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Upgrade Roberta tokenizer #1821

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merged 13 commits into from
Mar 28, 2022
3 changes: 2 additions & 1 deletion paddlenlp/transformers/auto/tokenizer.py
Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,8 @@
("MBartTokenizer", "mbart"),
("MPNetTokenizer", "mpnet"),
("NeZhaTokenizer", "nezha"),
("RobertaTokenizer", "roberta"),
("RobertaChineseTokenizer", "roberta"),
("RobertaBPETokenizer", "roberta"),
("RoFormerTokenizer", "roformer"),
("ReformerTokenizer", "reformer"),
("SqueezeBertTokenizer", "squeezebert"),
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4 changes: 3 additions & 1 deletion paddlenlp/transformers/bert/modeling.py
Original file line number Diff line number Diff line change
Expand Up @@ -499,7 +499,9 @@ def forward(self,
else:
if attention_mask.ndim == 2:
# attention_mask [batch_size, sequence_length] -> [batch_size, 1, 1, sequence_length]
attention_mask = attention_mask.unsqueeze(axis=[1, 2])
attention_mask = attention_mask.unsqueeze(
axis=[1, 2]).astype(paddle.get_default_dtype())
attention_mask = (1.0 - attention_mask) * -1e4
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这里和其他模型中ndim==2的行为是一致的不,是已经统一了mask的这个语义了吗

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还没有统一,这个pr统一了 bert 和 roberta


embedding_output = self.embeddings(
input_ids=input_ids,
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