code: def pad_mixture_dimensions(
      x, mixture_distribution, categorical_distribution, event_ndims
  ):
      """Pad dimensions of event tensors for mixture distributions.
  
      See `Mixture._sample_n` and `MixtureSameFamily._sample_n` for usage examples.
  
      Args:
        x: event tensor to pad.
        mixture_distribution: Base distribution of the mixture.
        categorical_distribution: `Categorical` distribution that mixes the base
          distribution.
        event_ndims: Integer specifying the number of event dimensions in the event
          tensor.
  
      Returns:
        A padded version of `x` that can broadcast with `categorical_distribution`.
      """
      with tf.name_scope("pad_mix_dims"):
  
          def _get_ndims(d):
              if tensorshape_util.rank(d.batch_shape) is not None:
                  return tensorshape_util.rank(d.batch_shape)
              return tf.shape(d.batch_shape_tensor())[0]
  
          dist_batch_ndims = _get_ndims(mixture_distribution)
          cat_batch_ndims = _get_ndims(categorical_distribution)
          pad_ndims = tf.where(
              categorical_distribution.is_scalar_batch(),
              dist_batch_ndims,
              dist_batch_ndims - cat_batch_ndims,
          )
          s = tf.shape(x)
          x = tf.reshape(
              x,
              shape=tf.concat(
                  [
                      s[:-1],
                      tf.ones([pad_ndims], dtype=tf.int32),
                      s[-1:],
                      tf.ones([event_ndims], dtype=tf.int32),
                  ],
                  axis=0,
              ),
          )
          return x
  
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 10 for calling a global function with example usage: pad_mixture_dimensions(x, mixture_distribution, categorical_distribution, event_ndims) and returns: x, tf, tensorshape_util