code: def _maybe_broadcast_volatility(volatility_parts, state_parts):
      """Helper to broadcast `volatility_parts` to the shape of `state_parts`."""
      return [
          v + tf.zeros_like(sp)
          for v, sp in zip(volatility_parts, state_parts)
      ]
  
imports: import collections
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.math.diag_jacobian import diag_jacobian
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc import metropolis_hastings
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 5 for calling a global function with example usage: _maybe_broadcast_volatility(volatility_parts, state_parts) and returns: unknown