code: def _conv_and_pool_0(self, inp):
      dtype = inp.dtype
      conv_filter = constant_op.constant(
          [[[[1.0, 0.5, 4.0], [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], 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)
  
imports: import itertools
  import os
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.core.protobuf import saved_model_pb2
  from tensorflow.python.compiler.tensorrt import trt_convert
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base
  from tensorflow.python.compiler.tensorrt.test.tf_trt_integration_test_base import GraphState
  from tensorflow.python.compiler.tensorrt.test.tf_trt_integration_test_base import IsQuantizationWithCalibration
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import constants
  from tensorflow.python.saved_model import loader_impl
  from tensorflow.python.util import compat
label_desc: Use image node_id 6 for calling the TfFunctionTest obj's underlying member method code with example usage: obj._conv_and_pool_0(inp) and returns: array_ops