Method stddev

tensorflow/python/ops/distributions/distribution.py:1061–1088

Standard deviation. Standard deviation is defined as, ```none stddev = E[(X - E[X])**2]**0.5 ``` where `X` is the random variable associated with this distribution, `E` denotes expectation, and `stddev.shape = batch_shape + event_shape`. Args: name: Python `str`

(self, name="stddev")

        type(self).__name__))

  def stddev(self, name="stddev"):
    """Standard deviation.

    Standard deviation is defined as,

    ```none
    stddev = E[(X - E[X])**2]**0.5
    ```

    where `X` is the random variable associated with this distribution, `E`
    denotes expectation, and `stddev.shape = batch_shape + event_shape`.

    Args:
      name: Python `str` prepended to names of ops created by this function.

    Returns:
      stddev: Floating-point `Tensor` with shape identical to
        `batch_shape + event_shape`, i.e., the same shape as `self.mean()`.
    """

    with self._name_scope(name):
      try:
        return self._stddev()
      except NotImplementedError as original_exception:
        try:
          return math_ops.sqrt(self._variance())
        except NotImplementedError:
          raise original_exception

  def _covariance(self):
    raise NotImplementedError("covariance is not implemented: {}".format(