code: def test_works_with_dynamic_num_steps(self):
      x = tf.Variable([5.0, 3.0])
      num_steps_ = 23
      num_steps = tf1.placeholder_with_default(num_steps_, shape=[])
  
      losses = minimize(
          loss_fn=lambda: (x - 2.0) ** 2,
          num_steps=num_steps,
          optimizer=_get_adam_optimizer(0.1),
      )
      with tf.control_dependencies([losses]):
          final_x = tf.identity(x)
      self.evaluate(tf1.global_variables_initializer())
      final_x_, losses_ = self.evaluate((final_x, losses))
      self.assertAllEqual(final_x_.shape, [2])
      self.assertAllEqual(losses_.shape, [num_steps_, 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 6 for calling the MinimizeTests obj's underlying member method code with example usage: obj.test_works_with_dynamic_num_steps() without return types