class_docstr: Implementation of the NeighborCacheClient with DynamicEmbedding.
docstr: Initializes the `NeighborCacheClient` object.
  
  Args:
    key_feature_name: feature name of the key in the input `tf.Example`
      instances whose value contains neighbor IDs.
    config: A DynamicEmbeddingConfig proto that configs the embedding.
    service_address: The address of a dynamic embedding service. If empty, the
      value passed from --kbs_address flag will be used instead.
    timeout_ms: Timeout millseconds for the connection. If negative, never
      timout.
code: def __init__(
      self,
      key_feature_name: typing.Text,
      config: de_config_pb2.DynamicEmbeddingConfig,
      service_address: typing.Text = "",
      timeout_ms: int = -1,
  ):
      """Initializes the `NeighborCacheClient` object.
  
      Args:
        key_feature_name: feature name of the key in the input `tf.Example`
          instances whose value contains neighbor IDs.
        config: A DynamicEmbeddingConfig proto that configs the embedding.
        service_address: The address of a dynamic embedding service. If empty, the
          value passed from --kbs_address flag will be used instead.
        timeout_ms: Timeout millseconds for the connection. If negative, never
          timout.
      """
      self._key_feature_name = key_feature_name
      self._config = config
      self._service_address = service_address
      self._timeout_ms = timeout_ms
  
file_path: neural-structured-learning/research/carls/dynamic_embedding_neighbor_cache.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import typing
  from research.carls import dynamic_embedding_config_pb2
  from research.carls import dynamic_embedding_ops
  from research.carls import neighbor_cache_client
label_desc: Use image node_id 1 to create a new DynamicEmbeddingNeighborCache object from inherited base classes: nb_cache with example: obj = DynamicEmbeddingNeighborCache(key_feature_name, config, service_address, timeout_ms)