code: def test_left_right_3d(self):
      x1_actual = [[[3.0, 4.0]]]
      y1_expected = [
          [
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
          ]
      ]
      x2_actual = [[[1.0, 2.0], [3.0, 4.0]]]
      y2_expected = [
          [
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
              [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
          ]
      ]
  
      b = pad.Pad(paddings=[[1, 2], [3, 4]], validate_args=True)
      y1 = b.forward(x1_actual)
      y2 = b.forward(x2_actual)
      x1 = b.inverse(y1_expected)
      x2 = b.inverse(y2_expected)
      fldj = b.forward_log_det_jacobian([[43.0]], event_ndims=2)
      ildj = b.inverse_log_det_jacobian([[45.0, 0.0]], event_ndims=2)
      [y1_, y2_, x1_, x2_, fldj_, ildj_] = self.evaluate(
          [y1, y2, x1, x2, fldj, ildj]
      )
  
      self.assertAllEqual(y1_expected, y1_)
      self.assertAllEqual(y2_expected, y2_)
      self.assertAllEqual(x1_actual, x1_)
      self.assertAllEqual(x2_actual, x2_)
      self.assertEqual(0.0, fldj_)
      self.assertEqual(0.0, ildj_)
  
file_path: probability/tensorflow_probability/python/bijectors/pad_test.py
imports: import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import pad
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling the PadBijectorTest obj's underlying member method code with example usage: obj.test_left_right_3d() without return types