code: def _testGradient(
      self, x, a, mode, constant_values, paddings_dtype=dtypes.int32
  ):
      def pad(x):
          return array_ops.pad(
              x,
              ops.convert_to_tensor(a, paddings_dtype),
              mode=mode,
              constant_values=constant_values,
          )
  
      with self.cached_session():
          jacob_t, jacob_n = gradient_checker_v2.compute_gradient(
              pad, [x]
          )
          if x.dtype == dtypes.bfloat16.as_numpy_dtype:
              # Compare bf16 analytical gradients to fp32 numerical gradients.
              x_fp32 = constant_op.constant(
                  x, shape=x.shape, dtype=dtypes.float32
              )
              _, jacob_n = gradient_checker_v2.compute_gradient(
                  pad, [x_fp32]
              )
          tol = 1e-3 if x.dtype == np.float16 else 4e-5
          self.assertAllClose(jacob_t, jacob_n, rtol=tol, atol=tol)
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the PadOpTest obj's underlying member method code with example usage: obj._testGradient(x, a, mode, constant_values, paddings_dtype) and returns: array_ops