Add HAT implementation files

modelling_hat.py

@@ -1186,6 +1186,7 @@ class HATModelForDocumentRepresentation(HATPreTrainedModel):
         super().__init__(config)
         self.num_labels = config.num_labels
         self.config = config
+        self.max_sentence_length = config.max_sentence_length
 
         self.hi_transformer = HATModel(config)
         self.pooler = HATPooler(config, pooling=pooling)
@@ -1233,7 +1234,7 @@ class HATModelForDocumentRepresentation(HATPreTrainedModel):
             return_dict=return_dict,
         )
         sequence_output = outputs[0]
-        pooled_outputs = self.pooler(sequence_output)
+        pooled_outputs = self.pooler(sequence_output[:, ::self.max_sentence_length])
 
         drp_loss = None
         if labels is not None:
@@ -1832,6 +1833,7 @@ class HATForSequenceClassification(HATPreTrainedModel):
         super().__init__(config)
         self.num_labels = config.num_labels
         self.config = config
+        self.max_sentence_length = config.max_sentence_length
         self.pooling = pooling
 
         self.hi_transformer = HATModel(config)
@@ -2043,6 +2045,7 @@ class HATForMultipleChoice(HATPreTrainedModel):
         super().__init__(config)
 
         self.pooling = pooling
+        self.max_sentence_length = config.max_sentence_length
         self.hi_transformer = HATModel(config)
         classifier_dropout = (
             config.classifier_dropout if config.classifier_dropout is not None else config.hidden_dropout_prob