class_docstr: Defines the interface for TF metrics.
docstr: Initializes this Metric's variables.
  
  Should be called after variables are created in the first execution
  of `__call__()`. If using graph execution, the return value should be
  `run()` in a session before running the op returned by `__call__()`.
  (See example above.)
  
  Returns:
    If using graph execution, this returns an op to perform the
    initialization. Under eager execution, the variables are reset to their
    initial values as a side effect and this function returns None.
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code: def init_variables(self):
      """Initializes this Metric's variables.
  
      Should be called after variables are created in the first execution
      of `__call__()`. If using graph execution, the return value should be
      `run()` in a session before running the op returned by `__call__()`.
      (See example above.)
  
      Returns:
        If using graph execution, this returns an op to perform the
        initialization. Under eager execution, the variables are reset to their
        initial values as a side effect and this function returns None.
      """
      if not tf.executing_eagerly():
          return tf.compat.v1.group(
              [v.initializer for v in self.variables]
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.utils import common
label_desc: Use image node_id 5 for calling the TFStepMetric obj's underlying member method code with example usage: obj.init_variables() and returns: tf