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Add a script to check all models are tested and documented (#6298)

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* Add a script to check all models are tested and documented

* Apply suggestions from code review

Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>

* Address comments

Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>
This commit is contained in:
Sylvain Gugger
2020-08-07 09:18:37 -04:00
committed by GitHub
parent e1638dce16
commit 6ba540b747
12 changed files with 351 additions and 2 deletions
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2
src/transformers/modeling_electra.py
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@@ -879,6 +879,7 @@ class ElectraForMultipleChoice(ElectraPreTrainedModel):
inputs_embeds=None,
labels=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
):
r"""
@@ -908,6 +909,7 @@ class ElectraForMultipleChoice(ElectraPreTrainedModel):
head_mask=head_mask,
inputs_embeds=inputs_embeds,
output_attentions=output_attentions,
output_hidden_states=output_hidden_states,
return_dict=return_dict,
)

9
src/transformers/modeling_tf_albert.py
View File

@@ -1260,7 +1260,7 @@ class TFAlbertForMultipleChoice(TFAlbertPreTrainedModel, TFMultipleChoiceLoss):
head_mask = inputs.get("head_mask", head_mask)
inputs_embeds = inputs.get("inputs_embeds", inputs_embeds)
output_attentions = inputs.get("output_attentions", output_attentions)
output_hidden_states = inputs.get("output_hidden_states", output_attentions)
output_hidden_states = inputs.get("output_hidden_states", output_hidden_states)
return_dict = inputs.get("return_dict", return_dict)
labels = inputs.get("labels", labels)
assert len(inputs) <= 10, "Too many inputs."
@@ -1279,6 +1279,11 @@ class TFAlbertForMultipleChoice(TFAlbertPreTrainedModel, TFMultipleChoiceLoss):
flat_attention_mask = tf.reshape(attention_mask, (-1, seq_length)) if attention_mask is not None else None
flat_token_type_ids = tf.reshape(token_type_ids, (-1, seq_length)) if token_type_ids is not None else None
flat_position_ids = tf.reshape(position_ids, (-1, seq_length)) if position_ids is not None else None
flat_inputs_embeds = (
tf.reshape(inputs_embeds, (-1, seq_length, shape_list(inputs_embeds)[3]))
if inputs_embeds is not None
else None
)
outputs = self.albert(
flat_input_ids,
@@ -1286,7 +1291,7 @@ class TFAlbertForMultipleChoice(TFAlbertPreTrainedModel, TFMultipleChoiceLoss):
flat_token_type_ids,
flat_position_ids,
head_mask,
inputs_embeds,
flat_inputs_embeds,
output_attentions,
output_hidden_states,
return_dict=return_dict,