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fixed BertForMultipleChoice model init and forward pass

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David Pollack
2019-04-15 10:38:01 +02:00
parent 616743330e
commit 38ba7b439b
1 changed files with 3 additions and 3 deletions
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6
pytorch_pretrained_bert/modeling.py
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@@ -1034,13 +1034,13 @@ class BertForMultipleChoice(BertPreTrainedModel):
self.num_choices = num_choices self.num_choices = num_choices
self.bert = BertModel(config) self.bert = BertModel(config)
self.dropout = nn.Dropout(config.hidden_dropout_prob) self.dropout = nn.Dropout(config.hidden_dropout_prob)
self.classifier = nn.Linear(config.hidden_size, 1) self.classifier = nn.Linear(config.hidden_size, num_choices)
self.apply(self.init_bert_weights) self.apply(self.init_bert_weights)
def forward(self, input_ids, token_type_ids=None, attention_mask=None, labels=None): def forward(self, input_ids, token_type_ids=None, attention_mask=None, labels=None):
flat_input_ids = input_ids.view(-1, input_ids.size(-1)) flat_input_ids = input_ids.view(-1, input_ids.size(-1))
flat_token_type_ids = token_type_ids.view(-1, token_type_ids.size(-1)) flat_token_type_ids = token_type_ids.view(-1, token_type_ids.size(-1)) if token_type_ids is not None else None
flat_attention_mask = attention_mask.view(-1, attention_mask.size(-1)) flat_attention_mask = attention_mask.view(-1, attention_mask.size(-1)) if attention_mask is not None else None
_, pooled_output = self.bert(flat_input_ids, flat_token_type_ids, flat_attention_mask, output_all_encoded_layers=False) _, pooled_output = self.bert(flat_input_ids, flat_token_type_ids, flat_attention_mask, output_all_encoded_layers=False)
pooled_output = self.dropout(pooled_output) pooled_output = self.dropout(pooled_output)
logits = self.classifier(pooled_output) logits = self.classifier(pooled_output)