class_docstr: Benchmarks for MapDefunOp.
code: def _run(self, op, name, num_iters, benchmark_id):
      wall_time = self.run_op_benchmark(
          op=op, iters=num_iters, warmup=True
      )
      zero_division_delta = 1e-100
      wall_time = wall_time + zero_division_delta
      self.report_benchmark(
          name=name,
          iters=num_iters,
          wall_time=wall_time,
          extras={
              "examples_per_sec": 1 / float(wall_time),
              "model_name": "map_defun.benchmark.%d" % benchmark_id,
              "parameters": "%d" % num_iters,
          },
      )
  
file_path: tensorflow-upstream/tensorflow/python/data/experimental/benchmarks/map_defun_benchmark.py
imports: from tensorflow.python.data.benchmarks import benchmark_base
  from tensorflow.python.data.experimental.ops import map_defun
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 1 for calling the MapDefunBenchmark obj's underlying member method code with example usage: obj._run(op, name, num_iters, benchmark_id) without return types