code: def testPaddingTypes(self):
      paddings = [[1, 0], [2, 0]]
      inputs = np.random.rand(2, 5).astype(np.float32)
      for mode in (
          "CONSTANT",
          "REFLECT",
          "SYMMETRIC",
          "reflect",
          "symmetric",
          "constant",
      ):
          for paddings_dtype in [dtypes.int32, dtypes.int64]:
              np_val = self._npPad(
                  inputs, paddings, mode=mode, constant_values=0
              )
  
              with test_util.use_gpu():
                  tf_val = array_ops.pad(
                      inputs,
                      constant_op.constant(paddings, paddings_dtype),
                      mode=mode,
                      constant_values=0,
                  )
                  out = self.evaluate(tf_val)
  
              self.assertAllEqual(np_val, out)
              self.assertShapeEqual(np_val, tf_val)
  
              if mode.upper() != "REFLECT":
                  with ops.Graph().as_default():
                      self._testGradient(
                          inputs,
                          paddings,
                          mode=mode,
                          constant_values=0,
                          paddings_dtype=paddings_dtype,
                      )
  
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 16 for calling the PadOpTest obj's underlying member method code with example usage: obj.testPaddingTypes() without return types