class_docstr: Test tf_policy which contains only trainable variables.
class_docstr_tok: ["Test","tf_policy","which","contains","only","trainable","variables","."]
docstr: Initializes policy containing variables with specified value.
  
  Args:
    init_var_value: A scalar specifies the initial value of all variables.
    var_scope: A String defines variable scope.
    name: The name of this policy. All variables in this module will fall
      under that name. Defaults to the class name.
docstr_tok: ["Initializes","policy","containing","variables","with","specified","value",".","Args",":","init_var_value",":","A","scalar","specifies","the","initial","value","of","all","variables",".","var_scope",":","A","String","defines","variable","scope",".","name",":","The","name","of","this","policy",".","All","variables","in","this","module","will","fall","under","that","name",".","Defaults","to","the","class","name","."]
code: def __init__(self, init_var_value, var_scope, name=None):
      """Initializes policy containing variables with specified value.
  
      Args:
        init_var_value: A scalar specifies the initial value of all variables.
        var_scope: A String defines variable scope.
        name: The name of this policy. All variables in this module will fall
          under that name. Defaults to the class name.
      """
      tf.Module.__init__(self, name=name)
      with tf.compat.v1.variable_scope(var_scope):
          self._variables_list = [
              common.create_variable(
                  "var_1", init_var_value, [3, 3], dtype=tf.float32
              ),
              common.create_variable(
                  "var_2", init_var_value, [5, 5], dtype=tf.float32
              ),
          ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import cast
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 to create a new TfPolicyHoldsVariables object from inherited base classes: tf_policy with example: obj = TfPolicyHoldsVariables(init_var_value, var_scope, name)