code: def test_shared_parameters_between_layers(self):
      weight = tf.Variable(
          np.random.random((10, 10)), name="weight", dtype=tf.float32
      )
  
      inp = layers.Input(10)
      hid1 = layers.Relu(10, weight=weight)
      hid2 = layers.Relu(10, weight=weight)
  
      network = inp >> hid1 >> hid2
      self.assertIs(hid1.weight, hid2.weight)
  
      # Check that it is able to train network without errors
      x_train = y_train = asfloat(np.random.random((15, 10)))
      gdnet = algorithms.GradientDescent(network)
      gdnet.train(x_train, y_train, epochs=5)
  
      np.testing.assert_array_almost_equal(
          self.eval(hid1.weight),
          self.eval(hid2.weight),
      )
  
imports: import copy
  import numpy
  import tensorflow
  from neupy import layers, algorithms, init
  from neupy.utils import asfloat
  from neupy.exceptions import LayerConnectionError
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling the LayersBasicsTestCase obj's underlying member method code with example usage: obj.test_shared_parameters_between_layers() without return types