def stddev(self, name="<STR_LIT>", **kwargs):
with self._name_scope(name):<EOL><INDENT>try:<EOL><INDENT>return self._stddev(**kwargs)<EOL><DEDENT>except NotImplementedError as original_exception:<EOL><INDENT>try:<EOL><INDENT>return tf.sqrt(self._variance(**kwargs))<EOL><DEDENT>except NotImplementedError:<EOL><INDENT>raise original_exception<EOL><DEDENT><DEDENT><DEDENT>
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.
          **kwargs: Named arguments forwarded to subclass implementation.

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