docstr: Create a graph containing single segment.
docstr_tok: ["Create","a","graph","containing","single","segment","."]
code: def GraphFn(self, inp):
      """Create a graph containing single segment."""
      dtype = inp.dtype
      conv_filter = constant_op.constant(
          [
              [
                  [
                      [1.0, 0.5, 4.0, 6.0, 0.5, 1.0],
                      [1.0, 0.5, 1.0, 1.0, 0.5, 1.0],
                  ]
              ]
          ],
          name="weights",
          dtype=dtype,
      )
      conv = nn.conv2d(
          input=inp,
          filter=conv_filter,
          strides=[1, 2, 2, 1],
          padding="SAME",
          name="conv",
      )
      bias = constant_op.constant(
          [4.0, 1.5, 2.0, 3.0, 5.0, 7.0], name="bias", dtype=dtype
      )
      added = nn.bias_add(conv, bias, name="bias_add")
      relu = nn.relu(added, "relu")
      identity = array_ops.identity(relu, "identity")
      pool = nn_ops.max_pool(
          identity, [1, 2, 2, 1], [1, 2, 2, 1], "VALID", name="max_pool"
      )
      return array_ops.squeeze(pool, name="output_0")
  
imports: import numpy
  from tensorflow.python.compiler.tensorrt import utils
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the SimpleSingleEngineTest obj's underlying member method code with example usage: obj.GraphFn(inp) and returns: array_ops