code: def build_graph(device, input_shape, output_sizes, axis):
      """Build a graph containing a sequence of split operations.
  
      Args:
        device: string, the device to run on.
        input_shape: shape of the input tensor.
        output_sizes: size of each output along axis.
        axis: axis to be split along.
  
      Returns:
        An array of tensors to run()
      """
      with ops.device("/%s:0" % device):
          inp = array_ops.zeros(input_shape)
  
          outputs = []
          for _ in range(100):
              outputs.extend(array_ops.split(inp, output_sizes, axis))
          return control_flow_ops.group(*outputs)
  
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 1 for calling a global function with example usage: build_graph(device, input_shape, output_sizes, axis) and returns: control_flow_ops