code: def test_jit_compiled_optimization_makes_progress(self):
      x = tf.Variable([5.0, 3.0])
      losses = minimize(
          loss_fn=lambda: tf.reduce_sum((x - 2.0) ** 2),
          num_steps=10,
          optimizer=_get_adam_optimizer(0.1),
          jit_compile=True,
      )
      self.evaluate(tf1.global_variables_initializer())
      losses_ = self.evaluate(losses)
      # Final loss should be lower than initial loss.
      self.assertAllGreater(losses_[0], losses_[-1])
  
imports: import collections
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python import optimizer
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.math.minimize import minimize
  from tensorflow_probability.python.math.minimize import minimize_stateless
label_desc: Use image node_id 11 for calling the MinimizeTests obj's underlying member method code with example usage: obj.test_jit_compiled_optimization_makes_progress() without return types