[quant][embedding qat] Add eager QAT test for EmbeddingBag+Linear model #66334
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…+Linear model" [ghstack-poisoned]
…+Linear model" [ghstack-poisoned]
…+Linear model" [ghstack-poisoned]
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@b-koopman has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
jingsh
reviewed
Oct 13, 2021
supriyar
reviewed
Oct 14, 2021
HDCharles
reviewed
Oct 14, 2021
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| def forward(self, input: torch.Tensor, offsets: Optional[torch.Tensor] = None, | ||
| per_sample_weights: Optional[torch.Tensor] = None): | ||
| x = self.emb(input, offsets, per_sample_weights) |
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isn't the input to nn.quantized.EmbeddingBag supposed to be quantized, so sholdn't this be inside the QuantStub()?
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Input indices shouldn't be quantized, only the weights, so this shouldn't be wrapped in quant/dequant as you would expect for a linear layer.
…+Linear model" Differential Revision: [D31618283](https://our.internmc.facebook.com/intern/diff/D31618283) [ghstack-poisoned]
HDCharles
approved these changes
Oct 18, 2021
…+Linear model" Differential Revision: [D31618283](https://our.internmc.facebook.com/intern/diff/D31618283) [ghstack-poisoned]
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@b-koopman has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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Stack from ghstack:
Differential Revision: D31618283