d97a73f8ea19e52166702dd448dea03e3a6be95b,opennmt/models/sequence_classifier.py,SequenceClassifier,__init__,#SequenceClassifier#Any#Any#Any#Any#Any#Any#,15

Before Change

        daisy_chain_variables=daisy_chain_variables)
    self.encoder = encoder
    self.encoding = encoding.lower()
    if self.encoding not in ("average", "last"):
      raise ValueError("Invalid encoding vector: {}".format(self.encoding))

  def _call(self, features, labels, params, mode):
    training = mode == tf.estimator.ModeKeys.TRAIN
    with tf.variable_scope("encoder"):
      inputs = self.features_inputter.make_inputs(features, training=training)

After Change

    self.encoder = encoder
    self.encoding = encoding.lower()
    if self.encoding not in ("average", "last"):
      raise ValueError("Invalid encoding vector: {}".format(self.encoding))

  def _call(self, features, labels, params, mode):
    training = mode == tf.estimator.ModeKeys.TRAIN
    with tf.variable_scope("encoder"):
      inputs = self.features_inputter.make_inputs(features, training=training)

Instances