code: def result(self):
      def my_func(x):
          if version.parse(tf.__version__) >= version.parse("2.0.0"):
              return (
                  tf.random.get_global_generator()
                  .uniform([1], dtype=tf.float64)
                  .numpy()[0]
              )
          else:
              return 0.0
  
      return tf.compat.v1.py_func(
          my_func, [tf.ones([1], dtype=tf.float64)], tf.float64
      )
  
imports: import random
  import numpy
  import tensorflow
  from packaging import version
  from determined.keras import TFKerasTrial, TFKerasTrialContext
label_desc: Use image node_id 2 for calling the TensorFlowRandomMetric obj's underlying member method code with example usage: obj.result() and returns: tf, tf, int