code: def _testAll(self, np_inputs, paddings, constant_values):
      for mode in (
          "CONSTANT",
          "REFLECT",
          "SYMMETRIC",
          "reflect",
          "symmetric",
          "constant",
      ):
          # Zero-sized input is not allowed for REFLECT mode, but we still want
          # zero-sized input test cases for the other modes.
          if not np_inputs.size and mode.upper() == "REFLECT":
              continue
          # Empty tensor is not allowed for MirrorPad.
          if 0 in np_inputs.shape and mode.upper() in [
              "REFLECT",
              "SYMMETRIC",
          ]:
              continue
          self._testPad(
              np_inputs,
              paddings,
              mode=mode,
              constant_values=constant_values,
          )
          if np_inputs.dtype in [
              np.float32,
              np.float16,
              dtypes.bfloat16.as_numpy_dtype,
          ]:
              self._testGradient(
                  np_inputs,
                  paddings,
                  mode=mode,
                  constant_values=constant_values,
              )
  
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 6 for calling the PadOpTest obj's underlying member method code with example usage: obj._testAll(np_inputs, paddings, constant_values) without return types