code: def _RunAndVerify(self, dtype):
      with self.cached_session():
          # random shape
          shape = np.random.randint(1, 16, size=4)
          # Make depth at least 2 to make it meaningful
          shape[3] += 1
          p = array_ops.placeholder(dtype, shape=shape)
          # random depth_radius, bias, alpha, beta. cuDNN requires depth_radius to
          # be in [1, 7].
          lrn_depth_radius = np.random.randint(1, min(8, shape[3]))
  
          bias = 1.0 + np.random.rand()
          alpha = 2.0 * np.random.rand()
          # cuDNN requires beta >= 0.01.
          beta = 0.01 + 2.0 * np.random.rand()
          lrn_t = nn.local_response_normalization(
              p,
              name="lrn",
              depth_radius=lrn_depth_radius,
              bias=bias,
              alpha=alpha,
              beta=beta,
          )
          params = {p: np.random.rand(*shape).astype("f")}
          result = lrn_t.eval(feed_dict=params)
      expected = self._LRN(
          params[p],
          lrn_depth_radius=lrn_depth_radius,
          bias=bias,
          alpha=alpha,
          beta=beta,
      )
      err = np.amax(np.abs(result - expected))
      print(
          "LRN error for bias ",
          bias,
          "alpha ",
          alpha,
          " beta ",
          beta,
          " is ",
          err,
      )
      if dtype == dtypes.float32:
          self.assertTrue(err < 1e-4)
      else:
          self.assertTrue(err < 1e-2)
      self.assertShapeEqual(expected, lrn_t)
  
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 2 for calling the LRNOpTest obj's underlying member method code with example usage: obj._RunAndVerify(dtype) without return types