class_docstr: Abstract class for Backend Storage.
  This class defines the API interface for front ends to connect with various types of backends.
docstr: Log multiple metrics, params, and tags for the specified run in async fashion.
  This API does not offer immediate consistency of the data. When API returns,
  data is accepted but not persisted/processed by back end. Data would be processed
  in near real time fashion.
  
  :param run_id: String id for the run
  :param metrics: List of :py:class:`mlflow.entities.Metric` instances to log
  :param params: List of :py:class:`mlflow.entities.Param` instances to log
  :param tags: List of :py:class:`mlflow.entities.RunTag` instances to log
  
  :return: an :py:class:`mlflow.utils.async_logging.run_operations.RunOperations` instance
      that represents future for logging operation.
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code: def log_batch_async(
      self, run_id, metrics, params, tags
  ) -> RunOperations:
      """
      Log multiple metrics, params, and tags for the specified run in async fashion.
      This API does not offer immediate consistency of the data. When API returns,
      data is accepted but not persisted/processed by back end. Data would be processed
      in near real time fashion.
  
      :param run_id: String id for the run
      :param metrics: List of :py:class:`mlflow.entities.Metric` instances to log
      :param params: List of :py:class:`mlflow.entities.Param` instances to log
      :param tags: List of :py:class:`mlflow.entities.RunTag` instances to log
  
      :return: an :py:class:`mlflow.utils.async_logging.run_operations.RunOperations` instance
          that represents future for logging operation.
      """
      if not self._async_logging_queue.is_active():
          self._async_logging_queue.activate()
  
      return self._async_logging_queue.log_batch_async(
          run_id=run_id, metrics=metrics, params=params, tags=tags
      )
  
imports: from abc import ABCMeta, abstractmethod
  from typing import List, Optional
  from mlflow.entities import DatasetInput, ViewType
  from mlflow.store.entities.paged_list import PagedList
  from mlflow.store.tracking import SEARCH_MAX_RESULTS_DEFAULT
  from mlflow.utils.annotations import developer_stable, experimental
  from mlflow.utils.async_logging.async_logging_queue import AsyncLoggingQueue
  from mlflow.utils.async_logging.run_operations import RunOperations
label_desc: Use image node_id 25 for calling the AbstractStore obj's underlying member method code with example usage: obj.log_batch_async(run_id, metrics, params, tags) and returns: self