code: def _random_mask(batch, dtype, seed):
      return tf.cast(
          tf.random.stateless_uniform(
              batch, maxval=2, dtype=tf.int32, seed=seed
          ),
          dtype=dtype,
      )
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import linear_gaussian_ssm
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.experimental.parallel_filter import parallel_kalman_filter_lib
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 3 for calling a global function with example usage: _random_mask(batch, dtype, seed) and returns: tf