tensorflow_probability/python/edward2/generated_random_variables.py
def _build_custom_rv(distribution, sample_shape, value, name):
  """RandomVariable constructor with a dummy name argument."""
  # Program transformations (e.g., `make_log_joint_fn`) assume that
  # the traced constructor has `name` and `value` kwargs, enabling
  # them to override the value of an RV according to its name.
  # User-defined RVs inherit their name from the provided
  # distribution; this helper method exposes the name as a dummy kwarg
  # so that it's visible to program transformations.
  del name  # unused
  return RandomVariable(distribution=distribution,
                        sample_shape=sample_shape,
                        value=value)
def _build_custom_rv(distribution, sample_shape, value, name):
  # Program transformations (e.g., `make_log_joint_fn`) assume that
  # the traced constructor has `name` and `value` kwargs, enabling
  # them to override the value of an RV according to its name.
  # User-defined RVs inherit their name from the provided
  # distribution; this helper method exposes the name as a dummy kwarg
  # so that it's visible to program transformations.
  del name  # unused
  return RandomVariable(distribution=distribution,
                        sample_shape=sample_shape,
                        value=value)
def _build_custom_rv ( distribution , sample_shape , value , name ) : # Program transformations (e.g., `make_log_joint_fn`) assume that # the traced constructor has `name` and `value` kwargs, enabling # them to override the value of an RV according to its name. # User-defined RVs inherit their name from the provided # distribution; this helper method exposes the name as a dummy kwarg # so that it's visible to program transformations. del name # unused return RandomVariable ( distribution = distribution , sample_shape = sample_shape , value = value )
RandomVariable constructor with a dummy name argument.
RandomVariable constructor with a dummy name argument .