code: def mixture_stddev(mixture_weight_vector, mean_vector, stddev_vector):
      """Computes the standard deviation of a mixture distribution.
  
      This function works regardless of the component distribution, so long as
      each component's mean and standard deviation can be provided.
  
      Args:
        mixture_weight_vector: A Tensor with shape `batch_shape + [num_components]`
        mean_vector: A Tensor of mixture component means. Has shape `batch_shape +
          [num_components]`.
        stddev_vector: A Tensor of mixture component standard deviations. Has
          shape `batch_shape + [num_components]`.
  
      Returns:
        A 1D tensor of shape `batch_shape` representing the standard deviation of
        the mixture distribution with given weights and component means and standard
        deviations.
      Raises:
        ValueError: If the shapes of the input tensors are not as expected.
      """
      if not tensorshape_util.is_compatible_with(
          mean_vector.shape, mixture_weight_vector.shape
      ):
          raise ValueError(
              "Expecting means to have same shape as mixture weights."
          )
      if not tensorshape_util.is_compatible_with(
          stddev_vector.shape, mixture_weight_vector.shape
      ):
          raise ValueError(
              "Expecting stddevs to have same shape as mixture weights."
          )
  
      weighted_average_means = tf.reduce_sum(
          mixture_weight_vector * mean_vector, axis=-1, keepdims=True
      )
      deviations = mean_vector - weighted_average_means
      return _hypot(
          _weighted_norm(mixture_weight_vector, deviations),
          _weighted_norm(mixture_weight_vector, stddev_vector),
      )
  
imports: import functools
  import hashlib
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 2 for calling a global function with example usage: mixture_stddev(mixture_weight_vector, mean_vector, stddev_vector) and returns: _hypot