code: def _conform(ts):
      """Broadcast all arguments to a common shape."""
  
      shape = functools.reduce(
          tf.broadcast_static_shape, [a.shape for a in ts]
      )
      return [tf.broadcast_to(a, shape) for a in ts]
  
imports: import functools
  import itertools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import hidden_markov_model
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions import sample
  import tensorflow_probability.python.experimental.marginalize
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling a global function with example usage: _conform(ts) and returns: unknown