| from safetensors.torch import save_file | |
| import torch | |
| from torchvision.models import resnet34 | |
| model_path = "RESNET_34_cancer_350px_lr_1e-2_decay_5_jitter_val6slides_harder_tcga_none_0403_0204_0.9826153355179645_16.t7" | |
| orig_model = torch.load(model_path, map_location="cpu") | |
| state_dict = orig_model["model"].module.state_dict() | |
| keys_missing = [ | |
| "bn1.num_batches_tracked", | |
| "layer1.0.bn1.num_batches_tracked", | |
| "layer1.0.bn2.num_batches_tracked", | |
| "layer1.1.bn1.num_batches_tracked", | |
| "layer1.1.bn2.num_batches_tracked", | |
| "layer1.2.bn1.num_batches_tracked", | |
| "layer1.2.bn2.num_batches_tracked", | |
| "layer2.0.bn1.num_batches_tracked", | |
| "layer2.0.bn2.num_batches_tracked", | |
| "layer2.0.downsample.1.num_batches_tracked", | |
| "layer2.1.bn1.num_batches_tracked", | |
| "layer2.1.bn2.num_batches_tracked", | |
| "layer2.2.bn1.num_batches_tracked", | |
| "layer2.2.bn2.num_batches_tracked", | |
| "layer2.3.bn1.num_batches_tracked", | |
| "layer2.3.bn2.num_batches_tracked", | |
| "layer3.0.bn1.num_batches_tracked", | |
| "layer3.0.bn2.num_batches_tracked", | |
| "layer3.0.downsample.1.num_batches_tracked", | |
| "layer3.1.bn1.num_batches_tracked", | |
| "layer3.1.bn2.num_batches_tracked", | |
| "layer3.2.bn1.num_batches_tracked", | |
| "layer3.2.bn2.num_batches_tracked", | |
| "layer3.3.bn1.num_batches_tracked", | |
| "layer3.3.bn2.num_batches_tracked", | |
| "layer3.4.bn1.num_batches_tracked", | |
| "layer3.4.bn2.num_batches_tracked", | |
| "layer3.5.bn1.num_batches_tracked", | |
| "layer3.5.bn2.num_batches_tracked", | |
| "layer4.0.bn1.num_batches_tracked", | |
| "layer4.0.bn2.num_batches_tracked", | |
| "layer4.0.downsample.1.num_batches_tracked", | |
| "layer4.1.bn1.num_batches_tracked", | |
| "layer4.1.bn2.num_batches_tracked", | |
| "layer4.2.bn1.num_batches_tracked", | |
| "layer4.2.bn2.num_batches_tracked", | |
| ] | |
| assert not any( | |
| key in state_dict.keys() for key in keys_missing | |
| ), "key present that should be missing" | |
| for key in keys_missing: | |
| state_dict[key] = torch.as_tensor(0) | |
| torch.save(state_dict, "pytorch_model.pt") | |
| save_file(state_dict, "model.safetensors") | |
| model = resnet34(weights=None) | |
| model.fc = torch.nn.Linear(model.fc.in_features, out_features=5, bias=True) | |
| model.load_state_dict(state_dict) | |
| model_jit = torch.jit.script(model, example_inputs=[(torch.ones(1, 3, 224, 224),)]) | |
| torch.jit.save(model_jit, "torchscript_model.bin") | |