code: def test_requires_coding_rank_bigger_than_prior_batch_rank(self):
      noisy = uniform_noise.NoisyLogistic(loc=0, scale=[[1], [2]])
      with self.assertRaises(ValueError):
          ContinuousBatchedEntropyModel(noisy, 0)
      with self.assertRaises(ValueError):
          ContinuousBatchedEntropyModel(noisy, 1)
      ContinuousBatchedEntropyModel(noisy, 2)
      ContinuousBatchedEntropyModel(noisy, 3)
  
imports: from absl.testing import parameterized
  import tensorflow
  import tensorflow_probability
  from tensorflow_compression.python.distributions import uniform_noise
  from tensorflow_compression.python.entropy_models.continuous_batched import ContinuousBatchedEntropyModel
label_desc: Use image node_id 4 for calling the ContinuousBatchedEntropyModelTest obj's underlying member method code with example usage: obj.test_requires_coding_rank_bigger_than_prior_batch_rank() without return types