当我在稳定的PyTorch 1.9中运行以下(未更改)代码时，我得到以下错误。我如何诊断和修复它?
(fashcomp) [jalal@goku fashion-compatibility]$ python main.py --test --l2_embed --resume runs/nondisjoint_l2norm/model_best.pth.tar --datadir ../../../data/fashion/
/scratch3/venv/fashcomp/lib/python3.8/site-packages/torchvision/transforms/transforms.py:310: UserWarning: The use of the transforms.Scale transform is deprecated, please use transforms.Resize instead.
warnings.warn("The use of the transforms.Scale transform is deprecated, " +
=> loading checkpoint 'runs/nondisjoint_l2norm/model_best.pth.tar'
=> loaded checkpoint 'runs/nondisjoint_l2norm/model_best.pth.tar' (epoch 5)
/scratch3/venv/fashcomp/lib/python3.8/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)
return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
Traceback (most recent call last):
File "main.py", line 312, in <module>
main()
File "main.py", line 149, in main
test_acc = test(test_loader, tnet)
File "main.py", line 244, in test
embeddings.append(tnet.embeddingnet(images).data)
File "/scratch3/venv/fashcomp/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/scratch3/research/code/fashion/fashion-compatibility/type_specific_network.py", line 119, in forward
masked_embedding = masked_embedding / norm.expand_as(masked_embedding)
RuntimeError: The expanded size of the tensor (64) must match the existing size (66) at non-singleton dimension 2. Target sizes: [256, 66, 64]. Tensor sizes: [256, 66]
相关问题:https://github.com/mvasil/fashion-compatibility/pull/13
问题是norm缺少额外的维度:masked_embedding是[256, 66, 64],norm是[256, 66]。您可以通过将这个额外的维度([256, 66, 1])添加到norm来解决这个问题，如下所示:
masked_embedding = masked_embedding / norm.unsqueeze(-1).expand_as(masked_embedding)
或者，通过修改生成norm的调用(这个):
norm = torch.norm(masked_embedding, p=2, dim=2, keepdim=True) + 1e-10