tensorflow_probability/python/distributions/deterministic.py
def _get_tol(tol, dtype, validate_args):
  """Gets a Tensor of type `dtype`, 0 if `tol` is None, validation optional."""
  if tol is None:
    return tf.convert_to_tensor(value=0, dtype=dtype)

  tol = tf.convert_to_tensor(value=tol, dtype=dtype)
  if validate_args:
    tol = distribution_util.with_dependencies([
        assert_util.assert_non_negative(
            tol, message="Argument 'tol' must be non-negative")
    ], tol)
  return tol
def _get_tol(tol, dtype, validate_args):
  """Gets a Tensor of type `dtype`, 0 if `tol` is None, validation optional."""
  if tol is None:
    return tf.convert_to_tensor(value=0, dtype=dtype)

  tol = tf.convert_to_tensor(value=tol, dtype=dtype)
  if validate_args:
    tol = distribution_util.with_dependencies([
        assert_util.assert_non_negative(
            tol, message="Argument 'tol' must be non-negative")
    ], tol)
  return tol
Gets a Tensor of type `dtype`, 0 if `tol` is None, validation optional.