code: def test_function_with_updates(self):
      x = tf.placeholder(name="x", dtype=tf.float32)
      w = tf.Variable(asfloat(np.ones((4, 3))), name="w")
      b = tf.Variable(asfloat(np.ones((3,))), name="b")
      y = tf.matmul(x, w) + b
  
      prediction = tf_utils.function(
          [x],
          y,
          updates=[
              (b, b - 0.5),
              w.assign(w + 0.5),
          ],
      )
      tf_utils.initialize_uninitialized_variables()
  
      actual = prediction(np.random.random((7, 4)))
      self.assertEqual(actual.shape, (7, 3))
  
      np.testing.assert_array_almost_equal(
          self.eval(w),
          1.5 * np.ones((4, 3)),
      )
      np.testing.assert_array_almost_equal(
          self.eval(b),
          0.5 * np.ones((3,)),
      )
  
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow.errors import FailedPreconditionError
  from neupy import init
  from neupy.utils import tf_utils, asfloat
  from base import BaseTestCase
label_desc: Use image node_id 9 for calling the TFUtilsTestCase obj's underlying member method code with example usage: obj.test_function_with_updates() without return types