INNER CODE UNIT · Python

_init_body

ematvey/hierarchical-attention-networks · HAN_model.py:104

  def _init_body(self, scope):
    with tf.variable_scope(scope):

      word_level_inputs = tf.reshape(self.inputs_embedded, [
        self.document_size * self.sentence_size,
        self.word_size,
        self.embedding_size
      ])
      word_level_lengths = tf.reshape(
        self.word_lengths, [self.document_size * self.sentence_size])

      with tf.variable_scope('word') as scope:
        word_encoder_output, _ = bidirectional_rnn(
          self.word_cell, self.word_cell,
          word_level_inputs, word_level_lengths,
          scope=scope)

        with tf.variable_scope('attention') as scope:

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