code: def test_works_with_optax_optimizer(self):
      if not JAX_MODE:
          return
      import optax  # pylint: disable=g-import-not-at-top
  
      target_x = np.array([3.0, 4.0]).astype(np.float32)
      final_x, losses = self.evaluate(
          minimize_stateless(
              lambda x: tf.reduce_sum((x - target_x) ** 2),
              init=np.array([0.0, 0.0]).astype(np.float32),
              num_steps=100,
              optimizer=optax.adam(0.1),
          )
      )
      self.assertAllClose(final_x, target_x, atol=0.2)
      self.assertAllClose(losses[-1], 0.0, atol=0.2)
  
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 3 for calling the MinimizeStatelessTests obj's underlying member method code with example usage: obj.test_works_with_optax_optimizer() without return types