(dataset,
                               training,
                               output_features='targets',
                               eos=1)
return dataset.map(add_eos)
Adds `EOS` to all features in `output_features`.
Adds `EOS` to all features in `output_features`.
Adds EOS to all features in output_features .
def add_eos_to_output_features(dataset,
                               training,
                               output_features='targets',
                               eos=1):
  """Adds `EOS` to all features in `output_features`."""
  del training
  if not isinstance(output_features, (list, tuple)):
    output_features = [output_features]

  def add_eos(x):
    for output_feature in output_features:
      x[output_feature] = tf.concat([x[output_feature], [eos]], axis=0)
    return x

  return dataset.map(add_eos)
def add_eos_to_output_features ( dataset , training , output_features = 'targets' , eos = 1 ) : del training if not isinstance ( output_features , ( list , tuple ) ) : output_features = [ output_features ] def add_eos ( x ) : for output_feature in output_features : x [ output_feature ] = tf . concat ( [ x [ output_feature ] , [ eos ] ] , axis = 0 ) return x return dataset . map ( add_eos )