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fix #1034

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thomwolf
2019-08-20 12:20:21 +02:00
parent 53c8f700f4
commit 6d0aa73981
1 changed files with 4 additions and 2 deletions
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6
pytorch_transformers/modeling_xlm.py
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@@ -440,8 +440,10 @@ XLM_INPUTS_DOCSTRING = r"""
Indices are selected in the vocabulary (unlike BERT which has a specific vocabulary for segment indices).
**langs**: (`optional`) ``torch.LongTensor`` of shape ``(batch_size, sequence_length)``:
A parallel sequence of tokens to be used to indicate the language of each token in the input.
Indices are selected in the pre-trained language vocabulary,
i.e. in the range ``[0, config.n_langs - 1[``.
Indices are languages ids which can be obtained from the language names by using two conversion mappings
provided in the configuration of the model (only provided for multilingual models).
More precisely, the `language name -> language id` mapping is in `model.config.lang2id` (dict str -> int) and
the `language id -> language name` mapping is `model.config.id2lang` (dict int -> str).
**attention_mask**: (`optional`) ``torch.FloatTensor`` of shape ``(batch_size, sequence_length)``:
Mask to avoid performing attention on padding token indices.
Mask values selected in ``[0, 1]``: