code: def test_gradient(self, shape, frame_hop):
      # TODO(rjryan): Eager gradient tests.
      if context.executing_eagerly():
          return
      signal = array_ops.zeros(shape)
      reconstruction = reconstruction_ops.overlap_and_add(
          signal, frame_hop
      )
      loss = math_ops.reduce_sum(reconstruction)
      # Increasing any sample in the input frames by one will increase the sum
      # of all the samples in the reconstruction by 1, so the gradient should
      # be all ones, no matter the shape or hop.
      gradient = self.evaluate(
          gradients_impl.gradients([loss], [signal])[0]
      )
      self.assertTrue((gradient == 1.0).all())
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.signal import reconstruction_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the ReconstructionOpsTest obj's underlying member method code with example usage: obj.test_gradient(shape, frame_hop) without return types