code: def test(self):
      def gelu(x, approximate=False):
          if approximate:
              return (
                  0.5
                  * x
                  * (
                      1.0
                      + np.tanh(
                          np.sqrt(2.0 / np.pi)
                          * (x + 0.044715 * np.power(x, 3))
                      )
                  )
              )
          else:
              from scipy.stats import (
                  norm,
              )  # pylint: disable=g-import-not-at-top
  
              return x * norm.cdf(x)
  
      np.random.seed(1)  # Make it reproducible.
      x = np.random.randn(3, 4).astype(np.float32)
      x_wt = weak_tensor.WeakTensor(x)
      y = gelu(x)
      y_wt = nn_ops.gelu(x_wt)
      z = self.evaluate(y_wt)
      self.assertIsInstance(y_wt, weak_tensor.WeakTensor)
      self.assertAllClose(y, z)
  
      y = gelu(x, True)
      y_wt = nn_ops.gelu(x_wt, True)
      z = self.evaluate(y_wt)
      self.assertIsInstance(y_wt, weak_tensor.WeakTensor)
      self.assertAllClose(y, z)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.framework import weak_tensor
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import weak_tensor_ops
  from tensorflow.python.ops import weak_tensor_test_util
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the GeluTest obj's underlying member method code with example usage: obj.test() and returns: unknown, unknown