class_docstr: Wraps a python metric as a TF metric.
class_docstr_tok: ["Wraps","a","python","metric","as","a","TF","metric","."]
code: def result(self):
      def _result():
          with _check_not_called_concurrently(self._lock):
              return self._py_metric.result()
  
      result_value = tf.py_function(
          _result, [], self._dtype, name="metric_result_py_func"
      )
      if not tf.executing_eagerly():
          result_value.set_shape(())
      return result_value
  
file_path: agents/tf_agents/metrics/tf_py_metric.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import contextlib
  import threading
  import tensorflow
  from tf_agents.metrics import tf_metric
label_desc: Use image node_id 3 for calling the TFPyMetric obj's underlying member method code with example usage: obj.result() and returns: result_value, self