code: def test_batch_of_optimizations(self):
      init_x = np.array([0.0, 0.0]).astype(np.float32)
      target_x = np.array([3.0, 4.0]).astype(np.float32)
      loss_fn = lambda x: (x - target_x) ** 2
      final_x, losses = self.evaluate(
          minimize_stateless(
              loss_fn,
              init=init_x,
              num_steps=100,
              optimizer=StatelessSGD(0.05),
          )
      )
      self.assertAllClose(final_x, target_x, atol=0.2)
      self.assertAllClose(losses[0], [9.0, 16.0], atol=0.5)
      self.assertAllClose(losses[-1], [0.0, 0.0], atol=0.1)
  
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 5 for calling the MinimizeStatelessTests obj's underlying member method code with example usage: obj.test_batch_of_optimizations() without return types