code: def testGradientTensor2D(self):
      for data_format, use_gpu in ("NHWC", False), ("NHWC", True):
          for dtype in (
              dtypes.float16,
              dtypes.float32,
              dtypes.float64,
              dtypes.bfloat16,
          ):
              np_input = np.array(
                  [1.0, 2.0, 3.0, 4.0, 5.0, 6.0],
                  dtype=dtype.as_numpy_dtype,
              ).reshape(3, 2)
              bias = np.array([1.3, 2.4], dtype=dtype.as_numpy_dtype)
              self._testGradient(
                  np_input, bias, dtype, 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 20 for calling the BiasAddTestBase obj's underlying member method code with example usage: obj.testGradientTensor2D() without return types