Script Fairseq transformer #1620
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Differential Revision: D19382299 fbshipit-source-id: 56cbdc3462a19ff87d3c9b8b79878ed3b44806f9
Summary: Pull Request resolved: fairinternal/fairseq-py#1011 Pull Request resolved: facebookresearch#1620 Make Fairseq transformer scriptable. Discussion points on possible code refactoring: (1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too. (2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py) Differential Revision: D19234599 fbshipit-source-id: 64b8a64995bd2bf9a24f6b0665609a2856dad840
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Summary: Pull Request resolved: fairinternal/fairseq-py#1011 Pull Request resolved: facebookresearch/fairseq#1620 Make Fairseq transformer scriptable. Discussion points on possible code refactoring: (1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too. (2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py) Reviewed By: myleott Differential Revision: D19234599 fbshipit-source-id: db3dd364ecf3ae14fb7ac8c0928bd0ebe250f19d
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Summary: Pull Request resolved: fairinternal/fairseq-py#1011 Pull Request resolved: facebookresearch#1620 Make Fairseq transformer scriptable. Discussion points on possible code refactoring: (1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too. (2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py) Reviewed By: myleott Differential Revision: D19234599 fbshipit-source-id: db3dd364ecf3ae14fb7ac8c0928bd0ebe250f19d
yzpang
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Feb 19, 2021
Summary: Pull Request resolved: fairinternal/fairseq-py#1011 Pull Request resolved: facebookresearch/fairseq#1620 Make Fairseq transformer scriptable. Discussion points on possible code refactoring: (1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too. (2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py) Reviewed By: myleott Differential Revision: D19234599 fbshipit-source-id: db3dd364ecf3ae14fb7ac8c0928bd0ebe250f19d
yzpang
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Feb 19, 2021
Summary: Pull Request resolved: fairinternal/fairseq-py#1011 Pull Request resolved: facebookresearch/fairseq#1620 Make Fairseq transformer scriptable. Discussion points on possible code refactoring: (1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too. (2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py) Reviewed By: myleott Differential Revision: D19234599 fbshipit-source-id: db3dd364ecf3ae14fb7ac8c0928bd0ebe250f19d
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Summary:
Make Fairseq transformer scriptable. Discussion points on code quality:
(1) Original decoder output is a tuple (x, {"attn": attn, "inner_states": inner_states}). TorchScript does not support dictionary with values of different types (attn: Tensor, inner_states: List[Tensor]). Current workaround is to use [attn] for attention field and access via output["attn"][0] in downstream. This is currently used in fairspeq custom transformer code. Another (maybe) cleaner alternative is to use namedtuple for decoder output but involves tons of downstream changes too.
(2) Currently TorchScript doesn't support **kwargs. Some unused arguments might get passed in due to polymorphism. Now the only workaround I can think of is to add possible unused arguments, (e.g. line 666 in transformer.py)
Differential Revision: D19234599