code: def build_dm_config_from_flags():
      """Builds a DynamicEmbeddingConfig from flags."""
      config = de_config_pb2.DynamicEmbeddingConfig()
      text_format.Parse(
          """
      memory_store_config {
          extension {
            [type.googleapis.com/carls.memory_store.GaussianMemoryConfig] {
              per_cluster_buffer_size: %d
              distance_to_cluster_threshold: %f
              max_num_clusters: %d
              bootstrap_steps: %d
              min_variance: %f
              distance_type: CWISE_MEAN_GAUSSIAN
            }
          }
        }
    """
          % (
              FLAGS.per_cluster_buffer_size,
              FLAGS.distance_to_cluster_threshold,
              FLAGS.max_num_clusters,
              FLAGS.bootstrap_steps,
              FLAGS.min_variance,
          ),
          config,
      )
      return config
  
file_path: neural-structured-learning/research/carls/examples/dynamic_normalization/image_dataset_eval_main.py
imports: import typing
  from absl import app
  from absl import flags
  from research.carls import dynamic_embedding_config_pb2
  from research.carls import dynamic_memory_ops
  from research.carls import dynamic_normalization
  from research.carls import kbs_server_helper_pybind
  import tensorflow
  import tensorflow_datasets
  from google.protobuf import text_format
label_desc: Use image node_id 2 for calling a global function with example usage: build_dm_config_from_flags() and returns: config