code: def testGradientsZeroInput(self):
      with self.session():
          shape = [4, 4, 4, 4]
          p = array_ops.placeholder(dtypes.float32, shape=shape)
          inp_array = np.zeros(shape).astype("f")
          lrn_op = nn.local_response_normalization(
              p, 2, 1.0, 0.0, 1.0, name="lrn"
          )
          grad = gradients_impl.gradients([lrn_op], [p])[0]
          params = {p: inp_array}
          r = grad.eval(feed_dict=params)
      expected = np.ones(shape).astype("f")
      self.assertAllClose(r, expected)
      self.assertShapeEqual(expected, grad)
  
imports: import copy
  import numpy
  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 test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import random_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the LRNOpTest obj's underlying member method code with example usage: obj.testGradientsZeroInput() without return types