class_docstr: Benchmark split!
class_docstr_tok: ["Benchmark","split","!"]
code: def benchmark_split(self):
      print("Forward vs backward concat")
      shapes = [
          [2000, 8],
          [8, 2000],
          [100, 18],
          [1000, 18],
          [10000, 18],
          [100, 97],
          [1000, 97],
          [10000, 1],
          [1, 10000],
      ]
      axis_ = [
          1
      ]  # 0 is very fast because it doesn't actually do any copying
      num_outputs = 100
      variable = [False, True]  # fixed input size or not
      for shape in shapes:
          for axis in axis_:
              for v in variable:
                  self._run_graph("gpu", shape, v, num_outputs, axis)
  
file_path: tensorflow/tensorflow/python/ops/split_benchmark.py
imports: import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 2 for calling the SplitBenchmark obj's underlying member method code with example usage: obj.benchmark_split() without return types