code: def testForwardAndBackward(self, sparse_labels, logits_time_major):
      with test_util.deterministic_ops():
          for seed in range(2):
              loss_a, gradient_a = self._forwardAndBackward(
                  sparse_labels, logits_time_major, seed
              )
              loss_b, gradient_b = self._forwardAndBackward(
                  sparse_labels, logits_time_major, seed
              )
              loss_a, loss_b, gradient_a, gradient_b = self.evaluate(
                  (loss_a, loss_b, gradient_a, gradient_b)
              )
              self.assertAllEqual(loss_a, loss_b, "Loss mismatch")
              # self.assertAllEqual(gradient_a, gradient_b, "Gradient mismatch")
              self.assertAllClose(gradient_a, gradient_b, atol=5e-05)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import ctc_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the CTCLossDeterministicTest obj's underlying member method code with example usage: obj.testForwardAndBackward(sparse_labels, logits_time_major) without return types