Update app.py

app.py

@@ -278,7 +278,7 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     
     print('Done!')
     print('=' * 70)
-    print(len(melody_chords))
+    print('Melody chords length:', len(melody_chords))
     print('=' * 70)
         
     #==================================================================
@@ -289,56 +289,37 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     print('=' * 70)
     print('Generating...')
 
-    output = []
-    
-    max_chords_limit = 8
     temperature=0.9
-    num_memory_tokens=4096
 
     output = []
     
-    idx = 0
+    num_prime_chords = 1
+        
+    for m in melody_chords2[:num_prime_chords]:
+        output.extend(m)
     
-    for c in chords[:input_num_tokens]:
-     
-        output.append(c)
+    for ct in tqdm.tqdm(melody_chords2[num_prime_chords:]):
     
-        if input_conditioning_type == 'Chords-Times' or input_conditioning_type == 'Chords-Times-Durations':
-          output.append(times[idx])
+        output.extend(ct[:2])
     
-        if input_conditioning_type == 'Chords-Times-Durations':
-          output.append(durs[idx])
-
-        x = torch.tensor([output] * 1, dtype=torch.long, device='cuda')
-        
-        o = 0
-        
-        ncount = 0
-        
-        while o < 384 and ncount < max_chords_limit:
-          with ctx:
-            out = model.generate(x[-num_memory_tokens:],
-                                1,
-                                temperature=temperature,
-                                return_prime=False,
-                                verbose=False)
-        
-          o = out.tolist()[0][0]
-        
-          if 256 <= o < 384:
-            ncount += 1
-        
-          if o < 384:
-            x = torch.cat((x, out), 1)
-        
-        outy =  x.tolist()[0][len(output):]
-          
-        output.extend(outy)
+        y = 646
     
-        idx += 1
-
-        if idx == len(chords[:input_num_tokens])-1:
-            break
+        while y > 645:
+    
+            x = torch.tensor(song, dtype=torch.long, device=DEVICE)
+            
+            with ctx:
+                out = model.generate(x,
+                                     1,
+                                     temperature=temperature,
+                                     eos_token=2237,
+                                     return_prime=False,
+                                     verbose=False)
+            
+            y = out.tolist()[0][0]
+    
+            if y > 645:
+                output.append(y)
 
     print('=' * 70)
     print('Done!')
@@ -351,17 +332,15 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     print('Sample INTs', output[:12])
     print('=' * 70)
     
-    out1 = output
-
-    if len(out1) != 0:
+    if len(output) != 0:
     
-        song = out1
+        song = output
         song_f = []
     
         time = 0
-        dur = 0
+        dur = 4
         vel = 90
-        pitch = 0
+        pitch = 60
         channel = 0
         
         patches = [0] * 16