code: def test1x1Image(self):
      for data_format, use_gpu in [("NHWC", False), ("NCHW", False)]:
          np_input = (
              np.arange(1.0, 129.0)
              .reshape([4, 1, 1, 32])
              .astype(np.float32)
          )
          self._testGradient(
              np_input,
              np.random.rand(32).astype(np.float32),
              dtypes.float32,
              data_format,
              use_gpu,
          )
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 24 for calling the BiasAddTestBase obj's underlying member method code with example usage: obj.test1x1Image() without return types