code: def tfsplits(_):
      """A more complex graph, including splits."""
      x = array_ops.placeholder(dtypes.float32, shape=[2, 2], name="x")
      y = array_ops.placeholder(dtypes.float32, shape=[2, 2], name="y")
      for _ in range(3):
          x0, x1 = array_ops.split(x, 2, 0)
          y0, y1 = array_ops.split(y, 2, 0)
          x0 += 1
          y0 += 1
          z = math_ops.matmul(x, y, name="x_y_prod")
          a = array_ops.concat([x0, y1], axis=0, name="concat_x0_y1")
          b = array_ops.concat([y0, x1], axis=0, name="concat_y0_x1")
          x = math_ops.matmul(a, b, name="a_b")
          y = math_ops.add(x, z)
      array_ops.identity(y, name="result")
  
imports: import argparse
  import os
  import sys
  from absl import app
  import six
  from six.moves import range
  from tensorflow.core.protobuf import saver_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.training import saver
label_desc: Use image node_id 10 for calling a global function with example usage: tfsplits(_) without return types