code: def _choose_direction_batched(point, seed_stream):
      with tf.name_scope("choose_direction_batched"):
          batch_size = tf.shape(input=point.state[0])[0]
          dtype = point.state[0].dtype
          return tfp_random.rademacher(
              [batch_size], dtype=dtype, seed=seed_stream()
          )
  
imports: import collections
  import functools
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python import random
  from tensorflow_probability.python.experimental import auto_batching
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.util.seed_stream import SeedStream
label_desc: Use image node_id 14 for calling a global function with example usage: _choose_direction_batched(point, seed_stream) and returns: tfp_random