charlesdong1991 / interpretable-han-for-document-classification-with-keras Goto Github PK

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ValueError                                Traceback (most recent call last)
<ipython-input-67-285d332a8fb7> in <module>
----> 1 sent_att = han.show_sent_attention(data[i])
      2 sent_tokenized_review = sent_tokenize(all_text[i])
      3 
      4 temp_df = han.sent_att_to_df(sent_tokenized_reviews, sent_att)

~/Privacy_Work/interpretable-han-for-document-classification-with-keras/han/model.py in show_sent_attention(self, x)
    183         )(prev_tensor)
    184 
--> 185         return Model(self.model.input, dummy_layer).predict(x)
    186 
    187     @staticmethod

/usr/local/lib/python3.6/dist-packages/keras/engine/training.py in predict(self, x, batch_size, verbose, steps, callbacks, max_queue_size, workers, use_multiprocessing)
   1439 
   1440         # Case 2: Symbolic tensors or Numpy array-like.
-> 1441         x, _, _ = self._standardize_user_data(x)
   1442         if self.stateful:
   1443             if x[0].shape[0] > batch_size and x[0].shape[0] % batch_size != 0:

/usr/local/lib/python3.6/dist-packages/keras/engine/training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, check_array_lengths, batch_size)
    577             feed_input_shapes,
    578             check_batch_axis=False,  # Don't enforce the batch size.
--> 579             exception_prefix='input')
    580 
    581         if y is not None:

/usr/local/lib/python3.6/dist-packages/keras/engine/training_utils.py in standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)
    133                         ': expected ' + names[i] + ' to have ' +
    134                         str(len(shape)) + ' dimensions, but got array '
--> 135                         'with shape ' + str(data_shape))
    136                 if not check_batch_axis:
    137                     data_shape = data_shape[1:]

ValueError: Error when checking input: expected input_1 to have 3 dimensions, but got array with shape (10, 100)