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fix #971

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LysandreJik
2019-08-08 10:36:26 -04:00
parent 7729ef7381
commit 7df303f5ad
4 changed files with 6 additions and 6 deletions
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2
pytorch_transformers/modeling_bert.py
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@@ -603,7 +603,7 @@ BERT_INPUTS_DOCSTRING = r"""
:func:`pytorch_transformers.PreTrainedTokenizer.convert_tokens_to_ids` for details.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Segment token indices to indicate first and second portions of the inputs.
Indices are selected in ``[0, 1]``: ``0`` corresponds to a `sentence A` token, ``1``

4
pytorch_transformers/modeling_gpt2.py
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@@ -393,7 +393,7 @@ GPT2_INPUTS_DOCSTRING = r""" Inputs:
:func:`pytorch_transformers.PreTrainedTokenizer.convert_tokens_to_ids` for details.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
A parallel sequence of tokens (can be used to indicate various portions of the inputs).
The embeddings from these tokens will be summed with the respective token embeddings.
@@ -627,7 +627,7 @@ class GPT2DoubleHeadsModel(GPT2PreTrainedModel):
Selected in the range ``[0, input_ids.size(-1) - 1[``.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, num_choices, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, num_choices, sequence_length)``:
A parallel sequence of tokens (can be used to indicate various portions of the inputs).
The embeddings from these tokens will be summed with the respective token embeddings.

4
pytorch_transformers/modeling_openai.py
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@@ -407,7 +407,7 @@ OPENAI_GPT_INPUTS_DOCSTRING = r""" Inputs:
:func:`pytorch_transformers.PreTrainedTokenizer.convert_tokens_to_ids` for details.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
A parallel sequence of tokens (can be used to indicate various portions of the inputs).
The embeddings from these tokens will be summed with the respective token embeddings.
@@ -617,7 +617,7 @@ class OpenAIGPTDoubleHeadsModel(OpenAIGPTPreTrainedModel):
Selected in the range ``[0, input_ids.size(-1) - 1[``.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, num_choices, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, num_choices, sequence_length)``:
A parallel sequence of tokens (can be used to indicate various portions of the inputs).
The embeddings from these tokens will be summed with the respective token embeddings.

2
pytorch_transformers/modeling_xlm.py
View File

@@ -427,7 +427,7 @@ XLM_INPUTS_DOCSTRING = r"""
:func:`pytorch_transformers.PreTrainedTokenizer.convert_tokens_to_ids` for details.
**position_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
Indices of positions of each input sequence tokens in the position embeddings.
Selected in the range ``[0, config.max_position_embeddings - 1[``.
Selected in the range ``[0, config.max_position_embeddings - 1]``.
**token_type_ids**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
A parallel sequence of tokens (can be used to indicate various portions of the inputs).
The embeddings from these tokens will be summed with the respective token embeddings.