2faf7acd48088783ab4d8507cc3eb1e74430b3ad,sonnet/src/reshape.py,Reshape,__call__,#Reshape#Any#,170

Before Change

        dimension and doesn"t actually need reshaping).
    
    self._initialize(inputs)
    return _batch_reshape(inputs,
                          output_shape=self._output_shape,
                          preserve_dims=self._preserve_dims)

  @base.no_name_scope
  def reversed(self, name=None):
    Returns inverse batch reshape.

After Change

          inputs,
          tuple(preserved_shape) + output_shape)
    else:
      dynamic_preserved_shape = tf.shape(inputs)[:self._preserve_dims]
      output = tf.reshape(
          inputs,
          tf.concat([dynamic_preserved_shape, output_shape], axis=0))
    return output

  @base.no_name_scope
  def reversed(self, name=None):
    Returns inverse batch reshape.

Instances