code: def bandit_policy_uniform_mask(
      values: types.Tensor, mask: types.Tensor
  ) -> types.Tensor:
      """Set bandit policy type tensor to BanditPolicyType.UNIFORM based on mask.
  
      Set bandit policy type `values` to BanditPolicyType.UNIFORM; returns tensor
      where output[i] is BanditPolicyType.UNIFORM if mask[i] is True, otherwise it
      is left as values[i].
  
      Args:
        values: Tensor containing `BanditPolicyType` enumerations.
        mask: Tensor of the same shape as `values` with boolean flags indicating
          values to set to `BanditPolicyType.UNIFORM`.
  
      Returns:
        Tensor containing `BanditPolicyType` enumerations with masked values.
      """
      return tf.where(
          mask,
          tf.fill(tf.shape(values), BanditPolicyType.UNIFORM),
          values,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import Optional, Sequence, Text, Union
  import tensorflow
  from tf_agents.specs import bandit_spec_utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.typing import types
  from tf_agents.utils import common
label_desc: Use image node_id 8 for calling a global function with example usage: bandit_policy_uniform_mask(values, mask) and returns: tf