code: def test_clip_gradient(self):
      session = tensorflow_session()
  
      x = tf.Variable(asfloat(1), dtype=tf.float32)
      x_clipped = clip_gradient(x, 1.5)
      y = x_clipped**2
      (gradient,) = tf.gradients(y, x)
      self.assertAlmostEqual(self.eval(gradient), 1.5)
  
      x.load(asfloat(0.1), session)
      self.assertAlmostEqual(self.eval(gradient), 0.2)
  
      x.load(asfloat(-0.1), session)
      self.assertAlmostEqual(self.eval(gradient), -0.2)
  
      x.load(asfloat(-2), session)
      self.assertAlmostEqual(self.eval(gradient), -1.5)
  
imports: import numpy
  import tensorflow
  from sklearn.model_selection import train_test_split
  from neupy.datasets import reber
  from neupy.utils import asfloat, tensorflow_session
  from neupy.exceptions import LayerConnectionError
  from neupy.layers.recurrent import clip_gradient
  from neupy import layers, algorithms, init
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling the GradientClippingTestCase obj's underlying member method code with example usage: obj.test_clip_gradient() without return types