code: def test_minimize_mean_square_loss_with_weight_decay():
      w = tf.Variable([0.1, -0.2, -0.1])
      x = tf.constant([0.4, 0.2, -0.5])
  
      def loss():
          return tf.reduce_mean(tf.square(x - w))
  
      opt = lamb.LAMB(0.02, weight_decay=0.01)
  
      # Run 200 steps
      for _ in range(200):
          opt.minimize(loss, [w])
      # Validate updated params
      np.testing.assert_allclose(
          w.numpy(),
          np.asanyarray([0.4, 0.2, -0.5]),
          rtol=1e-2,
          atol=1e-2,
      )
  
imports: import numpy
  from numpy import linalg
  import pytest
  import tensorflow
  from tensorflow_addons.optimizers import lamb
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 9 for calling a global function with example usage: test_minimize_mean_square_loss_with_weight_decay() and returns: tf