[using stable PyTorch 1.9] 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]

[monajalal]

Regarding https://github.com/mvasil/fashion-compatibility/pull/13

If you run the code in the current stable version of PyTorch 1.9, we will have:

(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]

[monajalal]

changed line 118 of type_specific_network.py

from: norm = torch.norm(masked_embedding, p=2, dim=2) + 1e-10 to: norm = torch.norm(masked_embedding, p=2, dim=2, keepdim=True) + 1e-10

This is how the result of running it looks like:

[jalal@goku fashion-compatibility]$ source /scratch3/venv/fashcomp/bin/activate
(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)

test set: Compat AUC: 0.88 FITB: 57.6

[marzooq-unbxd]

@monajalal I dont think we should use this keepdim=True This results in the embedding shape itself changing for eg: 66 to 67