code: def testHigherRank(self):
      indices = [
          constant_op.constant(6),
          constant_op.constant([4, 1]),
          constant_op.constant([[5, 2], [0, 3]]),
      ]
      data = [
          constant_op.constant([61, 62], dtype=dtypes.float32),
          constant_op.constant(
              [[41, 42], [11, 12]], dtype=dtypes.float32
          ),
          constant_op.constant(
              [[[51, 52], [21, 22]], [[1, 2], [31, 32]]],
              dtype=dtypes.float32,
          ),
      ]
      stitched_t = data_flow_ops.dynamic_stitch(indices, data)
      stitched_val = self.evaluate(stitched_t)
      correct = 10 * np.arange(7)[:, None] + [1.0, 2.0]
      self.assertAllEqual(correct, stitched_val)
      self.assertEqual([7, 2], stitched_t.get_shape().as_list())
      # Test gradients
      stitched_grad = 7 * stitched_val
      grads = gradients_impl.gradients(
          stitched_t, indices + data, stitched_grad
      )
      self.assertEqual(
          grads[:3], [None] * 3
      )  # Indices have no gradients
      for datum, grad in zip(data, self.evaluate(grads[3:])):
          self.assertAllEqual(7.0 * self.evaluate(datum), grad)
  
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 test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import gradients_impl
  import tensorflow.python.ops.data_flow_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the ParallelDynamicStitchTest obj's underlying member method code with example usage: obj.testHigherRank() without return types