model forwards can take an inputs_embeds param #1695
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@@ Coverage Diff @@
## master #1695 +/- ##
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+ Coverage 83.95% 84.03% +0.07%
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Files 94 94
Lines 13951 14021 +70
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+ Hits 11713 11782 +69
- Misses 2238 2239 +1
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julien-c
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thomwolf
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Nov 1, 2019
| elif inputs_embeds is not None: | ||
| input_shape = inputs_embeds.size()[:-1] | ||
| else: | ||
| raise ValueError("You have to specify either input_ids or inputs_embeds") |
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Should we raise an error if both are provided?
If not we should be explicit about which one has priority in the docstring (this input should be in the docstring anyway).
thomwolf
reviewed
Nov 1, 2019
| position_ids = torch.arange(past_length, input_ids.size(-1) + past_length, dtype=torch.long, device=input_ids.device) | ||
| position_ids = position_ids.unsqueeze(0).expand_as(input_ids) | ||
| device = input_ids.device if input_ids is not None else inputs_embeds.device | ||
| position_ids = torch.arange(past_length, input_shape[-1] + past_length, dtype=torch.long, device=device) |
thomwolf
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thomwolf
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Nov 5, 2019
| input_ids = input_ids.transpose(0, 1).contiguous() | ||
| qlen, bsz = input_ids.size() | ||
| elif inputs_embeds is not None: | ||
| inputs_embeds = inputs_embeds.transpose(0, 1).contiguous() |
thomwolf
reviewed
Nov 5, 2019
| model.eval() | ||
|
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||
| wte = model.get_input_embeddings() | ||
| inputs_dict["inputs_embeds"] = wte(input_ids) |
|
LGTM. |
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