code: def _evaluate(tensor):
      """Returns the numpy value of a tensor."""
      if context.executing_eagerly():
          return tensor.numpy()
      return ops.get_default_session().run(tensor)
  
imports: import collections
  import copy
  import os.path
  import re
  import time
  from google.protobuf import text_format
  from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.checkpoint import checkpoint_options
  from tensorflow.python.eager import context
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import training_util
  from tensorflow.python.training.checkpoint_state_pb2 import CheckpointState
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: _evaluate(tensor) and returns: ops, tensor