class_docstr: Abstract class for Backend Storage.
  This class defines the API interface for front ends to connect with various types of backends.
docstr: Return a list of metric objects corresponding to all values logged for a given metric
  within a run.
  
  :param run_id: Unique identifier for run
  :param metric_key: Metric name within the run
  :param max_results: Maximum number of metric history events (steps) to return per paged
      query.
  :param page_token: A Token specifying the next paginated set of results of metric history.
      This value is obtained as a return value from a paginated call to GetMetricHistory.
  
  :return: A list of :py:class:`mlflow.entities.Metric` entities if logged, else empty list
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code: def get_metric_history(
      self, run_id, metric_key, max_results=None, page_token=None
  ):
      """
      Return a list of metric objects corresponding to all values logged for a given metric
      within a run.
  
      :param run_id: Unique identifier for run
      :param metric_key: Metric name within the run
      :param max_results: Maximum number of metric history events (steps) to return per paged
          query.
      :param page_token: A Token specifying the next paginated set of results of metric history.
          This value is obtained as a return value from a paginated call to GetMetricHistory.
  
      :return: A list of :py:class:`mlflow.entities.Metric` entities if logged, else empty list
      """
  
      # NB: Pagination for this API is not supported in FileStore or SQLAlchemyStore. The
      # argument `max_results` is used as a pagination activation flag. If the `max_results`
      # argument is not provided, this API will return a full metric history event collection
      # without the paged queries to the backend store.
      pass
  
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 21 for calling the AbstractStore obj's underlying member method code with example usage: obj.get_metric_history(run_id, metric_key, max_results, page_token) without return types