INNER CODE UNIT · Python

_init_embedding

ematvey/hierarchical-attention-networks · HAN_model.py:93

  def _init_embedding(self, scope):
    with tf.variable_scope(scope):
      with tf.variable_scope("embedding") as scope:
        self.embedding_matrix = tf.get_variable(
          name="embedding_matrix",
          shape=[self.vocab_size, self.embedding_size],
          initializer=layers.xavier_initializer(),
          dtype=tf.float32)
        self.inputs_embedded = tf.nn.embedding_lookup(
          self.embedding_matrix, self.inputs)

  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

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