code: def _op_is_in_tf_version(op, version):
      if version == 1:
          return (
              tf_export.get_v1_names(tf_decorator.unwrap(op)[1])
              or op in _V2_OPS_THAT_ARE_DELEGATED_TO_FROM_V1_OPS
          )
      elif version == 2:
          return tf_export.get_v2_names(tf_decorator.unwrap(op)[1])
      else:
          raise ValueError("Expected version 1 or 2.")
  
file_path: tensorflow/tensorflow/python/ops/ragged/ragged_dispatch.py
imports: from tensorflow.python.ops import logging_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_tensor_shape
  from tensorflow.python.util import dispatch
  from tensorflow.python.util import tf_decorator
  from tensorflow.python.util import tf_export
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 4 for calling a global function with example usage: _op_is_in_tf_version(op, version) and returns: unknown, tf_export