code: def test_learning_rate_tag_order(self):
      num_tables = 30
      strategy = self._get_strategy()
  
      feature_configs = []
      for i in range(num_tables):
          optimizer = tpu_embedding_v2_utils.Adagrad(
              learning_rate=lambda: constant_op.constant(1.0)
          )
  
      feature_configs.append(
          tpu_embedding_v2_utils.FeatureConfig(
              table=tpu_embedding_v2_utils.TableConfig(
                  vocabulary_size=100,
                  dim=128,
                  initializer=init_ops_v2.Zeros(),
                  optimizer=optimizer,
              )
          )
      )
      with strategy.scope():
          mid_level_api = tpu_embedding_v2.TPUEmbedding(
              feature_config=feature_configs, optimizer=optimizer
          )
      mid_level_api._output_shapes = [TensorShape(128)] * len(
          feature_configs
      )
      result = mid_level_api._create_config_proto()
      for i, table in enumerate(result.table_descriptor):
          self.assertEqual(
              i, table.optimization_parameters.learning_rate.dynamic.tag
          )
  
file_path: tensorflow-upstream/tensorflow/python/tpu/tests/tpu_embedding_v2_initialization_test.py
imports: import numpy
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework.tensor_shape import TensorShape
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu_embedding_v2
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.tpu.tests import tpu_embedding_base_test
label_desc: Use image node_id 4 for calling the TPUEmbeddingTest obj's underlying member method code with example usage: obj.test_learning_rate_tag_order() without return types