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How to implement embedding + mask in torch 1.12? #117

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pingguokiller opened this issue Sep 24, 2019 · 2 comments
Open

How to implement embedding + mask in torch 1.12? #117

pingguokiller opened this issue Sep 24, 2019 · 2 comments

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@pingguokiller
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In rnn/utils.py

The below code is meaning add a mask to embeding. But it run error at torch 1.12. Does anyone know to realize it at torch 1.12? Thank you!

X = embed._backend.Embedding.apply(words, masked_embed_weight,
padding_idx, embed.max_norm, embed.norm_type,
embed.scale_grad_by_freq, embed.sparse
)

@dxbdxx
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dxbdxx commented Oct 10, 2019

Maybe it's torch.nn.functional.embedding(). The functions' parameters are similar but I am not sure they are the same.

@william-yl-gu
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I solved this problem by changing this code. The solution is referred from [site1] and [site2]

Replace:

    X = embed._backend.Embedding.apply(words, masked_embed_weight,
                                       padding_idx, embed.max_norm, embed.norm_type,
                                       embed.scale_grad_by_freq, embed.sparse
                                       )

with:

  from torch.nn import functional as F
  ...
  X = F.embedding(
       words, masked_embed_weight,
       padding_idx,
       embed.max_norm, embed.norm_type,
       embed.scale_grad_by_freq, embed.sparse
   )

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3 participants