVOR",
"part_6": "/ALFqUXry891kvXeyTFkgbpZoOPrpqNhKOAwqNQS6otpu9n020inR0z2XUe2Q01ilv6lbWKa4hiEGvdF7YrS0e+L+ig2892zJIlwbMj3xtzczM21SLPJJMWy6Ef35Kfp4w0BBVfnJu/fz/rVWbwgixdciw5zvyCNPHtnG9WHfx+aITSq8y6LRrnmeBsNCgdFpQ3a1x7/hp3GUgK5qQ5UxbdTz8nf2gidSIc+dl9en5Kx+DNxYKMsueNhiIGdDcJmfsJj3rEecawtus3Di0K0NdCY",
"part_7": "NA5I3ZmIYiRm5+NOqzQlkIWc+Ic4vEd0XnRr25YFjigUKgZoky1bHwTwsNZSkukfiD/N8bG4OwUTTq0a6A8fNSExOF7DPbgIZcdZulBLcFibwRVOwwJ/RtwRGwfer8HVVRgNn7VyLU7Ad2ISngv8xKl+wIv8zkHpQj+v1MB0kPSHykqP7FHHblPq/j36k2xWRmMaVBd3d6Rv8yTC8qbHOGkfrD5wsJLPg/AwxFnHDIqraKUqnTqCgylJnhdH48FUrSr7pE6svYATOXF9R72wT56v",
"part_8": "Ijt1kNW5CQVAZXxaUBVQVRs8cyEvd57Lnedy57nceS53nsud53Lnudx5Lneey53ncuf5ojtPB+KS2x+T9+/fh9Pw3FzuP/839x+qKSqT/DRMiDKoVPLjx3lC8obwkQVPlAemgD8j+3SGyZv5vt/3DR+6s2/50LGh6WHOY9jQtx4knyefhuK/N5pFBrIXEbNXIF6LveOniOkXIs6OEK9FsJH7kelZ8pAf5WHk0b8edxpVLIsiyM+S65vPoI84S9OzWMpPLOVnznuHm52FM9Ojeoac",
"part_9": "nCsbaZ+Nr/f0nJ0SZ/OcuOnkqPxxOq9FaNCbXpauxVv/+W14a/KyD5NXycCstzviz/341xd2xoF6pR3x9+X5f/t8Jv6OPCtHzNm3e24G6o4i0nZ7wJvPaMbsS/fFSSTNsUDHm9nspIHziO9p1IV5NDuLXI57NO0xT92fvq4z4obPj1R7FO3Ih7NxEFm0JjtJSZyAaRTc7GjHH53scS/5E3sbY2ZH6T+0Hic7Tu3sKPYurvTEenoWxjBrsxePP4fsSU+2u/Ssevh64ccX05b94pzx",
"part_10": "wYhrwweZgJFybwYU7puMfeCoOdtczoCSBZQsoGQBJQsoOXcf14pDCSg504crG1DygJIHlDygTLkJmEtMPs5IQJnyBhVQpqwgAWUaUGYvi9ps8prinB5a431xxNL2JtK/b1law1d3twhffIDgDuBmDBBpwEgDSMoyyRRlH5iY3Jrc79xCASULKFlAyQJKHlByVjwOhVuMuz2g5AElDyh5QMkDyjSgTAPKlBWAM8IHBm7wgDINKFPeFgLK54rzE/2ffe4h/IeF5LapW/XpP9iAPiUaKAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/+2UTU4DMQxGrzLyliIldoafXoVU3RQBEpqiabJAVe/OkOdpOyzYsmHjxI79lORzcpSXcV+H3baMtbzKWo5Z3oaPWg5Z1t1Tlj7n4abDpsneur3Es6y6LHfNj81qy2Buba7nerL7QHoIpIZ//+99pLmIh2xE0y/ykmFXUf1RPct9XqSQjpi7iw66b/ah2UffJAPVkfJIffR9QYjehDAikAhFoajvAYpCUSgKRaEoFIWiUAyK+eH9KFAMikExKAbFoBiUBCVBSf44/EagJH9xUBKUBCVB6cPi7pfqoMvme3Ffy9V71lnlNsSFtwxOfIfL5iQrOZTP9+fphxjrNJy+AK2UUVo5BAAA"
}
}
|
codegen__primeintellect___2401
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVus the Cossack has $n$ real numbers $a_i$. It is known that the sum of all numbers is equal to $0$. He wants to choose a sequence $b$ the size of which is $n$ such that the sum of all numbers is $0$ and each $b_i$ is either $\\lfloor a_i \\rfloor$ or $\\lceil a_i \\rceil$. In other words, $b_i$ equals $a_i$ rounded up or down. It is not necessary to round to the nearest integer.\n\nFor example, if $a = [4.58413, 1.22491, -2.10517, -3.70387]$, then $b$ can be equal, for example, to $[4, 2, -2, -4]$. \n\nNote that if $a_i$ is an integer, then there is no difference between $\\lfloor a_i \\rfloor$ and $\\lceil a_i \\rceil$, $b_i$ will always be equal to $a_i$.\n\nHelp Vus the Cossack find such sequence!\n\n\n-----Input-----\n\nThe first line contains one integer $n$ ($1 \\leq n \\leq 10^5$) — the number of numbers.\n\nEach of the next $n$ lines contains one real number $a_i$ ($|a_i| < 10^5$). It is guaranteed that each $a_i$ has exactly $5$ digits after the decimal point. It is guaranteed that the sum of all the numbers is equal to $0$.\n\n\n-----Output-----\n\nIn each of the next $n$ lines, print one integer $b_i$. For each $i$, $|a_i-b_i|<1$ must be met.\n\nIf there are multiple answers, print any.\n\n\n-----Examples-----\nInput\n4\n4.58413\n1.22491\n-2.10517\n-3.70387\n\nOutput\n4\n2\n-2\n-4\n\nInput\n5\n-6.32509\n3.30066\n-0.93878\n2.00000\n1.96321\n\nOutput\n-6\n3\n-1\n2\n2\n\n\n\n-----Note-----\n\nThe first example is explained in the legend.\n\nIn the second example, we can round the first and fifth numbers up, and the second and third numbers down. We can round the fourth number neither up, nor down.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAEb8N2gC/+1a3W7juBV+Fa7hiwSwBZESSTHYuSq22LlpC7RoL+I0o9h0IoxMefRTT3ZngT5EH6DP0kfpk/T8ULYzcWYaX8eYwBTF8/9959DA/DpZlX3Z+X5yNflTW238+9D7uvbLfjKbrIew7Ksm3IZy4+EAbFVh5T9PrqQszGzStNV9Fcr6dts2my2q+HNT/8OL/sGLdVPXza4K92LZrPALztzVfiOGDp/wCOzct+Vmg891Ge6H8h42H/uHJlwtwiL8dejo3O+ariuXH8VD2YlpmIrWl7UIw+bOt7BR3lbTRL",
"part_2": "zvRdWJj6HZBZApexLsho1o1qKsD8fhkP80gHzfiGkKgj97sStD3+HG8qFpOi9K0cEZH5ZeTO+mrKn6xaOq3UO1fEAl6Ec3wPo7xsCGKMNK+BLOTu/AV3KhAolWTBeLel03TSsgCLFYtPQwFQ2/WvqqHt/gGsMMoiHRXdOuulnUSBHFVIi2GaBGKzFsUc8KEjJmJzS9CH7pIZvtI8ZLR3GB/gdftr6DgwCAe98mWIHfgwb/udxsaz8T1RosiHfiOk90kctsJmSiVO7kTMxVIlMtLayyxKZZYW+mM9QaKIPLMog7z27O",
"part_3": "ABlHSrEM1/lMKFQCf/kNRImm/9D0npNLdmPiQFH0L6rHZHgOTqyq9RqesG53vt95tP5ChrEkJ1M8pnRXQR3Lelc+dnvXyVmCGzr4s6+34muIroEfjIsRQj/g2UWY4+d92A49rXDrL8iSqoWU11XwQJPQl1XoRAMPMUiC2cVUgnu1/yRC/Jbp3/X08j///u8//8WlI7wh+iLyyMGfEHKwx8X93JMyNNU9tXVEp5joi+kX+P4ifoyWRgABQ1vgigd0UWUY1CSC3ISiLvv6UUz1FGpxXwGpynUPWtGDlV9WGzC0bSC2lx",
"part_4": "R+xaNDbM+Je5TWPw79cV6BI/7F0GfQdcCBp0m+oxZCYKeIKoQBpmAOb778KKdiM0CZAAcb35Pl9+uIPOAMvKz7CtAMqOp24OtoowyPx27+xJjvoqMEhkXI4R/zaREin+B85BOsIp9QC8dJIgrPwF/OAdO2hmeTZEqnbhGyJEtTY2ArTRzIFyCTpPhBM85kSh6rnMNJcGAuSbVir6PfyMQToI0UpsJ83tYAJ6hiRYwUNeQ1rJJYDaqqB8ytDrzfeeoKsQPtlSIv19W6f9jXfdjOaPdICT9W7Wp/iLvc357pbIZ2rwqA",
"part_5": "wF0XNYaxNY4xVZhDZj2UuethZJGdx2YQ3UMz1KtYVNhoRdfUAw5GBCOcbTCF3LR2+C6OwHHioZ7W90PLqYB56BMYpa2P3Qrm5hoGqNiU4Gy12TZtL6hPzQT2pEUI0HXB9gU5eXF5uQhl22InvlkE7KYV5h2IdO8vwiWMTgEfOJGU2y2U4QJ0lQdhkP6IsmThoroUew0gAgpXvu6xzc+BiBcfL1+2AH0ZnQKp6+rmUvzwTvCS4iUt8SB+WOv8nZCHPUroBYY4Krnkl77u/NXX59jf8SDkr9vWFd45+hawB88x3W+3kL",
"part_6": "dbyNst5O0W8nYLebuFvN1CvnsLGZV0k6vryYcPH3jywdR/u5G87kayCJC9yc1s0sP8gmxOrn9dTPrHrV9MrsRiQsW8jWWazGCHwueX+eLAvwMBjxh4REGoMIk3TBqS1wukCx5aEB3xzG8z8f87gAr2tD3w9oi4B+YeqHvKlTlKoQdzGZ2Sr3cHxVIyJ9mHcfncnhxNvdJEtjeRkgZacvbH1XNj6WjsDIPyicHTus+IIT8KQh18n8sicfA5jZc8HqeD7vWGCRn6YNjtl+4YJM6qCJwsk5xwZ5x2p4FDGMR3LgKHJM5I",
"part_7": "dPbUJYBPlkU+5YkrdK5GamWpZmoVMpc5HyhSXTytFQTqZEHJTgrjMklxOutMTlyRzpDE3MLBXJknaTgRqItxEVHnT3lL9iKDXMzBvIgPr0xEQR4f0JHYPNWaM6IkE9gl1uZK8/tD6WRaOMM9wTnJiFLYCSh3JwA1RpJGV+cj8+d2jO+cMh65D54YNl8keWoozZDxXMkC3+NrJTmtiVWpJAcSkxqqfIYYUNmTNgYqJdTdxmXuMsvvTZ4VJPNyESlgMwaLcnYsoYxlU/vo7RGgz6ghMC1TjpzHLBSGpsABnyoxuZUuIt",
"part_8": "DonAiUFErHMBRglTxLEyOhtN/gn4k1zL72W57DRM48DAtagfOAQJUzPXVqCs2OZtYw41SRMzlNkuZpxilN8sJaxmqhuEYHeqVHq8LwzPpGteYjp+R+R8cijqw8J07FXWJfj+crCFg6rgfOGmgnmnJjlEvRDZtoV2RP6wqhS8ezNz2l0mLbcuqbNwI1Bk1jC/NQjN1Hx4UaW8xro85jV3GMOOga0PA5LGuz7DBMYxdOlaSOqRMNBCZAJrnOsnjPUGnGcwkmV+ZM7EmFtBEmDnJBbTExLlUuMt2qbORymqkXoD1mYqQn",
"part_9": "NYy4l+4zNJLWjdmZ29dnJfo1hg0DRxcZ5T1xMIQcx1pAWJR3CdyWqdMEAehfVkcaR3mQUoWKmS4AQPp0hHmcG/vZIvXYk2ws+jlNmFs55BipaflikcNkB+AxlCG+HBoSFh1uHKPXxmrwWxMEcJ1bFoapA8TOaV9l1BmoG1kDIzi1LwwXciCa5i82R8oNm2DlrJYVntdrtTWHMZjCdNSOcW7zIpFaOtJu0ySHmc83BvQ9c3yTkCnOFEVXBFkADIDnPACVAoBbfbo/aQpD8viylFpueaid9VrWyLqy8274BmIotOEW69",
"part_10": "ShlVjYLwxxV8M61ypaKrAFaX366m2I9qgIVTgSZiJFlL6+icrCQEu0mkCkYLoXyjBPUihF6rgt4j1XGkoJYAOZr3hWZNlR98xSOOZSOqathIFjyVNHEgVVEiQ0zMScLzsaHqzhPACBZAKBmNOEkzSDjWIWjG5Fh6Ir0Qk2z4b5TTRm2Iw68+ca8CvJHPMAKHUgH6QQWg76lzmYmVm8nZoc4lZWvnArBXWsiAhFvyy4seb2TAdTSPk4m7+1msvv/CySR6N5fubPyZPenDYXbwA3+N8dutshVJ8GP7nq28H/9j/Os0/iLyEAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2402
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nChouti is working on a strange math problem.\n\nThere was a sequence of $n$ positive integers $x_1, x_2, \\ldots, x_n$, where $n$ is even. The sequence was very special, namely for every integer $t$ from $1$ to $n$, $x_1+x_2+...+x_t$ is a square of some integer number (that is, a perfect square).\n\nSomehow, the numbers with odd indexes turned to be missing, so he is only aware of numbers on even positions, i.e. $x_2, x_4, x_6, \\ldots, x_n$. The task for him is to restore the original sequence. Again, it's your turn to help him.\n\nThe problem setter might make mistakes, so there can be no possible sequence at all. If there are several possible sequences, you can output any.\n\n\n-----Input-----\n\nThe first line contains an even number $n$ ($2 \\le n \\le 10^5$).\n\nThe second line contains $\\frac{n}{2}$ positive integers $x_2, x_4, \\ldots, x_n$ ($1 \\le x_i \\le 2 \\cdot 10^5$).\n\n\n-----Output-----\n\nIf there are no possible sequence, print \"No\".\n\nOtherwise, print \"Yes\" and then $n$ positive integers $x_1, x_2, \\ldots, x_n$ ($1 \\le x_i \\le 10^{13}$), where $x_2, x_4, \\ldots, x_n$ should be same as in input data. If there are multiple answers, print any.\n\nNote, that the limit for $x_i$ is larger than for input data. It can be proved that in case there is an answer, there must be a possible sequence satisfying $1 \\le x_i \\le 10^{13}$.\n\n\n-----Examples-----\nInput\n6\n5 11 44\n\nOutput\nYes\n4 5 16 11 64 44\n\nInput\n2\n9900\n\nOutput\nYes\n100 9900\n\nInput\n6\n314 1592 6535\n\nOutput\nNo\n\n\n\n-----Note-----\n\nIn the first example $x_1=4$ $x_1+x_2=9$ $x_1+x_2+x_3=25$ $x_1+x_2+x_3+x_4=36$ $x_1+x_2+x_3+x_4+x_5=100$ $x_1+x_2+x_3+x_4+x_5+x_6=144$ All these numbers are perfect squares.\n\nIn the second example, $x_1=100$, $x_1+x_2=10000$. They are all perfect squares. There're other answers possible. For example, $x_1=22500$ is another answer.\n\nIn the third example, it is possible to show, that no such sequence exists.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIAEb8N2gC/+1abW/byBH+KwNBgK1GJ3D5vsapwKFogXzJFbh+6YU5h7ZWFhtqqeNSkQzD/73PDElJdmRdlRooUFiIRO7u7MwzM8/MroE8DGZ5kzvTDK4Gf6+LpXlvG1OW5rYZjAfztb1tispe23xpIICpws7MdnCllPbGg6ou7gqbl9erulquWMUvVfnVULMwNK/KstoU9o5uqxk/IHNTmiWtHY9YBDN3db5c8rjM7d06v8PkfbOo7FVmM/uXRbVuCiocbar6C0tVlnJyTQ1hQ8u",
"part_2": "8WfRaJyz/j4WpDW1yx0Lm97Wxt4aqOQ3tkFaVK5oC2Ar4d2dqR8PttRrT9tofU5aVs6pxPLLDMW1ED++CafPV2AlB9V4lW/hq6ntyK3Nb5OWYOD7lPXyuWR4rnRUaNkOaIzg0VENqKlY6FsvvYPjdZDLBsxE7gPz7Oq8FsKuWO6Bk18sbPC6bRd5AcAzJlannyFC3YyTO/4I9i2ozlsi2exC3AiGqZjOStBlHzbq2ZsZIbhDAwnEuxrBH2AQQlYUX+aaD0WtB1DkKXQwrCwzFxEzYD5",
"part_3": "9jFvJP/CyMbcxArS8SlkWxZAMwXBvXVHVLkp5Au9hO6Ke7vLAw0Fw4uq/WtUDmfQtTrlhNn+odoUDeBgFaFneLBqT4Io41eDrxrJFs3uaWXbYVe+EKbNznE3HNy3JC7+edMPvvOJFA9o04tAKXKAQ9V2tstvcCKrM/8Oe9xaS89UjnRe0aKgsLHJVt4CDy3QW1Sy+z7XLocwyBsn0o77doONr56ww2z56pGWbZvM5vH+zjg//4As37JD3JD6yp1sz2umhf2PotJA4Ndz79LJ7unHoSq",
"part_4": "WMxHSM7gEDZ4EOVDUTTz7xjU7iDtX8alw0QiRlrs2fW6REHgPtBBY/D0a6GX3LeobWUM2aEQ+kSCrqw+MfZ5H74jAvLddkUKxjIrdsAU+9Bn/gPVWO48EAkZnVZLItGWA/7hVR3mddcyxCxsvDEVNOzE4z+ytUplW4x60yHohDCtObH3dxyDVJhV36E0i5vCje/5575YpQO8/vXbb6Eg67LsFA4s3FmI1KKwlASKBzILGfNhoSVmBfjsFvvNvmZ1drzvtmhPI/6hb3+QIWkIu1THAXR",
"part_5": "4R7wxh4A5BDv6WfbI0bKyrTQiYQp03BIuwY71QcDfIOpHz2bwTecBvGRWXyjKUC/sIRvPFUhm/upLBmP2/ddJs3TJu0mB8C7Su6QtweCmNqfDTzEhHTRe9GHFvWNTpIj74LbNXOi5+eOEBP6Gx9JT+z4fsROCaMOdx0CbBZFfYCv4INnzzI0Y9cdNSAqyt+tbxd77pkt2q/bta2W6psC8LncGlwGpOS5iXZl2FaTdHtXlWs+Y8RIM6uYCm2JbXitu1z0rZ/11KY9IRbcFWdmgktKbeY",
"part_6": "IC7DgRvIrTUliKcSzGMHWpYC6HI0yu91iqgTiy2W+wnwzpm5x4lZlwUKjFsLMzFGS5eUIlxOwjcOGrR8/dSO2077e7F9ZwmtfS7ef5haw5RLfbjtl/NksCkT3hn6c0q8H0/wpcCmgH2n7bLo18W6KTX9C+37X6z/83PD6s3lTisI/v6DwhynceVFhKRZPCORHLTpzxBZiOMlXK2Nnl6UbnVzfjo5COdv3Plk3xzzfZeuJltrkX/bTR1xpOdjOdXwE8pY2LU2EOJlF2DHudgvtLy/QHS",
"part_7": "9GT2boYvKvqrDCSNx2x7xHaHhguhP9UF2MwHihKtiOq3FhMe4K5O1G/nYjf7uRv93I327kbzfytxv52438f3Yj75W4wdXHwefPn9s7RWbfbudvt/P/89s5WwHjB5/GgwYXLVTA4ONDNmjuVyYbXOHMlQK87kprgHNxIBRvF+Ns3/GhSZbbS067zo38297Pko9j+s/N+Fl3RrxsY3danK2cfXh6qhyzguPlbM2K0YQh+QH0kkooTF9Ztw4IoMM0Ij/24UHyavo5SwFAR6diTiwR9EJn6",
"part_8": "/cTivQJ/ZogkXpRL3W2gfhFB74nJEwUHzT2KPFeVakGdQPy01dVmipKIkqTU/kDNyGm+AnZ0NvJn20tCbi24/jVXOCSV6+mLeKEBZRwD1IgheaaBLkCoXCgKQwoBBsVRcw2iuFOQomEMNGUBggMaUU6QpM5XRHodRAVQ4HYSsScEosRG/W12A3EdCLWlQCIGEOoBUYgSBIBowRPxJBiLagCAZYINiXwOHWUagEZCM6kh3p+X/E98j35tj/d78n+G0OGuCHxzhQgZXcQs8+iIkzDp4rO",
"part_9": "wpUyIXx0afS7VKMKozhFJL1E9FISJuxywoeR8hBvrRFX3+fpMNKIaBhHkQ88KUc0ThAt5cUBcpFGPpKlw1DadIwEqTAJA5gIAx/Cyk9jjUegfURcxQkWkdUUuxkNJgDGU8inwmbkWiWJ8njkJYHP+9gkenPggRNJHHPJae1rpiJ0Y3vqx0omY96gdcR9VeM4ax8R0xWfVyuHXTBhANd7djFpgwkHkjaYSYjY6IDLIErY/TTlMsEAR7gHAXjOvMV+rp2YyyfwMJPCJ9VFEkFF6HeBjBS",
"part_10": "YqxMtrsdsT/mB4jgGgRZBnL8cYw9x3cVRpVHI1RQFvBaFDFEloaRBx17MylSC7KnU81gEMtz5Y9/X7BvCmvZxhKGXePy9XQqKtTpRGX4IyzDqc+/oRc/vhX9kJkUeEknmd1rh4wc0E6q1fGO86cl2F4RRzLLEb0xl2YxBEgRxN2Rl4HWKYyY50Hh+V5ISkTKRn+73dOzlcprCpmzVqZd6utWAOQzaUTuUcTfxX6QpOHlC8Dosx56g72UfP/F/XnHXa1vgj+LBVVOvzeO/Ab7StDv9IgAA"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2405
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA multi-subject competition is coming! The competition has $m$ different subjects participants can choose from. That's why Alex (the coach) should form a competition delegation among his students. \n\nHe has $n$ candidates. For the $i$-th person he knows subject $s_i$ the candidate specializes in and $r_i$ — a skill level in his specialization (this level can be negative!). \n\nThe rules of the competition require each delegation to choose some subset of subjects they will participate in. The only restriction is that the number of students from the team participating in each of the chosen subjects should be the same.\n\nAlex decided that each candidate would participate only in the subject he specializes in. Now Alex wonders whom he has to choose to maximize the total sum of skill levels of all delegates, or just skip the competition this year if every valid non-empty delegation has negative sum.\n\n(Of course, Alex doesn't have any spare money so each delegate he chooses must participate in the competition).\n\n\n-----Input-----\n\nThe first line contains two integers $n$ and $m$ ($1 \\le n \\le 10^5$, $1 \\le m \\le 10^5$) — the number of candidates and the number of subjects.\n\nThe next $n$ lines contains two integers per line: $s_i$ and $r_i$ ($1 \\le s_i \\le m$, $-10^4 \\le r_i \\le 10^4$) — the subject of specialization and the skill level of the $i$-th candidate.\n\n\n-----Output-----\n\nPrint the single integer — the maximum total sum of skills of delegates who form a valid delegation (according to rules above) or $0$ if every valid non-empty delegation has negative sum.\n\n\n-----Examples-----\nInput\n6 3\n2 6\n3 6\n2 5\n3 5\n1 9\n3 1\n\nOutput\n22\n\nInput\n5 3\n2 6\n3 6\n2 5\n3 5\n1 11\n\nOutput\n23\n\nInput\n5 2\n1 -1\n1 -5\n2 -1\n2 -1\n1 -10\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn the first example it's optimal to choose candidates $1$, $2$, $3$, $4$, so two of them specialize in the $2$-nd subject and other two in the $3$-rd. The total sum is $6 + 6 + 5 + 5 = 22$.\n\nIn the second example it's optimal to choose candidates $1$, $2$ and $5$. One person in each subject and the total sum is $6 + 6 + 11 = 23$.\n\nIn the third example it's impossible to obtain a non-negative sum.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.0625
| 0.375
|
{
"part_1": "H4sIAEb8N2gC/+1a3W7juBV+FY5hYG2sbViS5TgGUmAvWnRudgq0d3HqUSwm5o5EekUpsbsYoA/RJ+yT9PyQEp3Y7Y67aG/sQSjpkDznO/8kML/08qzOrKx7y96fKlXKj7qWRSE3dW/Ue2r0plZGr3VWSlgAJKVzue8tozhORz1TqWels2K9q0y5QxZ/NsWLFPVWiidTFOZV6WexMTk+YM1jIUvRWPzCJUB5rrKyxO8i089N9gzEQ701ernSK/2DKJuiVmPbPP4",
"part_2": "EgIBRuZO1QkRCWfyEnR/EX4BVOLXNrOiXfZGrpydZSV0Lx8CKXVbVaqN2mYaPTabFZmuMBbCAfwKMsvo7K163B/FDIfdiUBPnbLMdCrs1TZGDVlUpsiNxuSzkc0avWWlAlS1gs3WTg2Q7EajIHyWD0n0UmiswuYSpP5iK7NBX/XG9FTtZWYQvxRdtXq1HLfp2rfq0sN0s7E5uVFaov0krFAjWuehXuOyff/8H4LNfVFGIQr7IAqcJkd/BUEE3IPIKNMSjFJrUeJ",
"part_3": "Efhowa7Vo1BUgwTyw+0LqSPzeqkkKCdUIT1Mbb1JpSog4QW8ig9QFwOohXxNd6AxRSekKONLo4AHNbV2rjHV2DXwiAbspHWRE3Z1/yHM3VMisDjhhToDnB8/C3AEt3QJxLHzleLYT4hKIOXZ+DsXKZs2hi0tn+lbaF4Ak0SCM+zmvbt06aiB/NKwfWq4EsqjDSAPyWg6MzHLyV2V6VsI81M3VWAN+SFO88S37J4MuZX9qRgIj6qbE1Ltu98xm5/CCzSqgnARyqg",
"part_4": "3gBeLnQRo8lJPAh9CSC8iGB0sk4g09PwLKprByxKrmRVn8H6mawKtMHUDqDsIBEAC9bcxQfUrAXQEkLqQ0wjyPgLeAhiVzpMf4+6l1T05uPzSdVAYtCadyk60xpsOKrAUa1fEbzYr5RZkAxGPQjsVoVEEP8iKZ/Tfsj4allQB1SEh3HW5e2xPFNMLqImnhkWu5rko7g7Bl0kO40v3QJ3uVwixXoDh5CHQO6GX9XfgJJAWAffAjqON896rAyuLxw5adVMbT6p6YO",
"part_5": "zQ4dQnMqYhEvpNemBUCBC5H6PmYpWttIxdD3xZRjMIi8QbbZmIqaBuQCl6Ds0bzIIcZ3f9q/PH6dWr/fZ+UO2DrFKLZWei6SlY7FfKUTHGKR4hsMkbjFtwj3s0VgNsYvtzM9vzM63pUc7YpxxTiiMcV9+B57SjQNt04Zv9PgR1PL1i0fOXU4ISTrJhT2MrOrVQme6KpLEMn9CMMqxiHBYQYDpCxGKYdGGZQwn5+wfgyx5CMN48oAvXLBzWuS/rjKuaB3kQDFpz8",
"part_6": "X3wv8S+nvTsRxfxJoYCXkSn6BCpw9aX8iPkE5cJ3U1/8Qa30WUhQhnuQID1TM6g0cVe6MtQqOMojIPGJmQxBjCL6LNtRfoa+530GnsXXu2vXBNL4D7SirgFCB+YvG91FYa9Dx+A9bh23PVv4ohXwqWTeVL525nMAZrZJ07tngkQ2q1No3yxHWrPUmg953J+5B5mA/xCQUezQVAR0MJ3ZXKHg+oFi/9v6B1q1xXQUnNTnwnHjdiUkvdAhHOQE/WLxW+X7kKtCvAh",
"part_7": "DsE+M7zD9HsfeO/DDJdjup8wFxHXosMIsccWUnfmJNVQ++yMNdkZWPeQZSl2K8p02AtFKSdH04zwTPGGuLyXAnpiHJqeRouJlJvN3tPubwfavPGzYwQS/dpAPnVR20TEZi3G0choqwrkR5hMNUiJCiPyRsmqryWkWsOnKhE41j5zRgmRDm7XZa6CYdadzOo3ScgWpN7D/ciVZWYJMjgNBABgHCUTA77LaEkPERGPKtdh0Eov1OTJenV3d2f2Ozfw9ppSl9BwERU",
"part_8": "pBiGNKvrqA8wLfL2OsN6XpDut6Qrjek6w3pekO63pCuN6TrDen/c0PyTGxved/7/PkzH6mQzfW+dL0vXe9L/9v7EhIhCXsPox5UrBqSsnf/y6pXH3Zy1VuKVY9qwtple28EFIp9nsSexK2Fews3F+4u3Ji4M4EU2mq4W9BeaFFI/joSv15e+h/kRWdEJZeIileu/7kG6Hpf++AeeEre9NvFzZ24eSht3o5AumHJNyclRhdoCOaa4g/Z0wt/n+bfznyriM6Iv4md",
"part_9": "ZmLGnibYZLTWK6eFRPEl3kiOpEyZPz/oKyEcydkQmE8vl8rjeOakTYNnIpKj52lPfbvohQu/9OQYt+H//nEi2/4L1ech/0VLStjFiTijc/rtEm/JgTPS2wdVHFA6eTxGbv3sNILZJTZnD7OM26CMTQP1xxziLPxMHsXzC1JzQSJvBBaU1OVp3FIWJH5B7zNHQRfdEsQZzc4ZnHssCPYtjbzjhlY5352z3PyC9OSayM2AxxN8LzBJSiZhFXyrCSv+nB+3Xu8pjXH",
"part_10": "np6OCdONpUWekmB/v4d5cAPdWdDIBQHLUr+I2tlps46RDEPv64ojTkFP0bldXjlqNHOm3USV15ZRjfhG8zwPKTTtygPEsv8eOPm/HxK053TEXF9SMiEGlzvHRim/JbWam3nQR5UPUrorFkTs6Unqmad1eUkIjhpXSSLpPneHS1qCLM+ZIpheVkHlrgsRVTB9WUZtDMw4h72JXyeK2pqa8J30TdzPOmiQ0b7DuRBVk8tcH/K9Sdt1o9XMje8u6auTXfwF/MgN6ayUAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/11Sy27DIBD8lRXnWILlYZxfKVUuqdpKlVM59qGK8u/FsxhoL7PL7MyyPB7qfblt8/WyLtv6oc7qkdTn/L2t96TO9JKUiTSlNI80ZvRkMhriykSKwD13hbEZJ/Jg9mqggVuIpFHX1TFCZWkwoFzGpE6UVEArU3DYC0ysdRct2T9RjBOaOMwpDU3JBQ0cuqIp+v9bMwVoAnKP3EM/ITednsEHGdVXMx/UiAWCWPLNBtwp1172OCSuwmMGR4PFwkEggw5cp/bi8eIxfSmI1R3tOl0Z4ega4YldHjpmrCgPJlXJufChoi2adlIuB7UVk3rdC7dt7b5a4DaY7l7TtGfhTmIb204UfXsS2eepTuq+/ny95c+9bDk8fwFo77em9AIAAA=="
}
}
|
codegen__primeintellect___2424
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nPeople do many crazy things to stand out in a crowd. Some of them dance, some learn by heart rules of Russian language, some try to become an outstanding competitive programmers, while others collect funny math objects.\n\nAlis is among these collectors. Right now she wants to get one of k-special tables. In case you forget, the table n × n is called k-special if the following three conditions are satisfied: every integer from 1 to n^2 appears in the table exactly once; in each row numbers are situated in increasing order; the sum of numbers in the k-th column is maximum possible. \n\nYour goal is to help Alice and find at least one k-special table of size n × n. Both rows and columns are numbered from 1 to n, with rows numbered from top to bottom and columns numbered from left to right.\n\n\n-----Input-----\n\nThe first line of the input contains two integers n and k (1 ≤ n ≤ 500, 1 ≤ k ≤ n) — the size of the table Alice is looking for and the column that should have maximum possible sum.\n\n\n-----Output-----\n\nFirst print the sum of the integers in the k-th column of the required table.\n\nNext n lines should contain the description of the table itself: first line should contains n elements of the first row, second line should contain n elements of the second row and so on.\n\nIf there are multiple suitable table, you are allowed to print any.\n\n\n-----Examples-----\nInput\n4 1\n\nOutput\n28\n1 2 3 4\n5 6 7 8\n9 10 11 12\n13 14 15 16\n\nInput\n5 3\n\nOutput\n85\n5 6 17 18 19\n9 10 23 24 25\n7 8 20 21 22\n3 4 14 15 16\n1 2 11 12 13\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAEb8N2gC/+1ZwW7bRhD9lQEvsVHZECnJtlz40AIt4EsbNL0UluusxZW0MbnLcJexlSBAr70X6LWHfkn7J/mSvtklRUqRgETupaiFQBZ3Z2fevHkzSyDvolQ4YaWLzqPnpcrlpXYyy+TURb1oVumpU0bfaJFLGGBJ6VQ+ROdxkpz2IlOqudIiuylKkxfs4oXJ3khyC0kzk2XmXuk5TU3Kf2Bzm8mcKstPbI",
"part_2": "KVeSnynJ8zoeeVmGNx6RZGn0/0RD+XpsgkpYZyoZc0LcXbJQ7C3JIzZJ3QKZnKkdIksG3u02N6YXJJZsYBckqFnsoeWV7LpCg13S5pgR+OyiqTlg1/qKxVQq8Q1OauXHKQWznlJ+wjkI8YUsoL6ZRTb9osZGl7dL9QQGwQvLSw8kQSaAT8XLgFmdtXWLHHnN5XmbKEfyI3gRArmyOmtMf0g5ovHGlzTxZk3Qvt",
"part_3": "fNpz6chon+PdkS3kVImMnAC3OHOpaYpq0tJUqEAJ256n2u+Tpr9/xxdiTgXipB0HarZRNbcoJeNBwiwBwCwlWeGUnSmZnhPJNxIUKchlLkuaQQEUMz79c0KiKECy5cK00eWDmLpsCfBT+SXxnhTTBaFspKv8lhnzMZSrhAM4GCg9LaXwgjFlKkscY3+2yjn95lQd5e4IBIPAKvcp5uJB5TAsDOqL+MfEpP9kqp",
"part_4": "LmhjP2bC5kVhAqMeUapzSDvkk4FosNNG9wzHGtettweUxfo9icg/XnQ/iQSICHRDrcQCGqsV/fd6bwejPO4anra90ukzPHhiWrw+tooo/4c6mLyvlfvPQjF1OVSCJTumkIMAUbLqoTCp7dvWkKiDA+6B0dxPTh1z/xyN+jfr9HYeEuLB/+9ceHX34LZWAeas+BnEAkmM2MueOqQYPeLZvUpXEL8GsXpspSWgg0",
"part_5": "0GahuLzdxL6vXDezb31WRQngXTGE9OpctiiiNinl60oxmR6wD/OdfECbeZ5sA6ymyB9JpZ2WquAuWM9WOSuz2XmX5/XjTKrEzJPcuvXRYAwBYM5Ibq9tB7ecq425W5hQa6BOD//S70NvrLm8ypwqPIcqgPTfPT8Q2EBwf3P6pqYQk7VL9jcPIsd5W9PtRTXRQ4rZIlRiopOziY4poQENJ3pEJ3RKWBlT3Kc4pj",
"part_6": "jB7oBiHBpRfOIxBjcjGnTdnI3C6fiU4jOKx7WLZEDJkBJswi0lWEAs+ES0jlOO74NRPGgEH+R9r7IMcxv3Q6qCqDn5muCQ9JKngIUwfFH9XZIahuT1wBN3dY811xb7KaWrSl2LOZXHuA9LOQP3mGi4/NDdd3QBPRcHCNILcA4Oj22RKfw9nGgBSVzQ1VXfN4ZinZa4duSBPrzmlVdrKxM9BcwL5h4iv2Hf/Yn+",
"part_7": "6CTuSsJn4/zdUdzs8AeRr9T11atrOIHXdoNDfOFjfLrjHul/yXfICza1DzhH2r5IB37v8JNxrUEKHlbAeiRRvgt6Rs8Og1EwePbsEDX09UH9XInWw3Nd8qfXmafXmafXmafXmafXmafXmf/L60zjxEbnV9HLly/D9TXRT682/8FXG65+c6r7a6JR2ei6FzlpHSodXb2bRG5ZyEl0TpPIC+2mllDUw4qvdtjk1o",
"part_8": "EHv2yC8P06eqhtoraL1tpovY/Yy/sefXpobrdtodF3G/2z0VwbbbnRiJtt+tm44h2U8Gr8+e6SHe6GIcuQ3D5uk61uT71b5izZx+1gV/JJo4cJz1sUoOZ9vE+M7dDjoDl49+ihOE/OnjG2iyupaa99D72mWU57xBjuyGMQ8hjVGSScASTpA3Y0PXxE7wx3pDds2nYVcLhqVt803LB15fYOPdwaetROjHglkjYa",
"part_9": "APm+7jcU7DUxtotzNGqHlRePH1YNBw3lgW5eaIcHxgZXiAfHIybGaFcv+vBUo/FSaPMPY62RABAFSdSoMMx8yR6Ja3up4n6/rdUqtC9XZ6K2MFagPZru3N8b2Gg7sLhbyZqCQF872Wsog/X7h0Jnn3YY3APYyQ6FjU+6CmuH347LMOiL18ariynUkUUA2gD3lBJkNaaB71OMbDjH1EJn42I82Qf6jqkahyuhgz",
"part_10": "cose2J0IwDWmMv9qLo6A+ogyRb5DSIfbc9Hvv2cRYPmqGyCXW40cIsk3WavWhaqlfvBTVuYF7Nhkdi39Fko3HbZF1KPdR1nOMV0rVua/WxSr8RSneMPQb7jj4863f7cFX6uhW7fNZQN3EC3Irjjqo80xsTd2/sJ9tv+H681qu1RFfy79S9ZXXw0bXwMU7QMPBvJifrLVBjv+b/TbU3lVavKxmdu7KS7/8BrsaxOo4dAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/2VTzW7DIAx+lU+ce4jtkJ++yqh22bRNmtKpTQ5V1XefDQkQ5YQB29+P4em+btdl+nifb8v87c7uGdzP9LfM9+DOeAuuQxvCFNwJwQk4xx26HLegHPtdjlTnVOWnnhfbXJe5giM/6hWBIaAR3ICtroVHB2awcrDiHgP0WtH0uLeSBkQgzRjAI6SxM+2h3DyEINrR2FAH6kEDpIXoTVFBQ0RWKF1Z4aytGE5O4YYyO6MkttXESEYZiGlPNAr2DjVpEpPAlAWZEImwpiZLqNnxUJA1MjsUVqMIHDFrxVQq+2gFVppRWzaLJGrcapRkNDsTjeb7mmexSzZGe1BzptK6cq3ErtPbZgfOKlbRVPsocpyU9/UUdiM4+H8w/+B8aVssjr6kR0fluaVu2btE6PJyJ3efH7+f+ntuiy6vf2dCOu1VAwAA"
}
}
|
codegen__primeintellect___2425
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nBob is an avid fan of the video game \"League of Leesins\", and today he celebrates as the League of Leesins World Championship comes to an end! \n\nThe tournament consisted of $n$ ($n \\ge 5$) teams around the world. Before the tournament starts, Bob has made a prediction of the rankings of each team, from $1$-st to $n$-th. After the final, he compared the prediction with the actual result and found out that the $i$-th team according to his prediction ended up at the $p_i$-th position ($1 \\le p_i \\le n$, all $p_i$ are unique). In other words, $p$ is a permutation of $1, 2, \\dots, n$.\n\nAs Bob's favorite League player is the famous \"3ga\", he decided to write down every $3$ consecutive elements of the permutation $p$. Formally, Bob created an array $q$ of $n-2$ triples, where $q_i = (p_i, p_{i+1}, p_{i+2})$ for each $1 \\le i \\le n-2$. Bob was very proud of his array, so he showed it to his friend Alice.\n\nAfter learning of Bob's array, Alice declared that she could retrieve the permutation $p$ even if Bob rearranges the elements of $q$ and the elements within each triple. Of course, Bob did not believe in such magic, so he did just the same as above to see Alice's respond.\n\nFor example, if $n = 5$ and $p = [1, 4, 2, 3, 5]$, then the original array $q$ will be $[(1, 4, 2), (4, 2, 3), (2, 3, 5)]$. Bob can then rearrange the numbers within each triple and the positions of the triples to get $[(4, 3, 2), (2, 3, 5), (4, 1, 2)]$. Note that $[(1, 4, 2), (4, 2, 2), (3, 3, 5)]$ is not a valid rearrangement of $q$, as Bob is not allowed to swap numbers belong to different triples.\n\nAs Alice's friend, you know for sure that Alice was just trying to show off, so you decided to save her some face by giving her any permutation $p$ that is consistent with the array $q$ she was given. \n\n\n-----Input-----\n\nThe first line contains a single integer $n$ ($5 \\le n \\le 10^5$) — the size of permutation $p$.\n\nThe $i$-th of the next $n-2$ lines contains $3$ integers $q_{i, 1}$, $q_{i, 2}$, $q_{i, 3}$ ($1 \\le q_{i, j} \\le n$) — the elements of the $i$-th triple of the rearranged (shuffled) array $q_i$, in random order. Remember, that the numbers within each triple can be rearranged and also the positions of the triples can be rearranged.\n\nIt is guaranteed that there is at least one permutation $p$ that is consistent with the input. \n\n\n-----Output-----\n\nPrint $n$ distinct integers $p_1, p_2, \\ldots, p_n$ ($1 \\le p_i \\le n$) such that $p$ is consistent with array $q$. \n\nIf there are multiple answers, print any. \n\n\n-----Example-----\nInput\n5\n4 3 2\n2 3 5\n4 1 2\n\nOutput\n1 4 2 3 5\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIAEb8N2gC/+1b627byBV+lVlBQSiH1prUxUoA/8i2XcDANinaAi1gqc5IHEmTJYcMOYzsBgb6EH2APksfpU/S75wZSpRsB426/VXZwJKcOXOu37l4gv3SSaSVlbKdN53flTpT18aqNFUL2wk7y9osrM7NrZGZAgGWtEnUXedNFMeTsJOXeqWNTG+LMs8KYvGHPP2shF0rsczTNN9osxKLPKEHaOapykRd0ReRYGVVyiyj71SaVS1XWLy369y8mZqp+SGfC10JaYT8rBOxxEu+5JP4VLlYQSsx7fyk5KpWtPWTUmBeTTshDiXC5om8FyBfqFTNS2kVmFXM4NEZ8ae8TBPxq7XMClhcrXUBxTOcsDl",
"part_2": "poEzynSCl/ojTNq9LcomxoDGVrqxKiFfXdEXQNWI6hSGjbk9YJTPILPOa1MHJDUnpix/UMi+dn1q8KitLW4WC7F5D0UwmSki4SSWa49CYX0rzM5xW0beSizXLCcUSURDdqHteWdIa2pzbdV+8XVpVuphQsEL2COIlwdfHYStgo+2a1+TC1jIVparq1LI3l2xEXoP3Wlom6mqSwNJxYJGXHGiIXiNsLa5wHkTVhWjOFbfuZJFXmimCbgSvpdDlVrsX00UQ09TRwoVK1EZ/qlWvL67hCLApyZsJ/NUtuowTUagyq61sXNWNQhGHYJfk5FbT7VMA31bk4JcV8PQZALZbMBSpvAdT7RCylFleV4DXYCUJUF",
"part_3": "hK1EKTITBwwweTfAPjPqvyXnQHXcaCWtRWIwWAOIpp1YSsrRr07Ysf8zKDffcu3ItSSQIRYb0sgdrup65D1HncFbbURapgwgZWw32f4KQrEcAzIRz2Rb+KHvxL/NDrIlKlg0Xj1Mal4NVncRugi9VGCtYMXYoYSw5FlZOx1TrfQCFtm3guS404irepXijnSMZVqmRpKOxg4vzq2TAh+Sz1QEPwK4ZejUQrFYxSvlYcOIdcaoRmfiAkfmalXFjafiUfSZ9Y23VCsDY+LdhvffF+SVLLSjlnJygmJrdirlJWAeRVDfJMrvSisZ+IPtaVA2xFlQY+k/OcVM5FpZQzEPYiR4rcJOyTH8n1d6ghKWRpih8CN",
"part_4": "XJqdgu83wCTQ4blIBSjGUAO/oaFNNW0hYCNRgbMEfGbwJ/rhSLw5+nV8+nNfGAX0jiGW7cxa1Nnc1U+5ZytA5tU3CLWg46sXSlLKgxZWNyW67ShPGMV3uVWuUg/pTG/DrYaU6ZRGKT4LFOd7FTmYujiG5LXfR9gWmoqLgWrjSy2hiGUuSs9iV4ukSTg4A1okr4Jl8NxKO7zWvxs8g2nS1WXXnEHW0oQF/3y3tc0SghotWSA0OFWOagkYEEVqULLQOkAh/m9WOnPdJbWpbl/hHIWB7uaFgKVd+V3CwFKGdIGzJTpcwuamnP6uTZFbfmt6UtLXULlVBvKMmMl9TUpqN9SEUBjX0EV16RGviS4R3TxF7Sr",
"part_5": "f/7jX3/7u8O7/is3x8Oq1Qjyhd8jxag76ysVya52wqkqerkVla0vKFjRA6Lq3+PW++Chu2sDbunjQ9MLWrodVtamCTk4Nx2ywVIigmpdL5epSnpbr6KjhJT1oEjQMtFFVNkXvwdfQlO4a3BfyRvKtPmeIMokmQIcX02nR+fYqdeMBExAWLOqKZeWyz1VZkt1FrHNjfomHGnCyB5q3te2DRvMfMYyJhKc1Zj3WgErbiPqK9xDU9dEi1vTfbJb91wNdcnvGvKhQltQO4Wul95Aau4Zxgxfj6oNhEMSa4bE2VP/N664ev05BaZmNDVDMRDx1MR48FdEX1PjrJ2aSAyF33MIZsds62tlMblwACmxkenUopw",
"part_6": "CWKC0Tmv2N+W6TXJiSb/vUBKq7cjbTLjEB/0Ncx0vY/5VfYzOpeLCtKBJmke1uca4AH9nRV5acTY1vLrIefxm7BxsYeYobZ6n7Q3/xqM6bW1Xqvvdeybt2vOgqoXB47HU4v5wba1k8elwcVnKR8qhP1DKowwEvT7mvgUa3eBian779s94gyL9TN5RTeGld1iLLvATEcn7X/Pn2dnrV5dTUxVLapKai7L2ObpSAR3rzaaYI5coTmjaQQ9/Igj8HBDGIZGGcbNNP2B6o2fgGz95ZBAizizh7OyiP+q9itqH0cTd+asr3Vpu+Hzc8dFn2gnXvQPCFp+P4PPxie1GT+xrZ+ZSzwMTZg0vnMcscSUuWoc9yG",
"part_7": "4uUFVnblmllWpRyFDMYTjzEt9/jxa826MoBYF8kfXEGV7m7iUW54IXe70X2Y442SPm/ReZeEXn6AVr9Nw7whq/AMMDrduaY9xKZrutA+3blOjYC8gjauefxVqW1++CuyvxUrxsvOSoA4Ic53QfdTahpgRgVlSC6Vmk2gZ3vV7DCXWJGIknOKGhVTbIZBEAI+F/xnbL1yxKRLBsOKKZXCXKXEVPorBsgwak5G88zgJzruFr5EkrGIrGygCPswDDf7O9p7g7XOQbIguxfx7Tf3s7YgZZWlfr4MBmbyaqXN/vE/nLly/Pzn/BX/CbGrKDso/LcUCuk5T/LiI99tHtzkcYMbgIEMnFDK6B7VODVosFWCPRQ",
"part_8": "+hPzoCCho0DD9PpVtHgzJVI7JbfE+TfqyZA9APeWOrLosDMGGjSz5C0G6ixTOWKJ3rS5Dx+LDAKza6WIBsSriJRS96dAAN5Q1L0DCa1UoG4tzZAd7HbnAN/P0/RncgRIX5nLeF3X5NowYx83lSLLVH8RrSpoj2qvay0N7HfdL5AL0yp4E/NZq3RwdPvrsxhcSZDQH1zHs9m+8WV7dwLgt9gcqjxOEo7713x1uMdz3TfaQfOcxv2oN3ceW4WKZ7hj73Aa917ajlqlvHVYIQc7FdThhKPEcEZSHoYArhKYACwJQZkfPuZ4XR1dro6O12dna7OTldnp6uz09XZ6ersdHV2ujo7XZ1tr84aJlXnzU3nw4cP",
"part_9": "btL1N1Kna7TTNdrpGu10jXa6Rjtdo52u0f4PrtGmBiNAZxZ2rKosRoLOzZdpx94XatqB9ztcWm79rNHBANbhtHCbo2kz8DQTTzPywBQmzt3cw9Tb2Ufw9kMovlXSCAElSSMRTWmWchIfS4qhA2gh79sljZnzWDQSI5Y45Cfr/6RE+IBoQD8+QuYljlx6mZfgRLLG4tJb6WSOwH/8rOxI8PmjLB61pFB8hniS70bPRJFpjo4i6Tho4Wbg7f1fSIq9JIcbis7wWWQSXuIjJZGeEUuMfKwGz0iiSA3+izg18WkQOfJe/GWzbezzeORzYeCfQx+v8TO2DUATHRmxcSu/xj7vyJ9Dr8vgWZnH593Y43DkEe+",
"part_10": "+x76ejb+Cy7EYHunbS1/BBh6hQ/btpX8i61mHy2eyj7xP6EFtOLrSUIScFtGetCYzn7d8sJUdHyV94m13OBr5/G9wNvGxvxREN/H177EWQ/YBnZtw1TtOjwGdZXnx1uqJz6yJx9zkq1WD0Qkd6CRxO16PkY/GuKXXZNsHBtveM3nGH0zrtRgdqcfEy2nyYOJz8HL77eoAfcfP5CLTgs+EM/Lb9XjN/F1uTMRr9vvEo5S+Ix+Py9a8MX62Ag5xgk/72j4+UiPCGT1f+woY+2oU+Yg0SB77LG40fwoxrlczBeX6kRqNybK9btD0n7HHbjNLOM0HX+l8TY8ds1aNRjP6vxOqW/dPXZ03tqzVw78BN/HUsd4wAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/2WRPQ7CMAyFr2J5ZnGTeuhVSMUCAiTUojYZUNW7Yzsp/WHJU5wvz37JhPehT931EocUH9jgFPDZvVMcAzZwDliH0HmowYlWoiRK4EDrAU8QkI2ojOBCyAre6mT1TNZ2ksnFk0T9wYvMnYALwUY4uckHMs/hwEPeM1Q2J9sUa1cqXWUtXv6QQLssWclIb7okW73UY8noTF1J0CrSp7h5vkrDKAA/D5vByrwWCexBpNmOY8gHG07DWfB90e05dfprosPoxTJMO+MJx/h53eTfhyQyfwESizjhDwIAAA=="
}
}
|
codegen__primeintellect___2426
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nBachgold problem is very easy to formulate. Given a positive integer n represent it as a sum of maximum possible number of prime numbers. One can prove that such representation exists for any integer greater than 1.\n\nRecall that integer k is called prime if it is greater than 1 and has exactly two positive integer divisors — 1 and k. \n\n\n-----Input-----\n\nThe only line of the input contains a single integer n (2 ≤ n ≤ 100 000).\n\n\n-----Output-----\n\nThe first line of the output contains a single integer k — maximum possible number of primes in representation.\n\nThe second line should contain k primes with their sum equal to n. You can print them in any order. If there are several optimal solution, print any of them.\n\n\n-----Examples-----\nInput\n5\n\nOutput\n2\n2 3\n\nInput\n6\n\nOutput\n3\n2 2 2\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.5
| 0.5625
|
{
"part_1": "H4sIAEb8N2gC/+1YbWsbRxD+K8OVYqlVLvdiybHAH1ooxZQ2JSmBkgvyWreSFu/tXnb3LIkQyNd87w/oh/yS/pT8kszciy0755dsKRRinbDuZmeeeZ6Z3RHWmyBnjlnugmnwu",
"part_2": "xEFP1aOS8nnLhgFi0rNndBqpljB0QFNQuV8E0zjJD0YBdqIpVBMzkqji5Ignmt5zsGtOCy0lHot1BLmOqcP9DmVvIDK0hO5oGVpWFHQs2RqWbElGrdupdU0U5n6kc1XSy3zi1",
"part_3": "Bh4ZybLXBmt+A05jBFJZnjIfwszrkCBqW2wuE9CNSx5AYUGF4abrlyIBwwi062KkAvoGAbUeAtxliBCUBVxSmG4FJJpWifbQhPFYc5U0SklsccYsxXl9CMygR8I6yzRAuY2l5",
"part_4": "QWBqOHA3FKYhDkvaMz5mUDVLndkb6yMzzNr9YEGW0XkVA8BxWqIRv2NxJLMVafy48F+fCamP/+fvju7/aoLMQKHumHtHrWJWVq+/I9Ad2RCtEkwLVYg2oRYJcsIOoUKi6dNgs",
"part_5": "uVvdQQIf33/AG/obRxFEUTQMd7I8rdz1NAthrLuSR9dOtyQ6a2Tc1TKLAde6EnZZLUf4vElrV7rCjdXmw9K30WvhVkRImHqT8NcVk7TTVAh/6qrdA8iJfArKRX3WJucmhONai",
"part_6": "uHADCXDnYqxunSiwE+rZUVsRm18HVcHFLvF+mnDilJy25ar7lCmxrTe1DFTCb4hJUu7OtldTWkVr05008C1wM12iqxcXnPOYYtq2iI0hNBgLliSZPTVhEjXb3pNa+3R7o4j4R",
"part_7": "juKqNqM55zHuKIMHyBVVBzmhjfQBLHk8P02Q8vfv0lw9lBp06owRAPOOBLwRG1eFDTHAyHjbVmNFDw+DEkrQmPgoJvUdnREURt8KXrXgJ78B10IW0Ml5bf4QqPIB7C97CX7g1",
"part_8": "JKDQcZzPrmHG4BWelpqiOb0OePD93Qem2lILGoDPoh89tpR4G48NgfBiMX/1g7EBsMH0ZnJycNCc6U1/TkMwUCg9ejQLHcSLgYHz5JgvctuRZMIUsqPswayscjNBSi24Wxxli",
"part_9": "1sbmVDTWJGv6TmtvR3B/uEkvXJp1G+WLAZNewJgAvxwsvRHMQ+rBrVI9APdvaYWH2Ce9cPtdK3wgD++A9BAdR72Y40uaPkTj+E5UH679m3Gyy9WLbXoPXB++/Tvq4CpfL8bje",
"part_10": "yF7cB731yKZXCd9r8uHQP+5Tp54EfAkMenfv2nkTcKTSBLdMICj+F9R+Z9dHoW54bvkprJ41P6wP8X+5D+tvM+c6f9eOOzh2aK/ol+97KxS4nWF/9I6U/G3nwDYyD2xNhMAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAEb8N2gC/6tWSi/KL81LiS8pKi3JULJSqo5RyswrKC0pjlGyUoiOUTKOicmLUdJRiFEytIQzjRCi5gh5I4Q8nIXQYwZmxYKY+aUlSDYYAiWMUTQYKaBCJDcYYpFGVWIMVWGMYjOSWoRhIHE4zwSuCtMsiKrYWiUdpeKSypxUYDgVlQKpWgDO3+UYPwEAAA=="
}
}
|
codegen__primeintellect___2430
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThere are $n$ candy boxes in front of Tania. The boxes are arranged in a row from left to right, numbered from $1$ to $n$. The $i$-th box contains $r_i$ candies, candies have the color $c_i$ (the color can take one of three values — red, green, or blue). All candies inside a single box have the same color (and it is equal to $c_i$).\n\nInitially, Tanya is next to the box number $s$. Tanya can move to the neighbor box (that is, with a number that differs by one) or eat candies in the current box. Tanya eats candies instantly, but the movement takes one second.\n\nIf Tanya eats candies from the box, then the box itself remains in place, but there is no more candies in it. In other words, Tanya always eats all the candies from the box and candies in the boxes are not refilled.\n\nIt is known that Tanya cannot eat candies of the same color one after another (that is, the colors of candies in two consecutive boxes from which she eats candies are always different). In addition, Tanya's appetite is constantly growing, so in each next box from which she eats candies, there should be strictly more candies than in the previous one.\n\nNote that for the first box from which Tanya will eat candies, there are no restrictions on the color and number of candies.\n\nTanya wants to eat at least $k$ candies. What is the minimum number of seconds she will need? Remember that she eats candies instantly, and time is spent only on movements.\n\n\n-----Input-----\n\nThe first line contains three integers $n$, $s$ and $k$ ($1 \\le n \\le 50$, $1 \\le s \\le n$, $1 \\le k \\le 2000$) — number of the boxes, initial position of Tanya and lower bound on number of candies to eat. The following line contains $n$ integers $r_i$ ($1 \\le r_i \\le 50$) — numbers of candies in the boxes. The third line contains sequence of $n$ letters 'R', 'G' and 'B', meaning the colors of candies in the correspondent boxes ('R' for red, 'G' for green, 'B' for blue). Recall that each box contains candies of only one color. The third line contains no spaces.\n\n\n-----Output-----\n\nPrint minimal number of seconds to eat at least $k$ candies. If solution doesn't exist, print \"-1\".\n\n\n-----Examples-----\nInput\n5 3 10\n1 2 3 4 5\nRGBRR\n\nOutput\n4\n\nInput\n2 1 15\n5 6\nRG\n\nOutput\n-1\n\n\n\n-----Note-----\n\nThe sequence of actions of Tanya for the first example:\n\n move from the box $3$ to the box $2$; eat candies from the box $2$; move from the box $2$ to the box $3$; eat candy from the box $3$; move from the box $3$ to the box $4$; move from the box $4$ to the box $5$; eat candies from the box $5$. \n\nSince Tanya eats candy instantly, the required time is four seconds.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.3125
|
{
"part_1": "H4sIAEb8N2gC/+1aXW/byhH9KwtBgC1UMfilL9+mxRVQCHlpC90L9MEyEtpa2ayppS5JxTEuLtD3vvYX9pd0zpmlRMVykLh5aAHJjkzuLndmzpw5swTya2eZ1mll685l569ltrbvXG3z3N7WnX5ntXW3dVa49y5dW1kgQ5lb2k+dyzCKx/1OUWZ3mUvz95uyWG+wxU9F/tGa+t6aVZHnxWPm7sxtscQfWXOT27XZVrjDEhm5K9P1Gvd56u626Z0MPtX3hbtcuIX7+d6W1qTyr+u65jZ1yydzU3yylcmcWZWFq02xMj+nLksvjCz2kykfKmVDu8TK1JTFI9avTW5XtakLI37f133jtusbMbHUyW7YxZzY0t2",
"part_2": "6WfdNfY9NJQRXp5mrTLd8n6krma36zYW5T33Ut0VelKZ7i1Xn+wFZZ+r0wZrCWfhc35fWmo9pvpWH//2Pf/L3X0Zc6Zs7mXJ9I0/dyHTvwvyY5ztD4kO2lPAMQMwZ8d54JVnyBs9lvclqk1XG/rJNcwYGr3oXQPady+oszfOnPuB7SrHO2U/EplYgPTimWwEOLkIU6wLGdJWzAuMNHJXlEm0Ke33zmAlqafM8h5fZamXLytw8AYEegrMyvI9KwduWpZWkynaNSVlVtYOvU1fD65ttzUfgzhrPAN2K8FZWsrXUMFfHtmGyfZR9XLhdzFld2XwleVgz2+LXJk9v7c6eMAtIFWJXLlvuZ/WFeedMgTXmsSiXVY",
"part_3": "Nsmj+mT5V6IIhroEc8McjYZ4Ds+eyKWrxaZVKZPjTm9sEVj04h3qUIS9vgkm4H5ABK6aoWT1OnHu+Tt+MsH2z781igDATdbZ19bHxjBI/32e29qeTJA5xZhxq95l/y1CNM6XKZQVc8RmeydrOxdVYTXljRPEstUEL6pirgg03FDnkKwL5gu++TVd0X23xpbuSqLrNbbHmQOQnbNWBvSvsxK7YkESH+c1FbxXZVlKppWVk9s63AP0pq2rA3HmjyJHfqgAQNAy2tQNp9qewBp32/sSBRoeKwufzmNhUfug87Fbowf9PkaUFkLltv160ttR4qYkQvnbXLP5q51M2+QJ8lr1Vr8LCWzgAT1QbFVrgchbyrPvV34",
"part_4": "d7g885ttjWvvIZ72PLM2b2QqgJm0mzuIAwiun1IDY0huPNuaBYLUTinfwYBFvixyk+1hh70TxQEQbdnIKZ7BHal1BeDFD6zKSoy0DcQ1KkYloZloWZbuZa5Z2nxadD2sG9wh5GhV+3jYr/YBSN3u3DaXj4rtsZjNVXfZ+XyMzOV6Lp1t2wnMJnbusZGZ/OzvjmbnTGgs6ncrK10SN9yj5c2J0R7q40wxSuwTJ3LXuQ++xL2xI3vT7I1b32TmttbVbe01jI9aJstLfLc8a68HJ8UTbUR7T3g1l+2dZtccmARZ0l5yelzyn+xaqQ5VEW+JQuWha3cmXj+KavkXLDhvovOm3DRaZv/06d0vclt5R0g0xduYGIT",
"part_5": "BgsXmkiuEjNYuPlsOp/jMXV44RLturyOTGjCAZ4bYmV7mRh0LXtQoINKaic9bdSkYfChSln1lQcpo237oN10426723ej7g/moG8crub0kV2iw13i9i5Pzyz+8DWeJC8sSw6XDb7s8ECOLYj9pwx4fXYMeGrrGx4pBdgMJ8FG6FbFtmx4dNHAnyGBKqJsKUucLqXMnopt02qUOk98umGXeC1rCyRY+8oj5vyhrTkWY5/S1tuyqcelvZDztjR9NM5bHL+l6kTCHsxbKZWqPl+nm3Mx1le3znsX1SbP5G+vt5DzuoiYBPsVS70k+JV+QQ+OLjcyenX1JiS1/g6p4Kn6/MH8zoS9aw5n+2HXu+ZjdmXubP2jq85",
"part_6": "dfd/nobt3CRYak630DP77tybwQ/j4wIPdouXmSp69vsLia/OHo6sP1uisfsu8OD5pPjr4zNfWhmLQA3aVXcO35g7747CqGGHy7dvmBnOtPfCBeGVuaw9cFVdEoc7lSlrpDTExb0zWEww9SpliJKN7L5CBfUSHcLzFtrtQAQXvJeuuOgz8paB1IdySq37Lj4dDJ8RHuFzJaEinxSuAhcdbhiAyte4JBWMNYOeeEJhME/LWpci63Hu+n94VT++Kp3fF07vi6V3x9K54elc8vSue3hVP74qnd8X/7l2x2aTqXF51Pnz4oMfjhTu9N57eG/+/3hv3QMA9oXLnut+p5Vwk1O5c/bro1E8bu+hciu6yst77mun0ZY",
"part_7": "RU1Ekvt229bQRXNubqQuWUyxOO/tY3X2/BC7QqNCX62MYS3TfvPJSdIzyX0PeB3KqF6Ww+PWqFfrzWylAsJGJHAvIYzV6wEny7lRAoMQ/4Og5+8ErwA4I/+L7gt3Ym6PPvtvOLlDzufPTtFiaeKQRdTMTMqvzQEMg/mx5P7egV4QQmnvAoDaaOTSK2hiZKTDI08UhKw8RcEcuICYXKvBybUJYG+Dvyy2RCXBRAQiP3gr+4LeQMsVcUYdOEtzES01xLdvBAKOQNMBBiIuJ0NBaHphIpPghbvuUzleqZSQFN51P9NyUeMjTn4PfLs3ghmVBggMEIgYv3iEQuIgSJCIW78hMzUEED0AlDJrwWOAaAJWnuxoyO6",
"part_8": "Mp3CP4IcGIoJnIAeMDJWFBM5JkxBiLjHRhh4xhEIB5QEvkRRICL3M0BBEf1w7kZODObfU9kJPohgYmgPiTDCFkMm+ROSIkRVE9yGpEdA6xIyIAxwJPYGtCESgIUAI2xdwzJxMCIORgRtAhbyvXYUy0AdiMSh6tAl6nioNBo7FMUjIBFBnGSHGIhzY7LQjgevA4VeENUBuQAA4azMfk+JiYhYhQOxT6ziHGMKBA6yl3iFjgEC4VNNpWLEXEkxomSacQKZckJazgAhImfGI9ZfijcgYEsIHw2TpYJL2Yz/eU1y4iVxWKSwaPQjIevqyQoDCQtAT8wMAITJlQGEiRWCQgYxxiOh6wu8iBm4omoxIgAWYsTFiL2",
"part_9": "Jtagk0eVdBJqTTzqsoFuNsHmCTEMVF9QM0QARQTCzFVg/YVyiJUE7rwg8vGrUEHA0UB7CQ4II/gbIofKdKl11FfMkEYkA9mDaEYMP0SqQRgWCnAde2kRSIVFAgdYQLkSCYGaDBtBDojNEOyBXEPMh0gU2+ULn9lLn6OwTCav6H7ezQDyHzOMiOExqgG50XwnqpYJ5tkmOYEGnbA1Dwkc1Fk3iH1HUSWYa2aRd6X//KUW/oqTTaypGwMA1CRaLBMY+Caq1/IdskpBhZjVTaaCrLF/BIqRNMUckO8hs5f49SiggW/MnlUJK55HBaX3lOxW/Ztp7VMGXjgjRq84SaO3CdoT1T/0Q21bAWs3hF9IW+DbWyJsQ7l",
"part_10": "H6rBh2xMi8pwQk/6oc22AnMdhISR3Q5XNmCob8NhL6YyUAIEvbqo+Ymess0bYcIJgx5xrqWMc6BxFIp68DgnIFPgWU8EpWXpoGJOwE6NVx9+Iv1g2pqInLOmE7Z5SiPRGvm5BEDy9GwBMEz1HYPW4YRcNhbv5pqxV3aj1U0radKq6p6MeC3bQo4AMX0cNyhYaEXwcNbpPakwIT8CjJ10HU0JGGVMPsRANckhJU8IQqZA9AsEO/Y4RH0pU90dN/wz8MZU4xTxvYTlS25yPvNZPKf0NSDw3zFUtlEkvYPJq/fcH7/8x/WeBsHhmKhZkxXyuJ0zFiCOzLwpnc7i8xv87rt5vXfbL1nYu63Jrf/sP03N3x7gsAAA="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2431
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThe rules of Sith Tournament are well known to everyone. n Sith take part in the Tournament. The Tournament starts with the random choice of two Sith who will fight in the first battle. As one of them loses, his place is taken by the next randomly chosen Sith who didn't fight before. Does it need to be said that each battle in the Sith Tournament ends with a death of one of opponents? The Tournament ends when the only Sith remains alive.\n\nJedi Ivan accidentally appeared in the list of the participants in the Sith Tournament. However, his skills in the Light Side of the Force are so strong so he can influence the choice of participants either who start the Tournament or who take the loser's place after each battle. Of course, he won't miss his chance to take advantage of it. Help him to calculate the probability of his victory.\n\n\n-----Input-----\n\nThe first line contains a single integer n (1 ≤ n ≤ 18) — the number of participants of the Sith Tournament.\n\nEach of the next n lines contains n real numbers, which form a matrix p_{ij} (0 ≤ p_{ij} ≤ 1). Each its element p_{ij} is the probability that the i-th participant defeats the j-th in a duel.\n\nThe elements on the main diagonal p_{ii} are equal to zero. For all different i, j the equality p_{ij} + p_{ji} = 1 holds. All probabilities are given with no more than six decimal places.\n\nJedi Ivan is the number 1 in the list of the participants.\n\n\n-----Output-----\n\nOutput a real number — the probability that Jedi Ivan will stay alive after the Tournament. Absolute or relative error of the answer must not exceed 10^{ - 6}.\n\n\n-----Examples-----\nInput\n3\n0.0 0.5 0.8\n0.5 0.0 0.4\n0.2 0.6 0.0\n\nOutput\n0.680000000000000\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5625
|
{
"part_1": "H4sIAFD8N2gC/+1a224cxxH9lc4+xFx7tZievs0QNgIDcRAZQWxAeuMy1HC3l9vUbPd6LlwygoC8+j0fkId8ST7FX5Kq6t4rJTKWZOWFK5Ca7amuOlV1TnUL0JvBrOqq1naD08GPjVva576zdW2n3WA0mPd+2rngL3y1tGAAS87P7O3glOcqGw1C466cr+qLVROWK3TxItQ3lnULy+ahrsPa+Ss2DTP8C2wua7tkfYvf0ARWrppqucTvdeWv+uoKFu+6RfCnEz/xL8Gm6WvbsjBnL1y3YC9D3yAW37GqsWwNSNlrH9aed",
"part_2": "YHZG9vcBW/HzEfrrnoN/qqmY85TwN32MXt58J21Hdi1bE37MG7lZ2HJpovgphbjd+sQva4XAcwg8NxdLbau565pO3ZZdV0NAL4FyD5uW0DKdWhtO2IL17JVXYE/eEBwnl3e0W5vb7sUsr7DoK31u2gzN/NfdCnepZ2HBkL8MUBdXAdb7Qyzv7SsrRw8LqqO2Wq6SGA2AI/rZ/0spVuxma3gb0CbQIfVCp581/7huExx18JGn8EDWnLc2GXlfMuq2t3YMTbveztz7PlN5Vk1nboZbK5qsK5WKwutm21g1Q7KFutErXJTt6",
"part_3": "og8ntgj9mfwxobHavZvoZGbG3/QgV6AcE2Hv8UGqg2UqUN0OImANPgCd5MAZjz87q3fhoJu2v1AQ4LAGxDfSCOHBGJhfiOuEYJQe+aLzaNruYdbN5rx5j9MAdF9E1rR4hjHbC1S9e2lNB0URGe5LCaQQE7lAXAcpi9rVdguESLaVVP+7rq7EZMl9Wlq113h8bo7MZNu9DcUTsm/hl+nvtV39HTRmCRuLWDzk8DxKIuMtQocaezV5CAZyec/fLzv+EBf/Ni+J9//fKPf0bu9stLMDmuW+rAcf8w7HdYjvSemO8pfrsD4IF",
"part_4": "QVZ1cg3LWCwdbgPhLwLasusbdstXFG3f9lp1kBCl9I3TDMaMQDtsHIwfblN6j8I6KRYLBRfcMoO7lALKYgzDijmt8CTwDsfS2Hm+ql9yj3MkMVQB6ra4CjEUK6t4S/+xPPSxA1/5umzBGYoJWajCdz22DAN2IXZMLskRgCfJX+HANbr5hnC1CPWthvsDWXQ4OSocxrkB7PmraB7aEMYHJeWjmLeQydUuEhLRsjxSaqpI6yR/T5j6hfui7fUbFr1Clvf7tqHKv7DsINFFBYHdxhCThHA/tby/bUPfAeChfY4H7aGqbJjQb",
"part_5": "nJVv17Bx2QN0H2Bg3U5xQPLsb2/YM6bf7mP/7rZaruB4SehJGxMvJj4bZywbK/gp8As+4ILELzk8aFzYpYvLusj2Pxt+OPQZk8MB3c2QQn7G7kLP2kXo6xkUBVSGCw2j5Fyg0wxsA7rGP38Na3x3s1M6HqTop7EdVCfOrzCzYzihG0uMmuKB7ZarACOrvWvRjQcKQawTAnUyHE48uoLFM+z0ybJanczrUHUjlizG7Qp6BZZD1B67QGLAKXVlT/zwfOJnK9x7BrU4/9IfW3D29dcsmZ3x87PsHAkcy4amy6p9vbMWI5Y2w",
"part_6": "MnP4IMmbj9eWsePm1NrT8jF71kM5Yb7JvjBaeJ8b3er6PT6PU6TY8d+9w3YYG0P3F8f2+IHMkOj8zOHyS2r25P7Nkd2owctgKKbcOT0S2o2PJ1dn79741f3trohWm+2XqOf+1uH2AZi3gnCBh/P+PlwCPShlgN1ugZGGXxPbHu62z3d7Z7udk93u6e73dPd7ulu9/+6222ctIPTs8GrV6/igTrxT/e8p3ver7nn4SrQZ3A+GnS27YBOg7M3k0F3t7KTwSmbDIjNF4mngxGsEFXiSzE5lNGhjg6FBJFoe4hqov33FYVWb0",
"part_7": "fsf4fAI4R3ugfyZR/pPo/uMSGjYkaU4PvyMeojA8ptSXUqa1yRqazioNAmrUZouCNPu94HUEn1qQCKFErTygYK30LGd2Va1dskEKR8CKCQn6RlKQTfPr0r2KfiB825/bC/CRnVQenlO8u/EVyxZUTBdnwS28ZItuOU2jYnT5x6kEF5Lj8qDb3TFMdApChBoPCXinCKqLOjV5hHfG/iM9uqk6U9PIlhuyHfGsnoLhZh65VA6GzrKXZSblEV20gie0j7shBZJrYT4MOlxXc/O1KxQ5rx3eqeDf9tCfg4wOwBgPzzA8yOAOI",
"part_8": "42s0HvlfTaF2wzybh45rt6qU2P9tVtf/mYFXtSfhwVX2GsUcfjCNyZaKsS21kToNl5/odAGjDRwAQhwBKnmmJzVMyL2R6WZRC5WzPSgnD8zTslOEKJ53UeWHUY3iNzGDm5TrTufoYYm6QGMVNTpBMLiRNcl2KwsQbhizyItsHDploXtAoKwudLgS50QpnOqQuioM8wdYUsQhSZJrjaQEZcEFHQMFzbh5LWBeF1BruCmWeFar8YKJvIeWlKTnlKcEzDdxcCMxcaMBTkrkwWZ6V+6lIbQqNmZe5LAt6yETGi5Sc4oqKJ3Iu",
"part_9": "DkoAm5TBvMGfKuIlUZRGa7qMwozmaM4FhzLu78vzHLKOB4gwRU4jotQlFdiUmeQIzxgj1KOk0ZnhQpRaCCN4WX74QbmphRDQfCyd4ELSMV0aVWpCJmVODxyApQNO69jxXXKC8xKLAqCkwmIC+zJFoxB0wKOqhS60IsoACTJz2A2IGGWmcyqcyEopUjcyuBcQvEyADFm8yuWHbSlMSTil0kakfyJkShm6fBhdEhgJQqXmcZ5nRh4g4BlIJ+6DYsh4PkOnEJUuM6UpsBQ5dVoVJZzKj6qbQ6qZhKQM9Ev8+kaZw0ZRmenSA",
"part_10": "BWPHdMmliRHBUc+c6VKmgAqS2LFemt1WC+0o+sHV3SPAdcw4IgECtgbFWV4lvSjC2o555kpDjypQgiSPYd45MCUqiypfkIDs6MDkUdiCFApjUXJtd6rIKagYRjRK12CiAkl8DtqzOCciWtZHLAFCJcejIA5dZSdFhlG4zBWZRqRppCS01iQQERSMIxeOtFEJkoyB16XB7yCWQIraS7KkhKF6ZCXxG0N44EeOLS5pIyNpNkJEyEieJgfOZegKlQNHC8felySAGOjjQaA7wkGNvfP5nP8DzftRe/dT70dnHZNb9/+FzDPd6qxIwAA"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2439
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nRecently Polycarp noticed that some of the buttons of his keyboard are malfunctioning. For simplicity, we assume that Polycarp's keyboard contains $26$ buttons (one for each letter of the Latin alphabet). Each button is either working fine or malfunctioning. \n\nTo check which buttons need replacement, Polycarp pressed some buttons in sequence, and a string $s$ appeared on the screen. When Polycarp presses a button with character $c$, one of the following events happened:\n\n if the button was working correctly, a character $c$ appeared at the end of the string Polycarp was typing; if the button was malfunctioning, two characters $c$ appeared at the end of the string. \n\nFor example, suppose the buttons corresponding to characters a and c are working correctly, and the button corresponding to b is malfunctioning. If Polycarp presses the buttons in the order a, b, a, c, a, b, a, then the string he is typing changes as follows: a $\\rightarrow$ abb $\\rightarrow$ abba $\\rightarrow$ abbac $\\rightarrow$ abbaca $\\rightarrow$ abbacabb $\\rightarrow$ abbacabba.\n\nYou are given a string $s$ which appeared on the screen after Polycarp pressed some buttons. Help Polycarp to determine which buttons are working correctly for sure (that is, this string could not appear on the screen if any of these buttons was malfunctioning).\n\nYou may assume that the buttons don't start malfunctioning when Polycarp types the string: each button either works correctly throughout the whole process, or malfunctions throughout the whole process.\n\n\n-----Input-----\n\nThe first line contains one integer $t$ ($1 \\le t \\le 100$) — the number of test cases in the input.\n\nThen the test cases follow. Each test case is represented by one line containing a string $s$ consisting of no less than $1$ and no more than $500$ lowercase Latin letters.\n\n\n-----Output-----\n\nFor each test case, print one line containing a string $res$. The string $res$ should contain all characters which correspond to buttons that work correctly in alphabetical order, without any separators or repetitions. If all buttons may malfunction, $res$ should be empty.\n\n\n-----Example-----\nInput\n4\na\nzzaaz\nccff\ncbddbb\n\nOutput\na\nz\n\nbc\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.0625
| 0.5625
|
{
"part_1": "H4sIAFD8N2gC/+1Z727bNhB/lZtgoDamGk3Q9oO3fGyxAsNWbAWGIQpSiqRsJhSpkFRdpSiwh9gT7kl2R8q2nCpd52X95DaxpePx/vzux+MV/ZAJFpiXIVtkr52q5SsTpNaShyzPqtbwoKy5NKyWqIAiZYR8ny1OTp89zzPr1FIZpi8bZ+uGTPxq9TsJYSWhslrbtTJL4FbQF+qU",
"part_2": "WtbQenojFZQsHatretfMLFu2RGEXVtYsClOYXySXJugOXlvdceYaMDYoLgXuZgG8rSXYKpoq2xCs8fS6Uh6uZVda5gQwJ6FmepMIeprDS+vAq7rRiqvQ5bCWwLxva5nMbpw9Gpjh1gSm0P7k9Plk62xqDeXpQDK+Ai1DkG4T0I8sKANMNytWyjCbwwvSSTsBI5QKtRysrbum9CuF",
"part_3": "ptDS3VgJhjcW+Erya1iv1NaGByMRCCcbzbisEad8B1PjpPe4GhHa6GM4Xt600nCZAzOIDfjgyPnET4A1jUSwBGB4FL/nTkozh99W0tw17HFrn8ka08DomGOckp/wSQ6ESo/CjgTyHYboYUV+jBSxvgBqWD1YM78FhFvnkIQa68P2HexCxWLRbom59P76hLbxksXQNSj7bszZPto5",
"part_4": "hLXd+fJf5izViDgl3zMkFYLr26axXu4RM+bjG2viWQh7flgsB49kHcvfiGHgn1gqiU93ifOq+rRqw3hUKrN1AlFlOZQ5ffJ89xyo8gNQ8Ult0KTozZKI4Psa+wWmMSkK7AirwJyza8SuLEdEY2qMjwrHVe8xS3I2p2L8btuI5VIh6fZpno7QONmBVUSxz56iOfwgdbPTQfiFxF01",
"part_5": "nd/98zlazdgufItL09hslCegEdc+Rm5bLajN9THeiRApzEzXE9DvqvkpmWdbJGrW7fW3IQuENY+wkSKM4c5+TGZ48LHsPYFSoIvU83pKDpqZH+QaVs62y5Vtk9P1yurY9Dnimt/pdv6z2jGZwjymP69M04b4FJsjdRnlfABNJdg2ampCCq+yJTWNMIHp5ASKAi2G9HXy5MlkBn/9",
"part_6": "8Wd0Ztq67Hu3RFOc0XHpj4gif/PeVxINlBL7+/a+ldNJwdaMBMKuhxQquxjQMETCeI+aKPfKB3rFOIzFC8UTKszA5GQSuwAKa+tkL3yGKQA6ly66TDdOuoX2APu5DUPEXm4urG20OcKMWP1DiJjMZA5vdg0hSsCvImX7LXjj6WFrS0di17Jiv+rJF9lInBlQZnBnKs506k95vGaI",
"part_7": "GER+Lxs0Hyxax0wQZVSNDIpNj/xvHBDzBxTL9yMusZnj0NINoXqRWniPVWRaYZ4WhhXm9pax28JwXlX4WQpRlrQtgZs06L3kG1ZG3mDkFBBhJig3RKDDM9mHkGBHAfYEq1sKkgBCXUs26e9Pdk1r/VC1maHIjpOhdYmPOGHJOQ5nTlbS0QWPk5iBMzoA0xTHdAazwlDzuSSMHXXv",
"part_8": "KRiYLegaBvBROyomgULBk/TI8BEHxM0KlhTPj4LvkWtmijs3NuK2inaebZfgMZxQmfw5yi/gm7P09C1KLwbbops5E2K60ZztL+KWMzjZyaT2cjGicppkGkM+xxuVEuaRVHDRr8y9ddtcYgGmUGRFNr+yCmPWGPMMofQ4HtJAGxyyGt975I8j7nHEPY64xxH3OOIeR9zjiHsccY8j",
"part_9": "7lcecTdGfLY4z96+fZtmqcIcx93Dx10qAkKZXeQZHRiENjv/UGTUEItsgeqxspd9zbIcJRG8tPi0IGps2NPTZ8sftB032ESiuCNq00rkEml8zOHLHZ7iFtF26YeeRdt2XdeO+koq8eNfujmhvFxQV+xa+/E81NW1xr58mG3v0LQRcty0kOrKOH9g2LUbt9rLDzHI2MObfHCL9/Ct",
"part_10": "/A8mhXjYKPW1vzL4Ww1+TXzw+CGqcRZXyDRzIBuElM241eZAVPi7d65aymoZ1uXNrb5eqiDN8uYe8DkqKgz/xoX17aF1uI/RBxe29sILJhh+MfrB+bH/7gX3OBSHH8p9l1/FJyvpnwzs3oZw+MlAy/X/atk9uOWb9ajBXnxAoHy8N/Tijxf0/6X+sjXqppXZIrhWfvwbLZp+z3AdAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/22Q0Q6DIAxFf8X02Ze9+ivDLEUYQwVnAc00/vtw0Q3NEpJLT+8lLTMo6oIVN0/BP6CAmYG2z+AdgyK7MrgwZrEaBroreVd+5P3UNkp7aVUfWwzybDMZ44QTKDAKrgfdrhugU4CEOBPEM+FHgNUx40jXaIU8uTgajhjjH16ujS74ZC/kVdxHN63tyY/TNx6ndL/C0P87T4pkIBRS1zZ9YDeWC+Tg/KuV8Y8pRFneuBS9hHsBAAA="
}
}
|
codegen__primeintellect___2442
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given array $a$ of length $n$. You can choose one segment $[l, r]$ ($1 \\le l \\le r \\le n$) and integer value $k$ (positive, negative or even zero) and change $a_l, a_{l + 1}, \\dots, a_r$ by $k$ each (i.e. $a_i := a_i + k$ for each $l \\le i \\le r$).\n\nWhat is the maximum possible number of elements with value $c$ that can be obtained after one such operation?\n\n\n-----Input-----\n\nThe first line contains two integers $n$ and $c$ ($1 \\le n \\le 5 \\cdot 10^5$, $1 \\le c \\le 5 \\cdot 10^5$) — the length of array and the value $c$ to obtain.\n\nThe second line contains $n$ integers $a_1, a_2, \\dots, a_n$ ($1 \\le a_i \\le 5 \\cdot 10^5$) — array $a$.\n\n\n-----Output-----\n\nPrint one integer — the maximum possible number of elements with value $c$ which can be obtained after performing operation described above.\n\n\n-----Examples-----\nInput\n6 9\n9 9 9 9 9 9\n\nOutput\n6\n\nInput\n3 2\n6 2 6\n\nOutput\n2\n\n\n\n-----Note-----\n\nIn the first example we can choose any segment and $k = 0$. The array will stay same.\n\nIn the second example we can choose segment $[1, 3]$ and $k = -4$. The array will become $[2, -2, 2]$.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.25
|
{
"part_1": "H4sIAFD8N2gC/+1Y3Y7qNhB+lVGUC+iyaPPHAtKqV73Ym9NKrVRVhLImGLBOYtPYWXa7WqkP0Sfsk3TGdgKnBbVFXFVLlDixx9/MfPNj7b4FK2aY5iaYBt/VouKP0vCy5IUJBsG6kYURSi4kqzgK4JSQK/4STKN4FA8CVYu",
"part_2": "NkKxc7GpV7Qjie1U+czBbDmtVlmov5AYKtaIBZZYlr6DR9EUiOLOpWVXRd8nkpmEbnHw1WyWnuczlT6oBVnPYiGcu8a1mrxCyENQaSi43ZguhDIdAYgWTUGyV0hyU5KD5puLSQDgrB1DPQ+iFEeR5yaF0Q+0GGfaByRUIdH",
"part_3": "rDa3hmZcMh/IwbdkoLg4oHIPmG0RuoGjhZ8iuvldtXbNFs3MAWqIct3kq4geh9gOArZTRN1SEsXy0iZ8UWemLIhyQvYPoANNwArq0JmtZDb5/wZob9ITHx45YZENqyVrEXUTUVoIFaLMmJplqi7cgKR37RbQ17geR4Z4oQt",
"part_4": "+F2omiJTiwNE5KvgK0N7SK2GtSsdrxmFOyvSWEub+n3KHeNsW809QOFVdTaQIkIGFdJUGjVXrUMagqJpYb0dqxLN2Q4FMgMRHc/Z+EA2uXi1HIf/vjtd+uxDzY66HKA4Gn+yEHl/Rq2dmqO5q3+YijZdjCULSKKUHwcLnlk",
"part_5": "NEXnrF1dNg6P6Pq2Mcd8YT1hDhLDbX61Hl0Qw/1WYJROBxFDhxlk66gLI6y4LmqxJKGleubHdn7zwqpdybW31EY5lyOY5HIC3UXiziNcow8vl0BMwjGMjiVih+81fFKGdzw8StcRbOpwpxv2/LhomXztitZmz2d4gDssboq",
"part_6": "l43ovyhK0wTeN3Wh4BOxjfRr50Aow2sk8PMDfpn/HXyJUhYTPMCtu8Y7nYZdSgtxvxdAS7GoW7BX7j96qplxhR6OI40QNWpWNjQPmJsoq4oiuT2pPa75Ltk2RcGpumtp5hC2TD7Hb1nzNay4Lar5ygHXygBmtTa9iux5qGj",
"part_7": "ibev2h3pUCx34/lzXXEcrN7ubwFWR3+IvsJBGaS+o0TOA+OItBvdcQyoyJOe7CZO21n9hN6a2Y978QunmAyE8cNnhZWr892mY5onVsfe0sumq1o5umxszGb8/Mx5nycaZ8nCkfZ8rHmXKtM6UF0cF0Fjw9PbnmmMv/8/lCJ",
"part_8": "KGrwXwQGK4Nuh7M3vLAvO54HkwhDyzzC89pgNUbWKvdIiXxl1mMeFZIuUR1UnYWG/W/B6asb9P+FGT83yFjJCqXEcTXAowsoI3z3UnM6BLMDu+6wBPrN3oPhzuB5CR8dgG5E4sVQYqodNMzsjpSp8mPpJmeKY6xnY3pPu3m",
"part_9": "JUEZ+zD/43Va5fhilTG4q1XgWG6f9rqml7SLaHU0HpQlnnZ3nVEZXexlYhUkXWzjzsfIRjg9k1OTi53MvJ7E5xaWSJdTbja6VtdBjZT7KdA1wivtoukyOPNzyRU1EtY9omdwbz1LLZsjfM+sDSPH9hU1EtbY1+HY80i6x3Z",
"part_10": "0NRxdrzd4jeTbPZ4RMWqK7HNstY892wncn9SYXqQxtRWZor7Ma5lYRsc2miPL7wTG1/IxmVgfU1//ifUxO8ocVzGpn4/B1VHmKyfymZZ1HSSG9HTpXlJIkQU72ZyvllbJeR1n9biAv8/pv6d60UjxS4N/z5u64e9/AhmVJxd+FQAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/4WR2w6CMAyGX6XpNTc7wfRVHPFGoyYGDGwXhvDuth0niYn5s620/TraDXjr2tRczrFL8Y5HHAI+mleKfcAjnAIqDy6ExgKrJFlQkwzJgpt8hrICFiCIpQ9N7gOFPaV5sdhmkMs48vgtogTJmm/QsuZdtEcU/NWCHASfy+Zlvn+ckz0FDIW8dKihkh/nU1FLZt8rI44CFXWkKVXJ7qe+89gMVFtEC8LT07IbmaDLc5Q7xSNIzUyb4uZNyqWWW6tuJ/Mjvlp2sXKdesQC+/h+Xun5u0TH+AHcr8vYFgIAAA=="
}
}
|
codegen__primeintellect___2447
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nDo you like summer? Residents of Berland do. They especially love eating ice cream in the hot summer. So this summer day a large queue of n Berland residents lined up in front of the ice cream stall. We know that each of them has a certain amount of berland dollars with them. The residents of Berland are nice people, so each person agrees to swap places with the person right behind him for just 1 dollar. More formally, if person a stands just behind person b, then person a can pay person b 1 dollar, then a and b get swapped. Of course, if person a has zero dollars, he can not swap places with person b.\n\nResidents of Berland are strange people. In particular, they get upset when there is someone with a strictly smaller sum of money in the line in front of them.\n\nCan you help the residents of Berland form such order in the line so that they were all happy? A happy resident is the one who stands first in the line or the one in front of who another resident stands with not less number of dollars. Note that the people of Berland are people of honor and they agree to swap places only in the manner described above.\n\n\n-----Input-----\n\nThe first line contains integer n (1 ≤ n ≤ 200 000) — the number of residents who stand in the line.\n\nThe second line contains n space-separated integers a_{i} (0 ≤ a_{i} ≤ 10^9), where a_{i} is the number of Berland dollars of a man standing on the i-th position in the line. The positions are numbered starting from the end of the line. \n\n\n-----Output-----\n\nIf it is impossible to make all the residents happy, print \":(\" without the quotes. Otherwise, print in the single line n space-separated integers, the i-th of them must be equal to the number of money of the person on position i in the new line. If there are multiple answers, print any of them.\n\n\n-----Examples-----\nInput\n2\n11 8\n\nOutput\n9 10 \nInput\n5\n10 9 7 10 6\n\nOutput\n:(\n\nInput\n3\n12 3 3\n\nOutput\n4 4 10 \n\n\n-----Note-----\n\nIn the first sample two residents should swap places, after that the first resident has 10 dollars and he is at the head of the line and the second resident will have 9 coins and he will be at the end of the line. \n\nIn the second sample it is impossible to achieve the desired result.\n\nIn the third sample the first person can swap with the second one, then they will have the following numbers of dollars: 4 11 3, then the second person (in the new line) swaps with the third one, and the resulting numbers of dollars will equal to: 4 4 10. In this line everybody will be happy.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIAFD8N2gC/+1aX4/buBH/KgO/nLfnGPpj2dYC6aHX9iEPvRzuDuhDnG60Nr3mRaIUkTrHFwToa9/vI/ST3Sfpb0iKlrfetrtIChxgR0hG5HDmNzM/DikgH0abwhRamNH16NtWVuKFMqIsxdqMJqNtp9ZG1upGFZWAAoak2oj3o+s4WaSTUd3KO6mK8qZp66phE9/X5U+CzE7Qti7Lei/VHa3rDf8DndtSVNRpfmMVjNy1RVXxe1mou664w+DB7Gp1vVIr9aeaDnVHpXwrSHdVJdqv6Duh5",
"part_2": "UYoo6ne0teixboNbeop/bATBxK6EWtZlOWByhpARGHYuFwLWreiqEgq63lXG29xSt/XGJLav9OmOFABOC2wvOtEJ9iRCq7a4L+USmyoa9jmtq2VYUU2fvSmDaBM6a+C3qp6j8nCANJ65zUr2hUaztaiNQWsFFXdOTO3IbASSDTtpdnZFTbOAYhBEopWkGLfjaibUkxI185ZI1pdw/pdK4QmU5PeFw01ZbEWR8u9Fiq6M/C/Q6FpJyvUsaUfO20o9mim9Je65fq2FSd6QnIbXHDEaqPdAm/Ez9",
"part_3": "1O2I06qq4LvCDZ/Xxw4BUL4qhu6U4Yi7gRmym93IJOXavFqVvO48+irfuETQgRsQNVm38Pt/c4ZZJ991AutWnByT6dU3rBcFsj112P8WCxdQ12D+0ZMsawkLlUV6JWwrnjrLRybUBKzSkDycA1dldB59Bzkvl0n0uVhfhHBMIbYSfKxqqerT8XBIaZXe0GPoZmde3IZ0HvGSRwIGtNc/iK/uCEYJUD4JU2gF3d13QrWxR1aBXM6PWGuHlNgcQjGUeb3ohNCBelFFqT6iowndf4uk3pm9qIgNX",
"part_4": "n/n5ljqPoFADB4zYyS/H7DK9VGXJcFUrxHhd63cpbbN/iFm3CJnmlnvHvhWo6YyUe4s3m4rYBrxEhNqqGOSPuYEjROKZf//FPCPx3EkUURdEV/fr3X6y/Y4DHkoWUDnM57b1pASebe+4U6QaxPNMCDCyM2PQA0D1uPsiPNI6sf/fCUhz9Lb+aMCu51nbYV/UI6et7TQZDBWfIoeO+WTuA8hlvmlpLPgtOUNtu1M9o14KsfUCEldZ2XxCjsksEnPke6VYP8v6yM8PEv9iStESUFcxriZOD61oV",
"part_5": "bx11T3eB5e8E5wnSQqvR9Xg1skyrO0ejdx1YBXK9ZE7uJXcPp+tj4ROp9KR+ONeTYzL6/l25PkfiXVeUDPA0w25/+5B918FzTGUPQIm9T8mLre8inMuqK41kqhdK7y0CB7tQh5MG4XP45/dFBW3ts2ipvFLJSsUxLVnLJXmlcvCDgkIGhYhyWvDofKiHRKqglkItoZTSocaMZs5WAMEb+FhGF57bQtqiI7OvB6XTKFK5GW7YCRVbI9pjE3CrQyfhXg+XPWuZwTvbdL36ThQnNOvbQ7+1gqG9t",
"part_6": "D0Q14QcW433mbdlJ1BVb/AsbX1k3qYP7RxlcQJL4e9E6DuStwYgoLLTgR3cQNpg5hi05wyfZDZD4bT2fsEvf1q6zh4iOr2BOUbqQaO95rrFlB5X9ya9y/E9Zl5ZAIP7gkNsAfQJdmGdd+iw9fuE3TNx7Klqb1+2UshTe7itN4dQAruzQ3OUzMQwp82GL01wzoejJ5LbIBjAIVuXnd1mfCCYTc185T/f4Cqmwz21v5a6y53pWhc3Lq1iivtuK7bYjWrN118ubAseH/RKrcsCB9i3Nlm4rBJ+G7",
"part_7": "GlmxuppLm5GWtRbifH64i9Nl95Rf7x/LTPzfNe8d68XYVZ+y9DZxcW+ri3pey0GdvUjK+u3Oid/EnwTCm1GVdFg2kzIa8z1U0pWdcr++PUa/tBvvbZ9mQvQWM1xO5vRHwlU5uxy8HYunwlX8PNqeGpRtLGb0FPeCiq201BzTU1IfgvIbv0uFVgETRfRa/pd6T+OxiowytWOG+Qh5bDmEvlM5LnLWImHlqV297w753wZfx6MO0cW7K446aHboe+oC+mP6Kh2Mzj7jdhE5wUp+XK2HYqFBHeQKr",
"part_8": "pTrzHBtBM2efPKYuyfJbNZnRtJx3bn1ONpMMhzjMzNe/NatQnm4k/9uSwvqwHUNiWG/TFfVYqvHvGX77WLl9rl6+1y9fa5Wvt8rV2+Vq7fK1dvtYuX2u/9a+13ogeXb8avXnzxl1PV+ry5Xb5cvutfbmtFAg8ej2xC0Do0asPWHxoBHADu7V643fKaIIRSxI3maz8MQJrdq52J4CddOfJ6OOE/neD2er02DlnF9nk4UfZTVfhnDpnsj+wHmd0BlsL2ORAHzA7p6dkIWa0Zy3GT0poRhktgeV8",
"part_9": "8HPMLDjh8ZNwRv3vPOAw/VjjzK2E4k9LgRjfk/knM8ngzof9+GjZTrqkNKEkJuzpZE4JSJnxSAp+RpTiZE75iVM7uyQwGuSKoXZ+B8JSkrCZkyezz/LhJ6f0afhngIf1Ec2QZ9BtQcmCzcV4FjacnB0sGTLC4jhiK5zf6DDkn/T0yQbPvH8W/ZNzpp4Ef4aWarHbPMAKw7NpZhBLrgbLuQ0u5rK4mOLsP+FPetgh/ado7z1c7+TRO5Hx50k0W0Y5tpqTlnkepGWQFkGaBykL0ixIaZCSIH263",
"part_10": "WgBZ+k8yfIY4X426Szg/4PfJxVwuZhny1k0R7f2UhqkuJeyPEiLIIUVWViRhRWzsGK2OJuPfsWcPp/0JH4kWJvMljn10jxIaZCiXlosgjQLUtxL82WQsiA9wI/7axdJkNIzPoK9xfwMluB3kQ8wPyUf6TLN8nQ5x1nwOClbBmkepFmQkiBFn3aDx/lyhkShn/bSPEizICVBih4vfeKOlERJGqVz5pST4iAlQUqDNAtSFqR5kBZBWgYpf4Bxn90vM+41/886fdMp+a4To2vTduLjvwAbzKlemicAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/72TS04DMQyGr2Jl3UX8yKtXIYgNCJDQFE1nFlXVu+OExlMqsQTJUj47+e3Enjm71/mwTs9Py7wub27vztW9T5/rcqxuDw/Voa91CuSJPUcPg9CIjNhIjIJRNEpG2aholep2oAWV0DxuHgEDW4haCCFvgXZFzsAEhCACFIEEMLQIC4gHRmBuhtx3M2hS9IB67C6R6oMHQd1o51SpSbkLyHdl6FwAY88rvZi6wRKJUtJLa9BvD2uYUwxZvPZlEBvhoFCMkpEpgimCKcQUknrBx1bxsC43k/yHIcL1pddVW9+a/O2UDbWhRK1rPyx0y79bAbYMvg9Dk3A3y6CzTcPKvbXPgexuEW6uNDoa4e9Ip3JxO3dcTh8v+qfNqy6XL+qj03uBAwAA"
}
}
|
codegen__primeintellect___2454
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nInnovation technologies are on a victorious march around the planet. They integrate into all spheres of human activity!\n\nA restaurant called \"Dijkstra's Place\" has started thinking about optimizing the booking system. \n\nThere are n booking requests received by now. Each request is characterized by two numbers: c_{i} and p_{i} — the size of the group of visitors who will come via this request and the total sum of money they will spend in the restaurant, correspondingly.\n\nWe know that for each request, all c_{i} people want to sit at the same table and are going to spend the whole evening in the restaurant, from the opening moment at 18:00 to the closing moment.\n\nUnfortunately, there only are k tables in the restaurant. For each table, we know r_{i} — the maximum number of people who can sit at it. A table can have only people from the same group sitting at it. If you cannot find a large enough table for the whole group, then all visitors leave and naturally, pay nothing.\n\nYour task is: given the tables and the requests, decide which requests to accept and which requests to decline so that the money paid by the happy and full visitors was maximum.\n\n\n-----Input-----\n\nThe first line of the input contains integer n (1 ≤ n ≤ 1000) — the number of requests from visitors. Then n lines follow. Each line contains two integers: c_{i}, p_{i} (1 ≤ c_{i}, p_{i} ≤ 1000) — the size of the group of visitors who will come by the i-th request and the total sum of money they will pay when they visit the restaurant, correspondingly.\n\nThe next line contains integer k (1 ≤ k ≤ 1000) — the number of tables in the restaurant. The last line contains k space-separated integers: r_1, r_2, ..., r_{k} (1 ≤ r_{i} ≤ 1000) — the maximum number of people that can sit at each table.\n\n\n-----Output-----\n\nIn the first line print two integers: m, s — the number of accepted requests and the total money you get from these requests, correspondingly.\n\nThen print m lines — each line must contain two space-separated integers: the number of the accepted request and the number of the table to seat people who come via this request. The requests and the tables are consecutively numbered starting from 1 in the order in which they are given in the input.\n\nIf there are multiple optimal answers, print any of them.\n\n\n-----Examples-----\nInput\n3\n10 50\n2 100\n5 30\n3\n4 6 9\n\nOutput\n2 130\n2 1\n3 2\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAFD8N2gC/+1a224cxxH9lcq+ZAmviLlfCDuAgTgAXxIDdhAEWoFq7jZ3R5zpGc2F5EowkFe/+xPyZf6SnKruGS5Fbmxt9BJgJVDs6a6uy6lT1d2APs7Wqled7mcXs+/botKXptdlqVf9bDG7GcyqL2pzZVSlIYCpwqz1w+zCD9J4MavbYlMYVV41bV01rOKHurzT1G813dRlWd8XZkOres2/IHNd6oqGjr9YBDObVlUVf5fKbAa1weSu39bmYmmW5tKY+k6xA9Tr1dbUZb0pdEeq1YQ5RXfFqocP9dBRpdrVFiv1YNZ",
"part_2": "WOTTq/px+3OodFQgKpnrNo5pUWVLXbHULZfUNbYdKQR1CvSv63R/Y9LeEtV4NrTI9rSCv17Sc/bl4d9v1rfpjR9+XaqWXM9qqjiDY9prNFuaWg1HX9dBT3fRFVXwYo72ua1nsdl2vq3NiMz+yDxKPmdZb/X6A7Q6DlS7uoPd6R6a+P6fvFEJ0y1R0tNqqFl7rtvhgpfr7msxQXeu2u6DV1cfiJ1KAo5HRr//6RfzoIM1R83gDvBr+uCu6AlB2dL+t6b4APqu60phWHFU3WVUO3b7uFTAcKt5c1QYY9wy0bO0aDbHCiOQjjg",
"part_3": "vobPHZ1IYJUe7OGYJ/aLpFdJBVPUjTkt6LciGpspE0um5KTfecEeQQ/hJ2SERgJ/UK7BL/GM5NLbDXzheWQmQQ0Hfa8NIL3t2AxDJZN1amAgRGrPjZheexOl5elXX3uCxB/N3A834wYFi5W7CUULTciTO31rnuudFz+ssYsYgs6N7B0T7JWaUeigpg2+Qy5iMaSNcK5HVoFND4rYOCp7fqzvnh5KcYBTObfuzthbV2/+UN7eqBt5saGSkYUZRni9rUph42zlXJ1SOuokoiN5KziVClZh84L0AHQZcMUKOY0lwvG8Hvn/UAZ",
"part_4": "aq7Ba0vaAPWW6QcbiPrxtJY0FqvijXbLh7J0nGC1GqlG8vT54vYVRYGwdeWbgKtkLdRha0gzGxV0+xEw82wH8m96sZEiNNL84r/XJpm6GXkKhqYtSgVseTqrGAZ0N/0qjCdbUfIo6G5T7/+/G8M+F/f87yzKeePuZ5CkOyN/khrM9jKhjrXb12TENuTOW4LzuTYFxauKTj7T+aeu/I5LcOBWLzqt5/XNZgT91ub+J3V/rsaCCNu9EP/SdAjxrdjjLf/FePDFcr6S9V9qv8WrQVHwKtON4pPlvUexO2Vv8A/wYLOz8959PF2",
"part_5": "gro9gPHBEhem7tX4Y7fYZ+Hfhn6fhpc2jj0mNm3BjfMJFaoFdS9gYWsIEU3Ee5pAmzluEhvdTy2l26/PA4kyzo3KkZZt64mw1dBNRSKeHkb4k+Th61OnJ5+fitnexQeDBpb7XfSl885m/zkMri21wodOrwZcHdD5nS04IVcCbqqCjj/yqm7XcAUftjcJ0+W4ko7nhKRZCGKXN+4oYZlqKPuCvZV7BdKgTHcPMBYOU2V2Lsgn7em7B1VhV+eoId1qacKl8T2KvaUJmIdLE1PoyXRECeW82zJKBEIrh3UKxpKzLU0q9xodoke",
"part_6": "iBR+mRbeth3Lt/Npxb+/qcrAXuZpla1bMf/+Ko66b7ozjFZH1tBqnhQUEF0h9jrtnq28AhlnxVdTQN0yHubgxPztbmgfMvH6z5JOYCsYS5bvRc3OGuyTRCjBBoFINtqCTuH3nXVMWdj/RA30FFXMcY5AuzqDr9pmVFjNl0fXzg5og1EEIkL3f82h+J1rVmXiGW0jb6fW8q/niOH84s06yh698Hg0YcX/g1JActTR/t6APsl2DZporYt7afUTFDa3o62/oA31Ng5uz+t6NH6zyA39AtqE/wZCTa183b6zD/PXegqCAFyPAUx",
"part_7": "1P3S2N5HNeajN/f4bOceYiKxb0Tvx6b4MQqYK+IjTBd/zrDLkTdJA33J4Lg2+X6tOT4fRkOD0ZTk+G05Ph9GQ4PRlOT4bTk+H0ZPiST4ZRSTe7eD17+/atvSouzen58H/0fFgaZG72ZjHruaTwZHj9cTnrdw0u0xe4YguRrhxFZgvMCKZ2MVyOtB1564jLzB2pC1rJvtryVzZaDlsSWxazFE6832+bN/qyffx5bsatk3+c+uA31Hvkfb7iwGLmW6xipzw+4H88ufFFzPjeIZy8Y4EK9nI/GvwNU/+TLbFho8qFQjwXU+AdI",
"part_8": "lr+aC44hmjhXmChIBlT5hgeUkT+QcuCOoXHplAUp2GOgkrZahBSErPlFG8fPxL7KTxKedUPPIpCmYtDymSUJMi8n2CUZxn8ZB8yP6XEi3gELXE8pSoKfYoCABmkUI4fqPFTj/I4ojROMR/g98vlnFCYBKwpIUsH9jKnVHoAz6cjEaPPh4FNBn5CWSLpzqFXkp0gpiyU4oljSiXiLEHsKY/iPKI8kFHGeOSCJXYE7ALiCYN0Cj0PgGJGUQzPPfzGtw9NCcIHKkECyET6eeQpIS2C9VhCYkhCDyXayEESCiTJcfxLEE3i8eYU",
"part_9": "LVUCTDDyLaoSLrITIio/RFkgc+GL7mIhyfLJH198C4/JioCXAq9EuASyxIJ2mGSUi4mcGRmLgRjUitn7IMmBE+9gRxNhLsv6YCo4F8Q5CEtJjiAi7El9ZBNOesmL0eCoib1cIkj3sI8nCsbH4C2MirBVVAtbsgi8CRh4VGBwoK9Z+aP6mmSEcyMcztFfQukwUURRxB4E8CCV1TxC6nJXr7k0PwAX+5YEOIpjEULd5iwlarIAlAa6+PFR4UkATvpACFBnBys6iLJA6BsKqAxkJkQJ3aEaCOvj4wgdo/kkvuUxvBBfkwBNKpw",
"part_10": "aUgLEI5RelOZgFNzNQH2wKwwSShBBwEP/IM0j23fjKSfhMWRIpdHAeCouAdcsljk0pFBomURoSELklLunJCLymCxC7gwHQBy6MzGLkgPksdLJsTcVP2E4E9cMIi+hFPUV5Ohf6GdpdOh6ZPfYM+ozzfLGEIzKJSYuUz9I3LESyJkLLuJEsdzOyZ5XAS8GrurDDNsBGhYBbAje83oMhz0s5NEhZlpDvmuvmQCXTPfIQNpAfCyUob1KWKbjHKDoAHbBl7kyyVPC8SM4fGXy9m8Rb/j/CnVXgynwEJ5d9O2gf/oPaEjzimwkAAA="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/21SQW7DMAz7CuFzD7ZkK3a/Mhe7bNgGDO3QJoeh6N8nOYmbdTuZESWaonN1b+fTdHx5Hs/T+O727lrdx/FrGi/V7fFUndR65DKgREN5CAjUkPeg4hUlnxCpKCIuiGwDZCQpsjJnHacEJaMHlwTjU8bglShRW6rboTobIARvqsErsLPh3sIbipHsemTD7TvioTWpSwmGRJ3nYnaEMgJ3XSFClAFxKCiZkLOgSFaPAokgMhh+eVwNpGbAuNT5pit2qyz16AVDYEsL7HXr+I/aLNfybLUE+rN08pt8NES/7B2hjlvzwbpP07h9P9D8YAGx9VpaulnLaw68NLm7qbA+waam17ZdwbOHuzcEiXMx9Rlu+qtaehgJSzizWNcv9zupOesM+67AC3O4uZ27jN+fr/rPnic9bj943TvYywIAAA=="
}
}
|
codegen__primeintellect___2456
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nEvery evening Vitalya sets n alarm clocks to wake up tomorrow. Every alarm clock rings during exactly one minute and is characterized by one integer a_{i} — number of minute after midnight in which it rings. Every alarm clock begins ringing at the beginning of the minute and rings during whole minute. \n\nVitalya will definitely wake up if during some m consecutive minutes at least k alarm clocks will begin ringing. Pay attention that Vitalya considers only alarm clocks which begin ringing during given period of time. He doesn't consider alarm clocks which started ringing before given period of time and continues ringing during given period of time.\n\nVitalya is so tired that he wants to sleep all day long and not to wake up. Find out minimal number of alarm clocks Vitalya should turn off to sleep all next day. Now all alarm clocks are turned on. \n\n\n-----Input-----\n\nFirst line contains three integers n, m and k (1 ≤ k ≤ n ≤ 2·10^5, 1 ≤ m ≤ 10^6) — number of alarm clocks, and conditions of Vitalya's waking up. \n\nSecond line contains sequence of distinct integers a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 10^6) in which a_{i} equals minute on which i-th alarm clock will ring. Numbers are given in arbitrary order. Vitalya lives in a Berland in which day lasts for 10^6 minutes. \n\n\n-----Output-----\n\nOutput minimal number of alarm clocks that Vitalya should turn off to sleep all next day long.\n\n\n-----Examples-----\nInput\n3 3 2\n3 5 1\n\nOutput\n1\n\nInput\n5 10 3\n12 8 18 25 1\n\nOutput\n0\n\nInput\n7 7 2\n7 3 4 1 6 5 2\n\nOutput\n6\n\nInput\n2 2 2\n1 3\n\nOutput\n0\n\n\n\n-----Note-----\n\nIn first example Vitalya should turn off first alarm clock which rings at minute 3.\n\nIn second example Vitalya shouldn't turn off any alarm clock because there are no interval of 10 consequence minutes in which 3 alarm clocks will ring.\n\nIn third example Vitalya should turn off any 6 alarm clocks.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.5
|
{
"part_1": "H4sIAFD8N2gC/+1ZzW4bRxJ+lQJziITQxPz/CNEeFkiwvngDZJGL6ZVbZFMcaNjNnemRrBgGct17HiCHvEPueZQ8Sb6qnqFImoZlgUfSBjnTXV391VdfVbfh96O5cqrVbnQx+qGpVvqlcbqu9cyNxqNFZ2ausubKqJWGAYYqM9fvRhdhVGTjkW2qm8qo+mrd2NWaXfxo6ztNbqlpYeva3lfmhmZ2zj+wua71irqW39gEIzeNWq34vVbmplM3GHx",
"part_2": "wS2supmZqvrvTzQPpO23Y4qfKqfpBEbC2ZEjVqlnRrLaz25acpXt1q6lb43Flm8beT8gv37KjBn5amnf8S/qdmrn6gazRBAid06TMnKqWZkvVYE431c96TtfepAIvN7ohdfW++vDnb3/98iuZbnWNEbvYrF9gEV7mprpZOiyh+2U1W1Ll/NaHMF1rUNjKPKNSTqiRUQkb3nlgC+FOFPdLWw+zE2LWBp7uq7qmuV5UpkJGHzYEVYthbWtXWIr8mF",
"part_3": "bPOlfdDY5ahlFr1Tq63SVanAq4AfGEflCIyDltWCoAi7UDBnZdzXXTgsL6Yc+VULPjawB2AyiG1kiAnQsB0OWE/qVpbnVrvnYbv4c8tk41Ts83Pq/1wjb6oE+hE74cotbtk1BsMwyptBbDDXaTsJGne2Wc6LGttV4DH3IAfmrLucVuxrottU7oexQU2c4x89VK1Vui2olto/6l7Wps1zUGNovdnYx+53i7Cb2y9zKy40OBBl4IuNZ4sUzNC/68N",
"part_4": "OvOyRMPfV81yHxdQfVMjmJ9umWjN0WA+htDOBzPLZ2F9Nf/f8cDfxv5jv78Iwz+m47JT63kGyPZ+X7hbOMbD+mYV6ykluf7sL9umTFOCnPGGH/UbLgHstX/67SZaV45r1qkdeYeMaurEFtcRWOaTCb89N58GNBLVT/CfCxdPwG/qm6HIrSbun7hljvFLOXRSFW8khg96V5J8Kma68o1Ci3ANpDvZJPWGhatWNA/dVNLIxp2Ef2gFlv01EbwDWW6",
"part_5": "k8N/d247if71c7LaqdYnaUukPNna97t3arWuddvvLFKamphiivgnpfARztTIS2+DqYBijEVUUFhQtGcbbNnmlLO/HG4TyCqD32jbNtuyjSjiyZB973nboH5lnd5w9dLQQjSvfSyfZMRb7WRcUuRbsnKDQuJJ77b1Mj3slzvZxrUy++fCTHWtnKVQEKvIWNFyc4d0Io/gTjp3L/mhc29kEx/o3CLNHppbVs38sxEzrGzHk6z/z5KbAQusPxHQduc",
"part_6": "sXwT7YLvBzRobOh5o0Cnrzh8Qlm0tp4T/cKdqN7eG4ZIg55wWFDyMK4Se4PbR6AXYQLi4apjxanxLlyid1p2t1PoMW409qLPzSeuaas2/67rC+/n51KgvMp60tsEzQ5zZDlFckihIjhf/cot7wcw/IkD5BfW19kcQfYsj1Jypc9xlCB+cu+q1zLzhk4MPgldw0M/y5w4+BpPHUe/S7zW4FH7Uaxl8Qy+w8lt02S1X/AGmby65orYHgQLj/7ik2z",
"part_7": "1r/nwl+TpTY8EwFvfjrjn/2HKz96UE8bGB5+zj/XtgLz6a8AE+Lvg8XTtuPOV++dT4OATDOWQjeYVk0Horg/deZaf76um+erqvnu6rp/vq6b56uq+e7qvHv68OTtrRxevR27dv/WVhak5319Pd9Sl3191tDr0N31MDeY3ejEeoKQe5jV6/n47cw1pPRxc0HYnar3odj8YYEf34Sd/7huYHX2JgfR8SCz/6YUxPd9o3y71uech58OXOfXfdb6+Hn",
"part_8": "Gdf7ty3Y9+Pj4Q3ZJTs8ljsRghcHH4i7Og5CUt6TiM8pZQddBw/J1mpF0LIoPG3ZJ1BE/mx2IDSvB7igErIIYHyEgQRQxU5hZ9K5DO0wfADSqZ8GYgKyiDEgLICgRWyYUBFRGVGcU5JeTT1cDpSZjCgCH+RfLCXSXgIN+XS4pAj1AHCPd6+KW8X8s5SwahkDIWgGEqB8qRvMLZIijs52r4Zh8M6iKI4yELsmuYFdk2KJE2pTLMoKKkMEkYXBkWQ",
"part_9": "UxHHETIRJUGRZVSWWR6DmSTNS4qzrAzQIMokRo7yKE8hyCCE2ygvkgzA4zT5RLLC57SPgGUQctxQQSQYsQkYigCtAHFZggoDcXEOWHguQWmJGCCuIi0oRyBJAmVl8JQh2SV4j6OjsRsETG/ES8OEsxqwXJmIgtOMzUpwFwMUxJSjcaVcQzEBSsbVC5SgEcMMq0D6SzjEyhgTPM/W7BbigDvOXkhpLCzkXPWYTxA8m2bcDAo+KpCZnIs2zHmcvUE",
"part_10": "ECQsMx0cGtAHrLYTeM/aRsfJT3gW+oXopgzDFD0PIwTFoTzDH8GEGAXBSGBr2DGAL0CmLgxIMZCwWoGUSROWcMDYMJXGIEnEgJSHaCUgCN7BANkNWGasKvjnZHCz2R0T54fYZPqO78QHHyxIEEzFFICJL8/TwDslzDhNogj/9sde/He2sCvrTOZLTOpUuVXCj5tKQrgLOEslgJjkqWBbc6cKjVWXYk/iE2N7wf3O3V52p8E+V0YVrOv3hb8tvr3MnHwAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/31RQW7DMAz7CqFzD6Gd1HG/Mhe9tNgGDOmQ2oci6N8r2UBSFMN8sUVJJCUv8jlfy3Q+5bnkLznIkuR7+i35luSAjySuwwCX0uTg0et7j4AREexAgg70YA8O4B4M4AhGaJujdiXZIYnWwSJ29bzgfcM3xCSGWlo5VHU0Yq8moom4AX0H76oPxrVR4WozwDWbayZo5I2ROoGZjQqYy7CW6BDNWaUg3n0G1WrktgOqdttJkqOlryW/bIybNP94baz+37rGcnzITm75/nPRv5mLXo8nQQe2LLMBAAA="
}
}
|
codegen__primeintellect___2462
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nVasya likes taking part in Codeforces contests. When a round is over, Vasya follows all submissions in the system testing tab.\n\nThere are $n$ solutions, the $i$-th of them should be tested on $a_i$ tests, testing one solution on one test takes $1$ second. The solutions are judged in the order from $1$ to $n$. There are $k$ testing processes which test solutions simultaneously. Each of them can test at most one solution at a time.\n\nAt any time moment $t$ when some testing process is not judging any solution, it takes the first solution from the queue and tests it on each test in increasing order of the test ids. Let this solution have id $i$, then it is being tested on the first test from time moment $t$ till time moment $t + 1$, then on the second test till time moment $t + 2$ and so on. This solution is fully tested at time moment $t + a_i$, and after that the testing process immediately starts testing another solution.\n\nConsider some time moment, let there be exactly $m$ fully tested solutions by this moment. There is a caption \"System testing: $d$%\" on the page with solutions, where $d$ is calculated as\n\n$$d = round\\left(100\\cdot\\frac{m}{n}\\right),$$\n\nwhere $round(x) = \\lfloor{x + 0.5}\\rfloor$ is a function which maps every real to the nearest integer.\n\nVasya calls a submission interesting if there is a time moment (possibly, non-integer) when the solution is being tested on some test $q$, and the caption says \"System testing: $q$%\". Find the number of interesting solutions.\n\nPlease note that in case when multiple processes attempt to take the first submission from the queue at the same moment (for instance, at the initial moment), the order they take the solutions does not matter.\n\n\n-----Input-----\n\nThe first line contains two positive integers $n$ and $k$ ($1 \\le n \\le 1000$, $1 \\le k \\le 100$) standing for the number of submissions and the number of testing processes respectively.\n\nThe second line contains $n$ positive integers $a_1, a_2, \\ldots, a_n$ ($1 \\le a_i \\le 150$), where $a_i$ is equal to the number of tests the $i$-th submission is to be run on.\n\n\n-----Output-----\n\nOutput the only integer — the number of interesting submissions.\n\n\n-----Examples-----\nInput\n2 2\n49 100\n\nOutput\n1\n\nInput\n4 2\n32 100 33 1\n\nOutput\n2\n\nInput\n14 5\n48 19 6 9 50 20 3 42 38 43 36 21 44 6\n\nOutput\n5\n\n\n\n-----Note-----\n\nConsider the first example. At time moment $0$ both solutions start testing. At time moment $49$ the first solution is fully tested, so at time moment $49.5$ the second solution is being tested on the test $50$, and the caption says \"System testing: $50$%\" (because there is one fully tested solution out of two). So, the second solution is interesting.\n\nConsider the second example. At time moment $0$ the first and the second solutions start testing. At time moment $32$ the first solution is fully tested, the third solution starts testing, the caption says \"System testing: $25$%\". At time moment $32 + 24.5 = 56.5$ the third solutions is being tested on test $25$, the caption is still the same, thus this solution is interesting. After that the third solution is fully tested at time moment $32 + 33 = 65$, the fourth solution is fully tested at time moment $65 + 1 = 66$. The captions becomes \"System testing: $75$%\", and at time moment $74.5$ the second solution is being tested on test $75$. So, this solution is also interesting. Overall, there are two interesting solutions.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.625
|
{
"part_1": "H4sIAFD8N2gC/+1b7W7j1hF9lanAAlaiVcRPkUb9IwgSIECRBNhF+2O18NLStcWaIrX8iNdYLNCH6AP0WfoofZKeM5eUaFn75S6K/pDiROLlvXNnzjkzc0kg70artElr04zOR79V2cb8XDQmz82yGU1G122xbLKyuCzSjcEEDGXFyrwdnbteHE9GZZXdZEWaX26rcrOliedl/ruRZm3kuszz8i4rbmRZrviFOVe52Uhb84pTMHJTpZsNr/O0uGnTGwzeN+uyOF8Ui+IvaX2fSp7dmlqa9FaNpFUjWSE/lCtzXVZL3FmW8Lhu6qn8dW0KSaUq22IlWS3l76aaiLVi3aklzXOp26tNVtcIrKYtulLf1w18oyH1Lr2a0oMXa1",
"part_2": "MZSfGvUzhSl3lLOOqJrnEy51mzlvKaVxup12Wbr+TKqBWzkrIQJ73MHL3mms54WZidKdE/u4QxIh7HxU4GUa2m8mK9n1qrH39rVzew3bldVitTyTXQ12VNST91We/2rbPbF3ADrxpb3K2z5druubdeZ5s2b9LClG2d30/lx3S5D26ZFnZ+2simxPeDIDCYSgPxKGjf46q412vM3ZiiEadxsCnYqXF96BCpKspGQ+MwF/emJ5L1uKiosmrgsw2c429a0yJg0K5YcxFum7SPEnBlxbIyqWrPomZD6+6vIJ8/G2y1hjM7++sUYs5WZFopL2gYE66MimRH8941tWbdOgi/yaC8h4Pyrbi94c6KJb6Tw9EVnqNx1iWWkOmhv/h9",
"part_3": "3eb5fe9a2jxeT0VO1ER63QCGZs1Z6yOsbDZmlaWoBqCjQd7Vuykp6ILEdhsr7T9ARNlKR8nxft+J5IosNYnsMG/TZQObzsZ56O1eilf3lgi7vtczBlIIcauhLkbPH6TsuTgr54+LUQ/klrXkLkN+DrL2Tu1gIm0t03zZ5qniVDMAx1nJha0ei0VurpszdzZbLJarslksrqt0+W7z/l3xfrFA1Vs344njcFVnU5edvR3DAhZf52VZvXsLuGfTkCt0wLEh9FW1S8NNuq3FoFTdCwSaM4kZQGGQvyrdxtyYaroviHA8p519GdNJVUdOdt1hrZsN+T/blph+ld9PkG/Fs87y2GZmMyg1xzS+y1xx3nQC4pKejzq9r4+R8oakTO",
"part_4": "WnrJtftJsrm3xDn3ccaZi/5UhUw5pgrDyRvkuOqKOsUtk2N4N6ljbYdNsodKgVw1Kxx+iwWFjV1+kAH3QU7AWxF0sz6WdkRdZk4MVOGk8GhRe/7vc77vW7Ko0taRt6ZrlbFM/4+bnYto3+6vpL52ieoaCylaVwQJq7UkAWNmYBsjzV2oOIO4v6meNSaEDJfkGqM9DSj97uRp0xs7fQFsz4HpIwbIXpI4oedw4QtsXZAG6hRfQRdEXrYQh09kgI6aULZC+9CR1EZtW8KgbxoD51vofwfZez2kghS/OmHeTIA0/rYVceJkfN+ag8Vcs6O2Tj17YZ0mEvLcEFClPn9r/++e+//+Nj6t2DODT+49t0A53WnXllflF44i2KICE1",
"part_5": "+y0XhcuLbkrAKb7HKeL74g7neYN5biAhZsfiJhJJIuFMPKyQwBM/lsAXPxLPlSCQaGgitD52Xv6CLNsBsKvh+wwyNoqpfH/QTGaOXJXD+mq7RC+axwuCxDnWxA+a1oStLX20dBo6wwb5sUq16+pOOPuCSoXJ7B9nV2aZtrXZF1EedY42KikhForvrhxP5Xk5+ZCHA7FMH8Hczf8YznvU+mAONvkk9r73edgrduusGvj/sPdPPgtLL7Rl/7EbPMEE0xBtMox6Th9uWB/lVPmE2Yf78/Bjj0ldKefttj44xh0wIN8fHHwexvupQ5TGgLS8kKh357psq0EmfNJEFPLoRwuRPa33ATHwJSYdBXWuoHZntwOL8+BLEkTBhLletA",
"part_6": "dgpTlS8AFiv+J4glPHpEsKPlmwRX24hb/Qxsliekd6UHzrBi1Ifb8v2/5haVvBBAf2Z0nWaswtWan4zy/lHe91T5X9QyTtVKZpK5vueMQ0UzydVuYaDqF741E022zLSlvwmnbwKHELxHHaOst4JlXvzsbTeptn+B4vihS386xuzj44B5MKuHMhL5+5r+QbuV3Ae1zNuoviLS9R1zf2C0Yq3v8JiBrtvhnPMhWedc1ZMX7F02OGVreRPwkfeQWfg1m3426cHxztsP/L7JX84YLdIVQczrqxiwt55gpbfHeVvrR3Xg1tPLLzzD24y89Gvr1g4zlcxQAvdr4OP3sn6Njj+9YpPac8vGmAzUfscc8jd+HIYw8H+ww20ZH9ZB7y",
"part_7": "zzy01m8YpRRj+e47DOCyGH8WBSsGSaOHqILtHnHs8aJqzaJQhZ/V7YaKqsZjiFTVBIE2FQ5KuO40fXp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp7cnp78r95e7JzYnT+cvT69Wv7MLkoTm9STm9S/v/epCwKSHT0ajLS08vofPTy3WLU3G/NYnSOAqAZc9nlAvJ+MVIN2ps8RuzOEdC03i9th9cJro6+n8jn2wzU5vDgccyw9+WG9aDyuSeVY3uGX76nBQgbfQig2RPiiNU/zxNE4oo3F3/OkDAOJoI5f7iheCHu+xJyDtAM5l8NR0DE/WHdFdfj1r54UbdnoL4cB9B/wmYwTtJ8Go4CSVwJXYljQf",
"part_8": "hRJCATf4nHcRcuiFKJP1wnx5XjPgXymfIYAd5OJxAmgA8hIokjCcOjWwVPUH+g4IYIAowC4DnI9ABCKIkvEQH3FeaZFXCiw1AzZpMA4BGSblJDWUD0LubGkIFPS5LEEvoyx9SEjLlzmQcSzxlT5DE4l6uxcoafhDTwjgvnCdkAf0kmsJtLAgxnEsXcC0HbFJG5VRR/WWfmdBUwYzqc8QPG7ksyY5jAPyT3uA1TuIFJQAfhBmA/JCYAZ55ITHBkjghxy1pH5AG3BsoI/kPJETxFKoyEUSr487kyiMaIbRADZOvCu94H5nLAhI1jC3rCwEnezCUlEB5Ywf3QIxZu0NHs8cFUKWUGRCxh7gw8SuSzhLmYCwlhyxj7qI5cr9uO",
"part_9": "lzCkQgZykQqAQ556G5NyekzxMNcUIG6PBMS++h+X1ODLs3rEbtAnaMVMJiLFqYnozmwIEetDYCnmIroLLl1vbjXGnTiUKA4zyphLGW1yvBQnT2CmK8Lz5KtVYpdQsxYiwzQtE3LgMbfCgPwBWjCC7EOkTEMMEmFMtpwDptjT9ItZ4MKgkyUoBfRId5DiakWNXe1XAWWTQEqaFSojohmrzkOdiTkAHL+x85wNAIDCPLSPxHc1K5IuSag9jzkAoyhu8xmt8M9n5sAJDKIchFrqYcC2EvrEwNlfmI2Y52slgSPzTiGQFYINlFekJTKQsyKmJWy63ARRIKhAJZMc747h7KkJyIXwkd4BARABZ4mXeu7ZFND6Fym+eiYAi9AmnG",
"part_10": "eJ1UoD1YI4qNHTEuNr+NA5tMvII60gWqotnoEWLeZWqFk51/TUQh0qFGAAHKNshcoQgGUKzsg08hyEgRFQC/4AIIpjR4qruPqUE5hCIbNlhaVtRhBjVQAAj7UdMe9jYo46SXA9sglpJloigTuaQPLhQ1sSP6G021MbgQU+CD/0v1qW2a4B1shOpIcZi6dVOVvE1zpugGTW/EC0brHSzlQQ84ECgp5yT1N2pozGPX+WvLhnK1FiIqXhuJdu9KRGGqrA4QJcHUg7UEVbLVsVR73r9twSq053Co0VSF+xTHoZBoMwZr30ol5uficxisvfCwod6zgL4X/RRPVAd0rhL0/hLs9e8X81qC/bInvTmtF5gyfA9/8BY9EGhaswAAA="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2463
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nYou are given a permutation p of numbers 1, 2, ..., n. Let's define f(p) as the following sum:$f(p) = \\sum_{i = 1}^{n} \\sum_{j = i}^{n} \\operatorname{min}(p_{i}, p_{i + 1}, \\ldots p_{j})$\n\nFind the lexicographically m-th permutation of length n in the set of permutations having the maximum possible value of f(p).\n\n\n-----Input-----\n\nThe single line of input contains two integers n and m (1 ≤ m ≤ cnt_{n}), where cnt_{n} is the number of permutations of length n with maximum possible value of f(p).\n\nThe problem consists of two subproblems. The subproblems have different constraints on the input. You will get some score for the correct submission of the subproblem. The description of the subproblems follows. In subproblem B1 (3 points), the constraint 1 ≤ n ≤ 8 will hold. In subproblem B2 (4 points), the constraint 1 ≤ n ≤ 50 will hold. \n\n\n-----Output-----\n\nOutput n number forming the required permutation.\n\n\n-----Examples-----\nInput\n2 2\n\nOutput\n2 1 \n\nInput\n3 2\n\nOutput\n1 3 2 \n\n\n\n-----Note-----\n\nIn the first example, both permutations of numbers {1, 2} yield maximum possible f(p) which is equal to 4. Among them, (2, 1) comes second in lexicographical order.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0.1875
| 0.6875
|
{
"part_1": "H4sIAFD8N2gC/+1Z/U7jRhB/lZHvqjqHsXA+gEai0vV0VZEQoOP6R0VoztibZO/Wu77dNQGhPEDfo0/WJ+nMrg0JJC3nv1opBhHvzO5vZn7zkZW4D/LUpobZYBica16wY2mZECyzQRRMKplZruRYpgXDDSjiMme3wTDp/rAXBUrzKZepGJdaFSVBXChxw8",
"part_2": "DOGEyUEGrO5RQyldMH7rkWrIDK0Iq2oGSq06KgtUjltEqnKLyzMyWHIzmSv6kKUs1gym+YhBRKpovKpuQRlKAmIKvimmkDSQTdCOI4jkDGcMLs9wZyNuES3QjLDqTmiUumKoavneoIRiNcje85viaL3+/lopF8RglvJAqNp1ZpYuIePV6EJZ5ZREAfsINH",
"part_3": "I9wlcmUNiT4vOq8phJ+RL2dbsFueUbjljGepEHdQ7NrZSkgYkGByilIJXLpTmBcSL+0yMEtvGgKL9JYXVQGlMoYjuXCTiorRCYotJgdGcpeeY1lW1r2R6CNBIwieEEQSHuC0AVMlbcrRiJ0rFFk2JXqRe4yigDCBv/74E1/obybtGKnpRDCfMUxSvQbuuf",
"part_4": "apeeb8coxzjh8vCOGjLxVXPOig4cY6IPLRVNe1ysTgwnoUEFMMcj6ZoH/SBWesxvDouOfXRR0DFdqcCwFT5NuoAmEypalgtNuGC40dQeAFRz99suyKOW8+ZybTvLRrt5i6AtFVOJZLCvgpgbCHHJBvyKi32XgLnnbp/h56R2dK5M9RuhD2X4Qy2FuGWaqT",
"part_5": "s8ouF4pf4qE6nUhI0RSfZl8rrlm+nODlknt/mxalYKYGcxU4kl3oPgLTMnHma21vVZsACmr3atRTZdmDe8c+ixOujQXm7UVwrVYbyyyPinuaFQu440zkz4vPjYQ5duiM6hgDTAVYBf0Y3hbKx11EEOKwSTrIbcEMtihynFPDPmlxUDpn+qGCfYM51q+xKC",
"part_6": "zORNdWd1h7ZqYqdKfUlCcUaCxCUbkiQuu4VxEb9HOq5qSrZ2yTeMLRzFZa1knPWYyzWjNX+RmN7pH/ke9Qh1nM0PMPKvvCaNjCO2x7hhSeN4VEpt5WqNMAQ8hmqbI8G/P0y0ie1IN6COduUkMv7seUtdrASL769gcuzk5+/Xh8dkrn0UHMDJdhB78FAB8Z",
"part_7": "FTiKNUvzsOMlBezitPbvlGlUX+5dvZFeIia43vPv2uK73K33UkNzypXGKFgoGwv0cLQKPx5B982bUO7y3e6ysjF0qe0VfS3sJKs6NPPoET1MGLbuvJisPY8u76ycL+C7ZVe8Yq65ZSHhdJqmeNWG7V/en5y//3DRYBDhjt0Ci+PoIe5XsDeEC4tFOW0EyR",
"part_8": "BOcPxSQxmnMI2m+6hpvje8ytW9oZjpJezEdLBsEkmko1E4OiJjdQ37I882JE82xKYU3K5B6j5sFOhSWKRliD5FT451Ok3snlZzhOVLddzEj4iGxsCpkljtFIKv8FrH8RvU2BTbKzSRs9RpduFv/BnHsDON8UZgOrWbtAEloanXrucJgMmcHAicV94j3wQd",
"part_9": "7GTnMnaxG+W4rht/e+HaXri2F67thWt74fpvXLgaEBMML4NPnz750fp4N9pevraXr+3l6391+RpJ7OPgKgqoR7Gvg8v7UWDvSjYKhmjJjZVxPTACvJEELk6vpNFLMZFY+Qlby3EGkwKvMC9H621Aq2f2N+MlWPHr8dr4tgmri961wettYK7Xkrv+Wjxirg",
"part_10": "1e/x/j7bdC7G3Mbr9VfvsbYk4Qr9cS8XAtosdrw+NgY00Tj4NWTA7gYGPcg5aRDyAZbAh90Dr4fehuqvIB7LsstYE92Bg/cboPBy15PYB+f4O7fQTdd0y0cfjwX5pp4Jw+bIfcXU8G4e07Itpmj7DXt8NhzcYq9hX988SMK8m/ViwYWl2xxd/6nPo9fRkAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/12QzQ6CQAyEX2XSM5f9gw2vYo0XjZoYMLB7MIR3p4sGiqed+WbSNjvRfehzd72kIacHtTQxPbt3TiNTixOTh2PumCow1bC7cSpo4L0Kdh1hbNxcQKO0XfW5mD4ntdJARsBi61oE1IIcjIZ/1qORVjhiJ3OUjb9OmXUIjKCwQoXKitL9HjpTRWP6vG7yS0OWZ14ASye+Az0BAAA="
}
}
|
codegen__primeintellect___2465
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nMonocarp has arranged $n$ colored marbles in a row. The color of the $i$-th marble is $a_i$. Monocarp likes ordered things, so he wants to rearrange marbles in such a way that all marbles of the same color form a contiguos segment (and there is only one such segment for each color). \n\nIn other words, Monocarp wants to rearrange marbles so that, for every color $j$, if the leftmost marble of color $j$ is $l$-th in the row, and the rightmost marble of this color has position $r$ in the row, then every marble from $l$ to $r$ has color $j$.\n\nTo achieve his goal, Monocarp can do the following operation any number of times: choose two neighbouring marbles, and swap them.\n\nYou have to calculate the minimum number of operations Monocarp has to perform to rearrange the marbles. Note that the order of segments of marbles having equal color does not matter, it is only required that, for every color, all the marbles of this color form exactly one contiguous segment.\n\n\n-----Input-----\n\nThe first line contains one integer $n$ $(2 \\le n \\le 4 \\cdot 10^5)$ — the number of marbles.\n\nThe second line contains an integer sequence $a_1, a_2, \\dots, a_n$ $(1 \\le a_i \\le 20)$, where $a_i$ is the color of the $i$-th marble.\n\n\n-----Output-----\n\nPrint the minimum number of operations Monocarp has to perform to achieve his goal.\n\n\n-----Examples-----\nInput\n7\n3 4 2 3 4 2 2\n\nOutput\n3\n\nInput\n5\n20 1 14 10 2\n\nOutput\n0\n\nInput\n13\n5 5 4 4 3 5 7 6 5 4 4 6 5\n\nOutput\n21\n\n\n\n-----Note-----\n\nIn the first example three operations are enough. Firstly, Monocarp should swap the third and the fourth marbles, so the sequence of colors is $[3, 4, 3, 2, 4, 2, 2]$. Then Monocarp should swap the second and the third marbles, so the sequence is $[3, 3, 4, 2, 4, 2, 2]$. And finally, Monocarp should swap the fourth and the fifth marbles, so the sequence is $[3, 3, 4, 4, 2, 2, 2]$. \n\nIn the second example there's no need to perform any operations.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIAFD8N2gC/+1azY7jNhJ+lVrBwNqIY1iy5Z8G5rCHNDCHSQJsLkGrt0dj07YmEulIVNxGEGAfIk+YJ0lVkZQpW25sPAsssHBLlqhS1fcVq4olHvrXYJ3qtBI6eAi+L7NCvJda5LlY6WAYbGq50pmSLzItBCqgKJNr8Ro8hNEyHAaqzLaZTPOXfamKPUH8U+W/CNA7ARuV5+qQyS2s1JpuqPMpFwXUFT2RCkq2ZVoU9JynclunWxQe9U7Jh",
"part_2": "0Qm8oOSapWWe9ilFaRliSpiDT3ZQ8hclTgu0hIxK8gkpFCqwwh+QFx+C2rDJL2s97XeWU3IKuilL1lvBA14nv2ECKpcC0LUO/SmGkKlAI0PqdQVaAWlsPw+ZVWvdsh7SI9olmpI87x5bdkrDJz1Z6PKArVXSupsW6sKKrEthNTQTyXxIj25p2R+xIsw6E4HjUGkKGCswQgoPu8lKLKDA3qPPjdTesNtnBf5OjSIv4jyaN3rfe4NITNe52KjC1",
"part_3": "VpFzWcTKPEIcw5phgC0sa4D8HOAbAidue2GNPKAlAm96rKqKqgV/ZaGDiQ1idrvMG6IjaaC2mTeePJiGLwgwIMS4ZWQCxbleZeIFaphLU6q0e1F2XKDqTyCLIuPglTLVj91QOsdkpVWMMHBVLgbD6puiQzG0Ez1eqQ7gm2YCd+VDW6RoWvkDJf1XmqzSrA2s6KuvBYGvYKWvWNpviGi6SVOEYx1CP4VjEu1hqJuWYJ01YJV51LNPpDXouf6zS",
"part_4": "3MVsrlEtFqdFalJhu3VRciYqZWQAd1THk2vZcOUsruy1e05W2xeuqvG7KnAOVyK/p773c15pHnELKTlZiyeSZNU0zWTFOht1oi5OkRd/rR5AkWBXS3KZ4W61xOuH4X/GgB3/8+3d28RRrFzfHUgkEX5/RYIk4lgqDIORKUI8Icc4v0RA5kIKy/sIuhIYbe4gZROMBrpsDr17uLBRR/WYT8iPxXa39UGAHlvqLCud8Mfhk37ymxR7jYek4C4mc",
"part_5": "J3KCsYzAXCNSN27hC9NmeBwnMhpDCOEUA95WG3tqIdrEECPWFBFjmMPMPuHdN4pC45p1jkq7icN70xVMVQjjNkpKIfwwpBhzIVW93Y3gkVTzo7f2q52q89NKpXIt102f2uCqbjJi+j33a1cBruVV3O+eJkOYDgGvEQ/wGj33+GsjrzPacnOUxoGrjI5n4hg8nn8gxIa+tG/O0M6pmWK2eWuGbT5LZvm8HNhJnJKAlf53aiPYHaldnKqPuukpO",
"part_6": "82iy6gu4JBhA/mEcHpNH2tEPGLTtDPYc9mjAJegymvuzQiMuooqhY5v1YHe2c2F20sQTil0XUq75tZihJuUUmzQS5wk7kiyYq9KDdWxIhgJ72i19/FxxK6MsNOuqSH0Bygos31/MEhkimp5Vul+ke77qD+EtwxG1T7PNBqi5Qe0fHoacwPN6Otmunh/jJENB88s/3wpT+QjGV61S2THCznAbRLg36udVfqUPQ+MqJvH6tMffuo/w9/ewasno7",
"part_7": "8PT5+fn16fEdGNvoJHHBmtR/Pq0chxBae4Dt/BuNO/E2GHN5nvjEGh61fU+fofcCLIOTQ+8KS4RnCrVA0wwRxwTK4usYXjs62H+wb0vgG9b0DvG9D7BvS+Ab1vQO8b0P/ZBtSBVMHDU/Dx40ezp0jkfTP6/7YZTSSmN3geBlpUGtMdPP2aBPq4F0nwAEnAWXqxdRRgMw+4Gs3LeXLe+bAqWEmZFsVaE5b+NoT/HDhOzlplF+74r+OG5Mv13tr",
"part_8": "Fgk32r9OQa+EELs8lHuGkm+gWHibCMM34DL2rP+g8w+vC8EIhxChdtQvPVfj0DcKWLDzH7iCcXbOOccPQYro+D6ogHnRnNhxPxrfmdgrXz/9asZrsUsXEtBQgjICf6Hnphu6I+YxagsawMY9P1mfAsUP2bVrmLUgu5Kgtjj18BxY5vz3q2NdeNgrdSZpMoxuTNMM1PecVTj+6hvNOjsXtuQmxi1AfCamduEdzGNGUW6N9NqfVj91L7nItnTN7",
"part_9": "MogZf+Le2V98Qo358UTfUDX+4OHQzM8xhC2pEXUnY7r4kmRMOQ10LHG87KSIb83FlPK75NO0ADzmdOUCm9l3Jwm5EM6MwDNhnXmjOuOg+bhTk7GlGczMWxrPLaaDZISZlUztz8DMWTp12HPriPPUmZ1ctiTO6e4WE86W4Rf0s4hPU04ReJJusps/V9y7m2YewwIfFniwYGEuMdiGf/qMNKIFW53uMwfkwBrkRr44G/qAJ92Fx9V40eBYpxf8V",
"part_10": "bGOmm9Mo+LJwtmVbhbf/MmhGIWX5xwWnVTzm5vazMwv8m7XdxKsYAYLX0phuFDHIzq9ccluY/lIEY3sU3NZOLuFVzCLBsIfLS58WTCJpQnbLl7J2Hxya8ZC8M+Jd++kmt6csRii9leVz8hc3KuJe4wutZxG1AjjCzWLEPNu/ypbW3jO0HjQ6He8775fTqhld6VJxTckjzpbdOULOL4Njjf/bwE+03+mVC+1zH6uRfCgy1r89ids9zt82iIAAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2466
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nЗавтра у хоккейной команды, которой руководит Евгений, важный матч. Евгению нужно выбрать шесть игроков, которые выйдут на лед в стартовом составе: один вратарь, два защитника и три нападающих.\n\nТак как это стартовый состав, Евгения больше волнует, насколько красива будет команда на льду, чем способности игроков. А именно, Евгений хочет выбрать такой стартовый состав, чтобы номера любых двух игроков из стартового состава отличались не более, чем в два раза. Например, игроки с номерами 13, 14, 10, 18, 15 и 20 устроят Евгения, а если, например, на лед выйдут игроки с номерами 8 и 17, то это не устроит Евгения.\n\nПро каждого из игроков вам известно, на какой позиции он играет (вратарь, защитник или нападающий), а также его номер. В хоккее номера игроков не обязательно идут подряд. Посчитайте число различных стартовых составов из одного вратаря, двух защитников и трех нападающих, которые может выбрать Евгений, чтобы выполнялось его условие красоты.\n\n\n-----Входные данные-----\n\nПервая строка содержит три целых числа g, d и f (1 ≤ g ≤ 1 000, 1 ≤ d ≤ 1 000, 1 ≤ f ≤ 1 000) — число вратарей, защитников и нападающих в команде Евгения. \n\nВторая строка содержит g целых чисел, каждое в пределах от 1 до 100 000 — номера вратарей.\n\nТретья строка содержит d целых чисел, каждое в пределах от 1 до 100 000 — номера защитников.\n\nЧетвертая строка содержит f целых чисел, каждое в пределах от 1 до 100 000 — номера нападающих.\n\nГарантируется, что общее количество игроков не превосходит 1 000, т. е. g + d + f ≤ 1 000. Все g + d + f номеров игроков различны.\n\n\n-----Выходные данные-----\n\nВыведите одно целое число — количество возможных стартовых составов.\n\n\n-----Примеры-----\nВходные данные\n1 2 3\n15\n10 19\n20 11 13\n\nВыходные данные\n1\n\nВходные данные\n2 3 4\n16 40\n20 12 19\n13 21 11 10\n\nВыходные данные\n6\n\n\n\n-----Примечание-----\n\nВ первом примере всего один вариант для выбора состава, который удовлетворяет описанным условиям, поэтому ответ 1.\n\nВо втором примере подходят следующие игровые сочетания (в порядке вратарь-защитник-защитник-нападающий-нападающий-нападающий): 16 20 12 13 21 11 16 20 12 13 11 10 16 20 19 13 21 11 16 20 19 13 11 10 16 12 19 13 21 11 16 12 19 13 11 10 \n\nТаким образом, ответ на этот пример — 6.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "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",
"part_2": "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",
"part_3": "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",
"part_4": "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",
"part_5": "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",
"part_6": "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",
"part_7": "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",
"part_8": "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",
"part_9": "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",
"part_10": "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"
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2477
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nThe Queen of England has n trees growing in a row in her garden. At that, the i-th (1 ≤ i ≤ n) tree from the left has height a_{i} meters. Today the Queen decided to update the scenery of her garden. She wants the trees' heights to meet the condition: for all i (1 ≤ i < n), a_{i} + 1 - a_{i} = k, where k is the number the Queen chose.\n\nUnfortunately, the royal gardener is not a machine and he cannot fulfill the desire of the Queen instantly! In one minute, the gardener can either decrease the height of a tree to any positive integer height or increase the height of a tree to any positive integer height. How should the royal gardener act to fulfill a whim of Her Majesty in the minimum number of minutes?\n\n\n-----Input-----\n\nThe first line contains two space-separated integers: n, k (1 ≤ n, k ≤ 1000). The second line contains n space-separated integers a_1, a_2, ..., a_{n} (1 ≤ a_{i} ≤ 1000) — the heights of the trees in the row. \n\n\n-----Output-----\n\nIn the first line print a single integer p — the minimum number of minutes the gardener needs. In the next p lines print the description of his actions. \n\nIf the gardener needs to increase the height of the j-th (1 ≤ j ≤ n) tree from the left by x (x ≥ 1) meters, then print in the corresponding line \"+ j x\". If the gardener needs to decrease the height of the j-th (1 ≤ j ≤ n) tree from the left by x (x ≥ 1) meters, print on the corresponding line \"- j x\".\n\nIf there are multiple ways to make a row of trees beautiful in the minimum number of actions, you are allowed to print any of them.\n\n\n-----Examples-----\nInput\n4 1\n1 2 1 5\n\nOutput\n2\n+ 3 2\n- 4 1\n\nInput\n4 1\n1 2 3 4\n\nOutput\n0\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.4375
|
{
"part_1": "H4sIAFD8N2gC/+1ZzW4jNxJ+lUpfbI1+IPafJGO0iz0EiA+7myDZ02jgoSVKot3N7u1mxxYGA+Saex4gh+yL5FHyJPmKTcmyI3kzgrGXtQYzZLOLVV99/KrYwHwMFtLKWtngIvi60rm6NFZlmZrboBcsGzO3ujBXRuYKBljSZqHugwsRhUkvKCq90kZmV2VV5CW7+LbIvldk14qWRZYVd9qsaF4seID",
"part_2": "NdaZyamp+YhOsrCqZ5/ycSbNq5AqLG7suzMXMzMx3sPmmUcpQsaQvzQo2C1rLmgzZSqmaVlUbQRuShDlP1qqilawWygzobxZxpO25aLpv13Qu6LcffyHt/jUd54eWQO9MMrW0LsBa6dXakrz6qD9Rrqyq6gF9Vyzkxtm1oBZqrhdqQbagpgSLbd71XBlVbRjyPpRv8epOGls7Iwf/zIep2UOulHWv5o",
"part_3": "VZaCb9AhRWJLMMaHew3wJ0z+PqkqC+n0/ptkd3CKjolnQbxDT5NRA8AJ6vi1oNmNl/Gfi2jQHobNPSUxUbmXm42AUfpgADlMv5WhtFjnvAk4bXl0221IDGOxeq1oiLhB9CaVNbZJttvqBLHB/245Qbq9pYuyjwRkpbJgpsVgpCdAaef7iU7RGBIWk2VBY1uIHCNFS6wq6tIQCb0/cP6CuIp14XTbY4R",
"part_4": "IacW/awTVqCaZ2z96/w8u/yRtV2w9rjrchT502+ZR9Gbeb1X5n4menz79KUjXWzrc6XuqotZcw0FGAlCCR7V1Bdyrnq16qUFQ5rsQVeX5Dp4ai9MNycJ2I4HHYgVRaiYik9cWmOOoSQBCsr7NFgMHAaM5+2/luR7QLQbz/8tMdzvT37tio9EajHAe3l/M/G7id92Vrt5V1WwAJyuT9kD0dU7qIdpfax",
"part_5": "qIxSC5SrD2DUvYUPjlD7EF6080qXXGiuVKF36Xpd3YK+XB5wyiI4ojN+utnrMDfPdJjrDd3T+T0s/kOi4/uLqwzjEXoK50VVqbrkjsAtkkmaBd1ff7759ef7WYAUj4E8UkwvALLFVzyDr7/D98Aj2oPE37zJrC4z7oSbtuvJW+VbN8Nz8rlWsrEatXa8ovxJ9WhTNM6x5LumbcVeRWbjE84Hexr88l7",
"part_6": "miF97FboynJmYxMwICtFPEzZtlToz4cx0KSIMfXI2f9wRUby/Y7gtZ812dMfd4hqlaBd8RaEaGbDvMy1QLFRUF1njlAj8sC3YFf/5B3el3Y26vUDZT6VsU20PYaEGuJkrtQTPZs4XtendTnNZniNCz0E57wzqMtMYOzMjp5mu7fkxA1iUU67zmXHVOUWufBVpPpAK97Q6Nx1c0ISfxmG80+//cvtG+x",
"part_7": "X+meJuOnx4XE7Zpg+bvTU4vHlwqDt723eOb95/MV12b9/cPHnpY3QZ2TGHXdEzzzi9eXP7J5xiA5belk9MyylWHy+1TC1BHR/redn5r5wBBe/pPqau3X7WPduavd1ZkcpQ0Wf9sx4nJ6/rc0ere8/kdjpQgTtEKMBW6Pd49qJ5/TR7/TR7/TR7/TR7/TR7/TR7/TT7X3+abZ3UwcW74MOHD+1FOjOvn",
"part_8": "2n/l59pMwMNBO97AfqjhSaCdx9ngd2UahZcoEqdJK+82IIeVtzRty9Z3g8VASU6g6IVubMIZ9va2BYHW33q0SlBuIgOBRl+vtNkuO+VEkppRGOa4N4iIUggo4gEQickUhIjEmMSEwqHFGJPSCFSiilMKEwpHFE4pnBC0ZAiQRFcRhTFFCUUpRSNKBpTNKF4SLGgOKQYEWOKE4pTikcUjymeUDJ8qdTE",
"part_9": "8dRekD0+7hCppo6u1NGSuvRTl2ZKaZpQgkFgRiNBI8yHIY1TmuCBGR5i55AdYGSWQyYeI7wIuBHwI+BIJBjhSaQcCb4SHAq8iTGe4U7An5gAAvyFQ4aCkSG5o8IIfyH8hfAXxulBEhKnT7YT7QyoRdxOR5SE7SqOPxWpm+Jwk3F80ulMJu540C0BG5qasDygA6QQpTGlk5hGk4jSUfpMSY081C4rNhT",
"part_10": "pCUg8kJcSRbiX2Ev5jJ6Q9VJ+4wOH8MKYwwnLH2KfhEePsc+dc9TOUKs+v1NYj4ao8eRwe/TaRdMZf77/kW8me+3kYJDUaTEk4Rt+O8Z+TPyY+nF0ykWQPIZyEEb8J2B8tlZCHzY6cslFPuj+ZcdBw9MvO5fjs8EOZXgyocfDPSV0PzcmNDylQHY5PtPgHmeIEO/5P/zqq8bofzcquLBVoz79DlfApPMxHAAA"
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/22SzWrDMBCEX2XRtSloVj+28ipV6CWhLRSnOPahhLx7R7KwTclpR6v1N6vBd/MxXufh/D6N8/RpjuaezdfwM0+3bI7ylo0X5DxAVJx4qmwOko1KSrUNa9dmaKP/h4OVwIM6lSjgfRTlTBQHcVE8xEeJMUhgAZV0kI7aqvRREg9QOhW3AmAlAmSAEJACYkAOCEJgJQmxOJEVuBdp6HkmDuQhcQXy1JZVWMtKZSfylDwlT8lTH9dXoD15bWzJoL5v6bothN3klha9k2jq6+Wp3F7naZf3FuemSpQvxadW16pvdYm9RU31WrwdFsU44RfZSdClq5bdWKVj6r1/4qnNS+uY33nok232X58e5mBu0+/3hb/TOLM8/gByPo62ZgIAAA=="
}
}
|
codegen__primeintellect___2486
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nAfter Vitaly was expelled from the university, he became interested in the graph theory.\n\nVitaly especially liked the cycles of an odd length in which each vertex occurs at most once.\n\nVitaly was wondering how to solve the following problem. You are given an undirected graph consisting of n vertices and m edges, not necessarily connected, without parallel edges and loops. You need to find t — the minimum number of edges that must be added to the given graph in order to form a simple cycle of an odd length, consisting of more than one vertex. Moreover, he must find w — the number of ways to add t edges in order to form a cycle of an odd length (consisting of more than one vertex). It is prohibited to add loops or parallel edges.\n\nTwo ways to add edges to the graph are considered equal if they have the same sets of added edges.\n\nSince Vitaly does not study at the university, he asked you to help him with this task.\n\n\n-----Input-----\n\nThe first line of the input contains two integers n and m ($3 \\leq n \\leq 10^{5}, 0 \\leq m \\leq \\operatorname{min}(\\frac{n(n - 1)}{2}, 10^{5})$ — the number of vertices in the graph and the number of edges in the graph.\n\nNext m lines contain the descriptions of the edges of the graph, one edge per line. Each edge is given by a pair of integers a_{i}, b_{i} (1 ≤ a_{i}, b_{i} ≤ n) — the vertices that are connected by the i-th edge. All numbers in the lines are separated by a single space.\n\nIt is guaranteed that the given graph doesn't contain any loops and parallel edges. The graph isn't necessarily connected.\n\n\n-----Output-----\n\nPrint in the first line of the output two space-separated integers t and w — the minimum number of edges that should be added to the graph to form a simple cycle of an odd length consisting of more than one vertex where each vertex occurs at most once, and the number of ways to do this.\n\n\n-----Examples-----\nInput\n4 4\n1 2\n1 3\n4 2\n4 3\n\nOutput\n1 2\n\nInput\n3 3\n1 2\n2 3\n3 1\n\nOutput\n0 1\n\nInput\n3 0\n\nOutput\n3 1\n\n\n\n-----Note-----\n\nThe simple cycle is a cycle that doesn't contain any vertex twice.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.1875
|
{
"part_1": "H4sIAFD8N2gC/+1azY7juBF+lYKwQOwdt0c/ln8a6MMe5jCHbALsIEDQdjy0RNvESKRGpNptNAbYa+55gD3kSfZR9klSRUqy3G33zDi5xT7YElms+qrqqyIJ+MlLmWGaG+/W+2spcv5eGp5lPDHewFtXMjFCyaVkOUcBHBIy5Y/ebRCFk4GnSrERkmXLolR5QSp+UdkDB7PlsFZZpnZCbiBRKf2gzCrjOVSa3kgERzYly3N6z5jcVGyDg3uzVfJ2",
"part_2": "Lufyp7XhJfxNGJbtYcc08MeCsKWwRntWRSXFAy+1MPsB4OuKJ4gUBPpQcm1QUkgrh3aKLT2pcj8k3bVWrgueCJbhYyY+oTwJJ/sk4xrUGpgElaaQcbkxW9K124pkC5zhF9o1/BFUklSlBmYgV9qAkgnvGiDYO4VBK8nLrdqBUaBPRKkOzxD+ripgJUJGzyQhqGQqSkwIonNuJEpqoQ2tQozSIhEJImYyhRx4uuF6AFIZkByHNSsFIsFV0moZwE5g",
"part_3": "jCsDBSvRdZ65JXZ5plShHQjJKR4K1phzMPDHr/+ykDFdIq9ykFW+wvQgArfabCkGFcZgxYGlqVtsg289cdgxhqrEaFjFqsyBgRZ5kdVRfxH0wTNvc1VS5EhG8joHQ/gzjip8sSSwGCzoXQv6AHbH9pqMI0J0ykE/Aeo0Guh9HU1/CO8NCE0Z3YqVMC4QZM8GF009C7zly4edOsJWB1V16EussPYRKirlnyuWgViTxB62rKaUpgrAgnYEtnk4WPlF",
"part_4": "ID+bkkoVWiCaaFOle6LwiZJimspij3xALFueFbAVuWUQSqOX2Dw+WdVzeUOf97KojH2yXhHHRYkJyYS08SQTgmTIFcOERBXoOpXsBs2CrFnc+yGC+Tzjn3HE/Qb+P57iLwPw6/e8/p3PVcFLZlRJbeoJ+fmlN5+vS5Y8yZ6EGwj6X55CXOgU9H/4/Tekxe+/HfOiLaKjjkFYjuVaxrRC1vuf+SOy33qpG8+sSMp1UoqC2qhu/Hc66herY2AJROOA",
"part_5": "vlg1Q3hHbcaOYZxdEa0wTcgeYaG0MWPLJ4H+regHegH88c9/H4/RgOx3/G69tVVbE8u1B7Jhk3RjnPUh/JRldQRaz52jtFBzYnO9kKpZbrBydMHqRuiKAZt7yRCvbbE107p9gbgo/9SSAgO/r8uFUvCsXuBDmyBhV53sc11W/qUyXVriTidN48pLfiorbXlp/bg5+NjG3Fhgu05MX22MGhtulr5sjW5f+rZe+A2tEDco7A1f26AGJ3jd9J5U2bru",
"part_6": "Bu/dIyNUug6frfC5HMFoLgMI6Sui15C+Ilrlol3PtgsimrRDIT1FEHRlfffayvrdyVq2RfSzMvyoxxzFDenWNHAb+1PcqoNjdqKm6Ye2L+0E0h0TpU0qXDei7lcnsLDMwYGSdvGKytru6CZVBNS2AtzkDzt8c+whPSU3VelIh4ciPsTzVMnXmDDMCR6eUr5GEZYu6UjW6+MZCPAjB9hX7pCf2vRyVvTQ/sAh7fWHusgE/vb7TvadRsn7+wXRCR6I",
"part_7": "4Fh0G96T/YUToHF+GM8bI/Rh2C2+1ZCVh5s7ykvzvnr2/k7fs8WQFQWXaW/VP5pYtROsnqhjQ94OUIICSfGwgew1ow1c3PQwJnfgd+DXCiI8+cCPUDf+5insw9u3MD6sZo+91lGsLqu83yedwUudIaWANN2ENdqCGTxiSgq370YSlWFsMfr+AkXlIdxVNw0d3YjCrrmvFp1Rp0pijVf8MNoIwlGAtWHJJzJZLQ6DctkiCXCv7Mzg2ZUaMy16ZvAB",
"part_8": "pe34sFBFr388WZT8odXpgDwsjkXIzR25iZl9eO6NxV+VSHLzTM1u8VKSonIsfNdBcEJ1J03+oBud1zT6ZxQ1uBDiTcfsaeE60ve9ToTeIOfevg0X8ObuFJY2aw37d/1u5jjth3etYv8orbQPHOaCzlxLxjd3jRIiq3uyVYDcDxGbU2Ln6KGdOqpAZE2jsCnC5RJBl7TvLAuFbeGoNw1c1+k0rrpEqFP2fnxWwH3S+VIfdkLbYbALmhJ7NL7XjfN6",
"part_9": "qbxeKq+Xyuul8nqpvF4qr5fK66Xyeqn8+qWyUaK923vv48eP7vjjznLXC+b1gnm9YF4vmP9nF8y5xD7oLQaewSsc9kXv/mnumX3B594tzD3blpd1w/UGOGL7kpukTcltMm5bcvuS25jQmhV3u7uTd5JzD09K324kssrc0tA+0/50Sr1fj3+nev+ksugSZeMOVheEMcQn1YcQXBCLwKfPecRj/NDXxMp9v/74RUKDeiQ+k9DxfxeksGbNOfXBJT7E",
"part_10": "L/gyao3E/0vuxLMgmp3NRjQaTfx4Oorj2Wg6+37ts2l8XnkQz2yaJ1P/AtVhPJtOzuoOZ+Fo7EfTyTgexRfgHgXBedzRdDoJZ1EcjuNLcMevBDycTGLUPB7H00vi7bJJNAj8yEfKT2fhmdol0cmFGbUGJmEAs9FkekY/Cl6gfjIOX2HMJJqRXyGSMbyEM7MweoUzQRSMwmAymk6CWXQJa8ad1tNt8+d6Q1uwC/rzjV5WUnyuuHdryop/+Q8O2w5EvSMAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/3WQTW4CMQyFr2J5zSK24yTmKg3qBlQqVTPVkCwQ4u7NwDCNQGycH39+Ly8X/JrGOuw/y1TLEbd4yfg9/NZyyriFj4wBJOeBgFvl296DtppxAxnVSAxoJpw4Ak3Ga5NVW9OtZ0u6sJEJzMe0tgL4Jxe5kb2XsaTYycnLy+4zD3Nb6d18MdbSxaIehTlG7IQ5RjXREDQl67iW4B9znURzFvJM0adIJl7fUGzsg2s5gi7M7oobPJXzz6F9/lTbcv0DtzWk9pQBAAA="
}
}
|
codegen__primeintellect___2488
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nA group of n schoolboys decided to ride bikes. As nobody of them has a bike, the boys need to rent them.\n\nThe renting site offered them m bikes. The renting price is different for different bikes, renting the j-th bike costs p_{j} rubles.\n\nIn total, the boys' shared budget is a rubles. Besides, each of them has his own personal money, the i-th boy has b_{i} personal rubles. The shared budget can be spent on any schoolchildren arbitrarily, but each boy's personal money can be spent on renting only this boy's bike.\n\nEach boy can rent at most one bike, one cannot give his bike to somebody else.\n\nWhat maximum number of schoolboys will be able to ride bikes? What minimum sum of personal money will they have to spend in total to let as many schoolchildren ride bikes as possible?\n\n\n-----Input-----\n\nThe first line of the input contains three integers n, m and a (1 ≤ n, m ≤ 10^5; 0 ≤ a ≤ 10^9). The second line contains the sequence of integers b_1, b_2, ..., b_{n} (1 ≤ b_{i} ≤ 10^4), where b_{i} is the amount of the i-th boy's personal money. The third line contains the sequence of integers p_1, p_2, ..., p_{m} (1 ≤ p_{j} ≤ 10^9), where p_{j} is the price for renting the j-th bike.\n\n\n-----Output-----\n\nPrint two integers r and s, where r is the maximum number of schoolboys that can rent a bike and s is the minimum total personal money needed to rent r bikes. If the schoolchildren cannot rent any bikes, then r = s = 0.\n\n\n-----Examples-----\nInput\n2 2 10\n5 5\n7 6\n\nOutput\n2 3\n\nInput\n4 5 2\n8 1 1 2\n6 3 7 5 2\n\nOutput\n3 8\n\n\n\n-----Note-----\n\nIn the first sample both schoolchildren can rent a bike. For instance, they can split the shared budget in half (5 rubles each). In this case one of them will have to pay 1 ruble from the personal money and the other one will have to pay 2 rubles from the personal money. In total, they spend 3 rubles of their personal money. This way of distribution of money minimizes the amount of spent personal money.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.375
|
{
"part_1": "H4sIAFD8N2gC/+1Z227jRhL9lYJeIiGyIl5ESkqcIAGywLwkC2yAfRhNPJTYkjomu7m8jK0Y/oD8R74sX7KnqklJviiYEeZhF5AsyWR1XU5VnS624YdemtRJperevPfPUufqjalVlqlV3Rv21o1Z1dqaG5PkCgoQaZOq+97cC4Jo2LOl3miTZDdFafOCXfzLZh8U1VtFa5tl9k6bDa1syr+gs8xUTk3Fd6wCyaZM8pzvs8RsmmQD4a7eWjNf",
"part_2": "mIX5njalbQqyazJUrbbWZku7qyhVK52qlGpLJS5oqW9VNaLvKzJ2adMdG8B/TtukokSWhxJQrI1qTZWpRW3EsX7BMksYS6VrBR9rVbImO8q7GMdqRalXijTwaNGFu7Utj+7EZrjXZwS/XdVbkaMqVV1RcfPw2yOVDSpTCY43BtjqJDsA/oKqbcJIlk26UTUHTDoL+kFVqACCqGS1fZL3Fnr2zlChysqiR5Rbo3bOrRYUdieKy5sH/XhQ6zxz",
"part_3": "pk8DrxJDSwgLzs0aSsyu7cpqq7MUaVJSLnVdJqXOEGnZ1A4WIn1RPQPywltXJWuyHUACvTPjYkllfmxdiaXUN6nhq2Jr1TaZr7BsbE0bDSKKG642+l3ZXAk7VFY5j//esofkXudNTqbJl6rkEh4x7U5nGaNMUJOndPuOnLU2Yl3hA9NnOYo5Cs6F/uBAIN2UdNtklmSoLLqQv1LNQzTWKGxVaeD4jqEvzBW/3piiqeWq4/Bal6hIpo1q2YBg",
"part_4": "0AHdTJ1oU0FUKhbWagOwZIYgdwJMCfU9+uuPP52EL7zxr5OvaSzXSSeZDVpqKHhMXaAj37zwn0aZlYTfR1neeODDjT+k0WjEVw/msYvn+Ne6DwdDutti+7Ri7ZwmuW2YJusn9H1BKgcN5Ck/GlnByIo9MuzHfI/Mbc594h0yJ26RuSHA+/7VbT46atbPTX3cLUxbHkB39gCmlE5UXaCyC/K3HK2Zh4c94fgufvbmLUkd555xlMfh0UAsu0n3",
"part_5": "xtX6GSXbzeVCgbHtiIMm4tM1Yl7T+DjpH++TvMBAadMWwi6MTz5qujATmixMTBGru/LwWuAGodyFNCF/Yabk4QcXEQUUO9nBJKCpC9kG/cnWal9nnqj7jVEJGpAH/XmZ2nEJR/QPNBXcqRNwZui2MetURaZrV5unc9lgl2dr6k/aGSrDD9tFAKAVKzxmZUJ1Y1rGQzcZimSHDMWS1nicOnY97RV3lcVAzzSAqxcu/C74CR8Ozv4Js2snUtCZ",
"part_6": "OWy6fGVnIYW7RB6uqa7qUmO+42zA9w6d0Ez/rp5vWTfin/nr5pWbTt2crWocFSTNnW1QX9tkKW8x2ENQYoZnLiiP0jq13Hz++cne8Vp79OhOGuynVHVTOgbgHKJGOMKUSp7PKz7RCNVStYZekmamP5jvLRoQpZ8nRR/Rhw5nfzCS7vcHgwEb8qgcgi/Xe/OFWeIuQ336lS1rlfa7FbYo/mZtYTKs8uMMO2hheDOhoH34NwP6kjzWuANXeSxc",
"part_7": "UUbfkodDEuF1C9V+CZ1sQF99xTuDpbwTU+eLb3lC3Q9pxzT9XRf95dur2/k7DLy389t3g9YTv/Sa7ukb2h2J+JXSl9ewvqL7g7wSmbuHWUrfXFNyZMcJ3R5uXW6YZf3xELZXlAzcIj+Qj8xKZ4ZyceP7ICosB2ic1B5NwwlDG9y3fb4cOy/Hzsux83LsvBw7L8fOy7Hzcuz8Hz12dk6q3vxt7/379+7EARZdjqD/J0dQFqBxvXfDXq1wjMLB",
"part_8": "8+3DolfvCrXozWnREx7dtAzpDSGRnrnFdvi46ePGDxyKlnUDpVULRP44pI/37cbVYV4dD6zXgvDk+uQgnWsPn9fdejQ+BzscL3iaInUJEJxw7p+DOXTOGTNxmSYnnHuf7jwAXnbcFSaA++hzFsa5m8B93LY3RshZ27yXTfX8c6JMHS19zsI1eAxPEBLHm/HF7PNlNeWOcAIzXPCeYJa68nsex52eiAbtM9KLKGr3g4c4ASfThgoRGamjtqeq",
"part_9": "GZ3BtzFHiCVgTB5nFnB2IfF9yJEFBd4xx/Zm5I95GUhexzGh8Bzeh+xUCuYHDgTqEAiTAMoRKWIQ3Arfd9q8wJ0XvoWMzI85H16JTtSJM/YmZ1UK/gOusedLMzymRiiMCB0lZw4psI6lUpHgicQQ5hPJiBMKBGPMdY1OoYxmnw7Sl3YGwpiYg/tcNKGptNEXvFDhBsqFbBhfOIYKsupUXIxb3LjlyoavokQ3zuBciPBIT0JOaTJjKCghhgcK",
"part_10": "hwkFzEyA0JcBGzDrBVPkyZ6IUMYpBSEb4feELcMZkuZvFNSX9yRg9OGUiRKHnAwjjWY0idg2ith/HLTG/oziMcePYxaicbFstQm3gSK48FkCK7yhPJUUsBoDD2gQyyq8eexn4vMbhr58RycenD7Ngtm5W3Ysc2/M1x//5Ww8+pSvV7GPz5mk3GiBIH2Vp4WMtJkM8+eSl0FR5/DzRn0mOxE1aDn+jv+dXN00RuMP5N68Lhv1+F9xkoaEjx4AAA=="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2493
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nLittle Tanya decided to present her dad a postcard on his Birthday. She has already created a message — string s of length n, consisting of uppercase and lowercase English letters. Tanya can't write yet, so she found a newspaper and decided to cut out the letters and glue them into the postcard to achieve string s. The newspaper contains string t, consisting of uppercase and lowercase English letters. We know that the length of string t greater or equal to the length of the string s.\n\nThe newspaper may possibly have too few of some letters needed to make the text and too many of some other letters. That's why Tanya wants to cut some n letters out of the newspaper and make a message of length exactly n, so that it looked as much as possible like s. If the letter in some position has correct value and correct letter case (in the string s and in the string that Tanya will make), then she shouts joyfully \"YAY!\", and if the letter in the given position has only the correct value but it is in the wrong case, then the girl says \"WHOOPS\".\n\nTanya wants to make such message that lets her shout \"YAY!\" as much as possible. If there are multiple ways to do this, then her second priority is to maximize the number of times she says \"WHOOPS\". Your task is to help Tanya make the message.\n\n\n-----Input-----\n\nThe first line contains line s (1 ≤ |s| ≤ 2·10^5), consisting of uppercase and lowercase English letters — the text of Tanya's message.\n\nThe second line contains line t (|s| ≤ |t| ≤ 2·10^5), consisting of uppercase and lowercase English letters — the text written in the newspaper.\n\nHere |a| means the length of the string a.\n\n\n-----Output-----\n\nPrint two integers separated by a space: the first number is the number of times Tanya shouts \"YAY!\" while making the message, the second number is the number of times Tanya says \"WHOOPS\" while making the message. \n\n\n-----Examples-----\nInput\nAbC\nDCbA\n\nOutput\n3 0\n\nInput\nABC\nabc\n\nOutput\n0 3\n\nInput\nabacaba\nAbaCaBA\n\nOutput\n3 4\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.6875
|
{
"part_1": "H4sIAFD8N2gC/+1a3XLaSBZ+lV7d2K4hqQBOasu1mSoMtsHGNgHH2A7ZpCU1qI3ULXe3EHI8VXu79/sI+w5zP48yTzLntAQGL84kbPZiqyCFUavPz3e+8yN1Vb44PjVUM+PsOR3FI9YShoUh84xTcoaJ8AyX4pOgEQMBuMWFz6bOXrla/WvJkYqPuKDhp1jJKEYTPRlOGDEBI0MZhjLlYkQ86eMPyLghi0iicYUicGekaBThOqRilNAR3MxMIMXeQAxE",
"part_2": "mxsTMnJBRUaJzzzuM58YCXpMM2FIwBTxqU8oiaU2HlU+kYIEXJN9rkzg0+wl6YGfgGpCQ8WonxEPfgxDnYhpjQ5//8e/iDYKQWgihyRkYmQCIkoAXGiuDe7A/SSOmfKAKkKFTyC2YnUgRiHXAegZw5R+WeD1qNgyJFXcMJIxUyJaEm15SQS6FyzVMQWT1txCdF5iiIQvMlTYtCKjMLHMRoQLELMEzsKGNfUCzoD7WSiAAyQevUAwhnKhZwJm7fj6jIyF",
"part_3": "TAEBnaG0jIGNmW0ysjQrIhVhdwkNSYH4URRXc6yY7WW4Ec0wPM3dMIMEYlFJSYYstW5k9MiNYKxgLqLjvPYMmxobBepEkI65kjRYNI+pghC2NEmDrMhaSoXRsyxYDTF3hEkpgC8nz/p9LKjHGmJT6hnAL2z2LV/cALVyjBWoSZR4Af4WgUJMHCwBrtZwIf2Q7xwKiHFsR1vQnlQKupRMKNYFwpjdKbRs8rZBd5FpK7h8z8IqoudhaKPZKaGEsAWrAwhc",
"part_4": "k1uZDZMQghk417XrvwycUm7rKVJcjfgElJfgSgGquLeM200sJdCyhWqqJI4MwF5AyO2pkGiaaXDeb56fd3oDJ6+Z5aTZRGgkdZYLGxyA03ZY2FDmAazKwIx6BZTCN0pCw2NITIrOwYOPaeS6wGZtMmgjH2YSh2loMgzFIpnyiN/n5SiSyMVeAMswYHXO6pNoyLVMFIFJPC4sBCyMi7TM67qIyoY+EC/w0xJxYuzVrIeGXGmImQv22PN2pcl2mfz+z3+T",
"part_5": "B/1gfyu//Vp+9ffXO2tOAjs55+0GehYttNMiTERUULQCkiHbMzAP5n8ACsevgUQVxTVvWwutiVl+oA+AlwKgZ8cTXeT7PDGLhMMjEx5EJpU4lNkIAWgWU2WfMW4GUwEcemyP5M9Em5qiHLheWRx5youmm5dqGnCoQiiE2bOz4LiUGy4Y/ibLy4X3rOWXZCHqgymNoA10EbctuoGoufWBaNTdGsrlxAxElbzC5UxkH0So6y1KvCLVBQnqUg++aI3W6f4T",
"part_6": "W7uzGuIonQ8oFzMDrxS2EDKZWLJC24KQiwz7SMswsaMHGglkJRrDf2fw2NLzV5TZGwnaUcwkShQTymcv4VVHsSFUiPDwzcdnWIHetrcDbyYEPjD3PPLzW7JFt/LhS/4Gi/utYhs/HnlLvEBtS+WDHnlB8ALkd8hP+WVta2cnFy+8A020DHO1AppffinBdyCG8AjlWMCWge0F//YuLS94pOUP/CP56S0p5/dYqNl/bNvdP7NaWVSrfN1qZW5VAXiF4F+V",
"part_7": "sApoFWLZfRLLeAn1BHYB1vjj3L+QppBZxIBjg4uE5XeQWXhr3J4gV6BcsGivyYu3yGMR79JalTEK7xtwoANM93hnIdsoX10MvPrBs7xMVvNit+3uo7/Kor/Kn/vbXTS4+3V/uyv8VfdWELv7LLEWVnUJ1ozn3QWeq0943n3Cc6Xg2Xbkdl4VO9BROg45nhKMgkcArIsG3JwbNueGzblhc27YnBs254bNuWFzbvg/PzfMjGhn74Pz+fPn/M1kIDZniM0Z",
"part_8": "YnOG+K/OENiL0FHOx5JjmDbQYc6HLwPHZDEbOHswnmyDfypaF141Bo4tznwT504xeMCQ3ZX5xLDbOIHwPhbat9vcR5s4qVaZxJH13SZnk+1xtK1Gu/v9pu/xA2o3+HkG8eu1zOb24C9crjT8Gpp7DSo8mJqjgN+Ow0jI+A6eg8kknWYYBFDfODg8araOT9qnZ+edd93exfvL/tX1c5FV3vxgBLDgkaFuMrkPRGoFQWyayXglgsqbdSosBJXDjlu7vNWn",
"part_9": "cadx0R4P07Prw2i/0excNHr93vn7UO03r4+bndOVbsvreBXeKbvSut3sgW6SZuzUo4fUxC1xc+kfXMfp8bueuJy2T1a6fLNOshsxP9uP6t3D/jT23eHR+f1kcu6x6FYlnpE1/yBlo4uJe+kO+/1u5yg7qE2P/Ea3fxnenWVH/dN+81Q1a62bOJtORnQYKn15EwQ3XZlM4qk6uTq8oRGgStNO+9CcDTvm+Gpy2k6atyfD64x2A8XOgM3780kjvmvWj7y7",
"part_10": "MKzVzzpHzWmXscP39ah21zq5us6M7r1LW9Pj+zPO35sRcy+TtBv1426t3c5OavdZozMZtY6mtXaPMnbRuotWcwQkVb6fpXq9dgBavse8HzhzGp7ngpbLGHN/XBHVfITIqM+gjai/uinWKpX9mm+B+gxN+z71KX1mTK7B8UGjftBA5Mxl1PNd+gzRa0zgul9zGxa45/rsGUbWgIwQ95+BuUbmFE632tftfcT/DqA/JYLfJczZMyphv/wB61KyZU8gAAA="
}
|
{
"ground_truth": {
"compressed": "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"
}
}
|
codegen__primeintellect___2495
|
[
{
"content": "Solve the following coding problem using the programming language python:\n\nInna and Dima bought a table of size n × m in the shop. Each cell of the table contains a single letter: \"D\", \"I\", \"M\", \"A\".\n\nInna loves Dima, so she wants to go through his name as many times as possible as she moves through the table. For that, Inna acts as follows:\n\n initially, Inna chooses some cell of the table where letter \"D\" is written; then Inna can move to some side-adjacent table cell that contains letter \"I\"; then from this cell she can go to one of the side-adjacent table cells that contains the written letter \"M\"; then she can go to a side-adjacent cell that contains letter \"A\". Then Inna assumes that she has gone through her sweetheart's name; Inna's next move can be going to one of the side-adjacent table cells that contains letter \"D\" and then walk on through name DIMA in the similar manner. Inna never skips a letter. So, from the letter \"D\" she always goes to the letter \"I\", from the letter \"I\" she always goes the to letter \"M\", from the letter \"M\" she always goes to the letter \"A\", and from the letter \"A\" she always goes to the letter \"D\". \n\nDepending on the choice of the initial table cell, Inna can go through name DIMA either an infinite number of times or some positive finite number of times or she can't go through his name once. Help Inna find out what maximum number of times she can go through name DIMA.\n\n\n-----Input-----\n\nThe first line of the input contains two integers n and m (1 ≤ n, m ≤ 10^3). \n\nThen follow n lines that describe Inna and Dima's table. Each line contains m characters. Each character is one of the following four characters: \"D\", \"I\", \"M\", \"A\". \n\nNote that it is not guaranteed that the table contains at least one letter \"D\".\n\n\n-----Output-----\n\nIf Inna cannot go through name DIMA once, print on a single line \"Poor Dima!\" without the quotes. If there is the infinite number of names DIMA Inna can go through, print \"Poor Inna!\" without the quotes. Otherwise print a single integer — the maximum number of times Inna can go through name DIMA.\n\n\n-----Examples-----\nInput\n1 2\nDI\n\nOutput\nPoor Dima!\n\nInput\n2 2\nMA\nID\n\nOutput\nPoor Inna!\n\nInput\n5 5\nDIMAD\nDIMAI\nDIMAM\nDDMAA\nAAMID\n\nOutput\n4\n\n\n\n-----Note-----\n\nNotes to the samples:\n\nIn the first test sample, Inna cannot go through name DIMA a single time.\n\nIn the second test sample, Inna can go through the infinite number of words DIMA. For that, she should move in the clockwise direction starting from the lower right corner.\n\nIn the third test sample the best strategy is to start from the cell in the upper left corner of the table. Starting from this cell, Inna can go through name DIMA four times.\n\nThe input will be stdin and you should print your solution to stdout\n\n\nNow solve the problem and return the code.",
"role": "user"
}
] |
codegen__primeintellect
|
codegen
| true
| 0
| 0.125
|
{
"part_1": "H4sIAFD8N2gC/+1azW4jNxJ+FW5fJG1kwbI9CVaBB2igE2wfOhMgubm9M1SLkhh3k+0me2RlMECuuQfIC+RN9k3yJFtVZP/IlmY8s3ZykQ5mkyx+9VWxqkgCfhcsuOVG2GAWfF/JQsTKijwXmQ3GwbJWmZVavVa8ECAAQ1ItxF0wm56/uBgHupIrqXj+uqx0USLEDzp/K5hdC7bUea43Uq1YphfYgMw8FwWrDfZQBEZWFS8K7OdcrWq+gsGtXWs1S1WqYqU442",
"part_2": "rBIllwNtf1am0ZZ5YDDtNLZuTPgin2399ZwaQiSLPW5YR9w7M1y8AMlMJhtyTTynKpDGAgBxjJhbWimrE0iNJgDE3smsQ1YRpMWiK5fisMURkzo0GTYBuurGFWs5UGNRUSZGtpGLqLccMKrrbMglMN9kptjEQe8I2rCwJs1rU0J+xbXUGX2zFzHsgsrXceNeQaBgZLK3meb71UttbaAJ7RoPuh7Zu1qBp7nbkMiG4qCQPqa4aSygNxRdTQLgIzciFO+OInngll",
"part_3": "G1eiAuTYObXFBh9+7fCWEBbwBYpIHo1GdPSWZlqJhuIhDeaeCpT1lDt1SatuF5/fg/0QZdxo9mPrAm5MXQivHVHX4P4VEm53GZaZjRCgl1d24LYc3IjLsSfurHMi8pkLWExB/1lW72wapgMZu+H5DaC1jCjmojgJ21SQhcx5hUGoRDVxlinxFpnfyBKzwCFP2A963OzVvRhB43m+4Vu0X1Cs78hQvjxcGu9buqaQ6u/bvqXJI7SGuBQ98XB5+IjlEe42ZlEkSq",
"part_4": "GoOGnnM0gimbUb5FOstzXjLkV6Kd+5XkiLkQHTUi1xOdSnupjDEEJSIYDcpqyCagDoECEfkHPxPLB764tWGdSKf4u8dKQAZ8F0bSHVIXoKfieLungA28+R+/Sp1qXqBH+xKmtLXzj0IxZ0WRnLcql6/gGZXnZuNAxZsRIVUKT9Kdhwyv789Q+mxvCNH9PT/5yPnPcp31xRA3EE9pG/ECarJGTNzgEAaeXrI5V3ItLqLmDreAWVEnQ39b8ZwELXS7vuYFrquuqt",
"part_5": "++AxQIy/01Y4itIiqtKwNTWsB6vFws3sO27AbYKD85DFThT2HP6qtn2Px8s21EjLvmjDCBjDKQpOxwDuTjV0TRp8ryGG0HP/gJzYQGRicCC92xrsADfF5BA4FqTx+/kgFlGZcdr2RH6j3OtCiUO6XqGmjTTCL2nJ+ohhf/7yGy04FLgfTLy+I7+540WZC+NdSYGcqik7g3yPUcp5OlU9/6hW7gzlkhD60QNZZ18n+4K9QMwkjFwTuyaBJkpCwAjDZBfmwvH0TD",
"part_6": "Gc2g3HTluqjDPB34Jc2FL6gYz1s+OPB0jrZHThpAdmBATnYj9aH+pAVGx0tXBR0b+sGHf/qvOFO/r8OZTlOruhnV/IStB9khkLpyalYFvA9Qaw4T65xopS4YnV4wt3iGqHLo3OqW8rDhG0pSDWDrmDpUPfE6nLElTkYtlo2LkhwSl4j5S/tnys5lMVoRidNKXSFcaNBN1QxYyFI4bK2FbXjYdcFmxxrdF5TV4h+guNgeIiYoNz/j7dXJ8RpxK2rrx39UJM4F5e",
"part_7": "iSVkMhQEuIRTsb2ETCqHoGTs6AxHE1PmEtpRqgr2xSWbpuoWxN4N4sGMnY7ZIIF2Cm0I7Rm0EbTn71PgecmurlO1hK2W6E0oeCsxVKMZXkTh7ohoqO12shKdvpGfnfASj9nhyVcjxALZq5Ovrtk/WZGqEqGvrhlC39JGgZ4MB09RIhdqaEdOM+9pxsWNdpyb49yQsxNWwMWAfeGaE7QGe9NGFn9yyfjcDO3V/Bok7BW/Jgl2ecnOemL4K2GyYT8f7c5luN550S",
"part_8": "BfSUTk2JkhIFkEBuYwG6FGTNFbMG2zlhC8xuvhsNBMSl0OR/dsQc09MkQWfXxHvMcd7U6GCJ0QoZ6pNAqmnc5AU8+UmwZuBE44Yy9fYt2joBwOumI3IG+pLVohckjhGxy4YS/ZqesPuiI6GEEYUohBCEJSSgV9H7XHl+HxZXh8GR5fhseX4fFleHwZHl+Gx5fh8WV4fBn+NS/DBsQEs6vgzZs37hqdquMr8fhK/DteiamCIAyuxwEmLQRlcPUuDey2FGmA5yzl",
"part_9": "xGsf7XTIUqC4SazVVKwhC2hOu/JJk72qjdPvx+zxwGcEDNWdyvtBdFfnPxkdj4PmPGgOhOZEaI6E5kzYp/vi01VOYYfBlid31K4pYRTRZiTQJuS7KEJTooOm/P9uDPH3iPZp7Xb+jJ4B98L7cy/09NMRL1qmtDPokaeCPuvSjyL3abe3h56Ezxa4ELLYJr6F+KVATpIEWwjbcP8mn3/G3p7Co4aUgpYE/5JmSJGw6WACRTjkuODPE8NUoj9+DUl1a0LHm4Bpjj",
"part_10": "oADBaGHZo382lKygU7v+h40g/rwO6vKXIHpvcINWM733ES+6RoVhwUfoDUGN7v9jnFu1RiPxQfQHKq8S/SjpNdodCNdrxD2qCeULyHG6K54p/c94u3lAxAbn2kZNdFXm/rzLjP2lPx/JI2KsK+6Q4iAQhY0FRxxPYSEEwJnFaUFlBWKYijZyjt/2JfNsdK5M8R+kiaj7Dd6cfINB8PSZ59bulPnulICZ/pSPEp9nHoa/yvLvO6VvK2FsHMVrV4/z9h/NFgFiYAAA=="
}
|
{
"ground_truth": {
"compressed": "H4sIAFD8N2gC/41UTWvDMAz9K57PPTRdOlhvAl90EOw+lzHY2ApbMtLkMEr/+yxbcu30gxkSy4r0/PSk9mA/hn7q3l7GYRo/7cYevN11P9O493Zjnr1tWnPfet+5YiGBqxd7ctD55wtB6qtsJH6gQLoafIbEa3YxlZywpoLiwitI6Wp+M22kOgiS98QbHNSc8AI3RoOIRHNdpNJYAHMrkaiWSO7NYmLJWqgIPwINgrL0BEEBIiQweuSEuR4EIALWJyAF2yWhQpC3CxNmwvBESDvV1TDG6bw0zTKhcgGiMtcPegDpUaEapAOqgFkqckUOJC6qjHQ5ADuEYsIooSU+j+YhIosTdYRIDchD9Z8YNbT4VUzMjjarwT5WF/K3tVnrLbKj7GnGQs84nlsTc7ac1E9j8Zt86vvBYNe93mXU6HK779uuNlurW2HNLGF7tAu7H3+/3sMfxDCF7fgHPrmJGDgEAAA="
}
}
|
codegen__primeintellect___2504
|
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