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Summary: Pull Request resolved: pytorch#332 To allow efficient use of fork/join annotation, we return an empty tensor instead of `None` for `encoder_padding_mask` from transformer encoder in the unmasked/inference case. Note that this slight hack is preferable to more far-reaching changes in, e.g., Fairseq multihead_attention. Differential Revision: D13969691 fbshipit-source-id: 5b6106d8f4ac311ca4a5708898639b18ab2be07d
Differential Revision: D13969501 fbshipit-source-id: 525464bd46f7d5c925e2392ba93f6ef6533dfb63
Summary: Pull Request resolved: pytorch#332 To allow efficient use of fork/join annotation, we return an empty tensor instead of `None` for `encoder_padding_mask` from transformer encoder in the unmasked/inference case. Note that this slight hack is preferable to more far-reaching changes in, e.g., Fairseq multihead_attention. Differential Revision: D13969691 fbshipit-source-id: 862ed44019012449554527f236cb344046c75184
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Summary:
To allow efficient use of fork/join annotation, we return an empty tensor instead of
Noneforencoder_padding_maskfrom transformer encoder in the unmasked/inference case.Note that this slight hack is preferable to more far-reaching changes in, e.g., Fairseq multihead_attention.
Differential Revision: D13969691