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mvasil / fashion-compatibility

Learning Type-Aware Embeddings for Fashion Compatibility
BSD 3-Clause "New" or "Revised" License
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return _VF.norm(input, p, _dim, keepdim=keepdim) # type: ignore[attr-defined] IndexError: Dimension out of range (expected to be in range of [-2, 1], but got 2) #26

Closed monajalal closed 3 years ago

monajalal commented 3 years ago 
(fashcomp) [jalal@goku fashion-compatibility]$ python main.py --name test_baseline --learned --l2_embed --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, " +
  + Number of params: 3191808
<class 'torch.utils.data.dataloader.DataLoader'>
/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 324, in <module>
    main()    
  File "main.py", line 167, in main
    train(train_loader, tnet, criterion, optimizer, epoch)
  File "main.py", line 202, in train
    acc, loss_triplet, loss_mask, loss_embed, loss_vse, loss_sim_t, loss_sim_i = tnet(anchor, far, close)
  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/tripletnet.py", line 146, in forward
    acc, loss_triplet, loss_sim_i, loss_mask, loss_embed, general_x, general_y, general_z = self.image_forward(x, y, z)
  File "/scratch3/research/code/fashion/fashion-compatibility/tripletnet.py", line 74, in image_forward
    embedded_x, masknorm_norm_x, embed_norm_x, general_x = self.embeddingnet(x.images, c)
  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 147, in forward
    masked_embedding = torch.nn.functional.normalize(masked_embedding, p=2.0, dim=2, eps=1e-10, out=None)
  File "/scratch3/venv/fashcomp/lib/python3.8/site-packages/torch/nn/functional.py", line 4428, in normalize
    denom = input.norm(p, dim, keepdim=True).clamp_min(eps).expand_as(input)
  File "/scratch3/venv/fashcomp/lib/python3.8/site-packages/torch/_tensor.py", line 417, in norm
    return torch.norm(self, p, dim, keepdim, dtype=dtype)
  File "/scratch3/venv/fashcomp/lib/python3.8/site-packages/torch/functional.py", line 1356, in norm
    return _VF.norm(input, p, _dim, keepdim=keepdim)  # type: ignore[attr-defined]
IndexError: Dimension out of range (expected to be in range of [-2, 1], but got 2)

I have the following in type_specific_network.py:

if self.l2_norm:
    ##norm = torch.norm(masked_embedding, p=2, dim=1) + 1e-10
    ##masked_embedding = masked_embedding / norm.expand_as(masked_embedding)
    masked_embedding = torch.nn.functional.normalize(masked_embedding, p=2.0, dim=2, eps=1e-10, out=None)
monajalal commented 3 years ago

silly copy-paste mistake! masked_embedding = F.normalize(masked_embedding, p=2.0, dim=1, eps=1e-10)