class_docstr: Abstract class that defines API interfaces for storing Model Registry metadata.
class_docstr_tok: ["Abstract","class","that","defines","API","interfaces","for","storing","Model","Registry","metadata","."]
docstr: Empty constructor. This is deliberately not marked as abstract, else every derived class
  would be forced to create one.
  
  :param store_uri: The model registry store URI
  :param tracking_uri: URI of the current MLflow tracking server, used to perform operations
                       like fetching source run metadata or downloading source run artifacts
                       to support subsequently uploading them to the model registry storage
                       location
docstr_tok: ["Empty","constructor",".","This","is","deliberately","not","marked","as","abstract",",","else","every","derived","class","would","be","forced","to","create","one",".",":","param","store_uri",":","The","model","registry","store","URI",":","param","tracking_uri",":","URI","of","the","current","MLflow","tracking","server",",","used","to","perform","operations","like","fetching","source","run","metadata","or","downloading","source","run","artifacts","to","support","subsequently","uploading","them","to","the","model","registry","storage","location"]
code: def __init__(self, store_uri=None, tracking_uri=None):
      """
      Empty constructor. This is deliberately not marked as abstract, else every derived class
      would be forced to create one.
  
      :param store_uri: The model registry store URI
      :param tracking_uri: URI of the current MLflow tracking server, used to perform operations
                           like fetching source run metadata or downloading source run artifacts
                           to support subsequently uploading them to the model registry storage
                           location
      """
      pass
  
imports: import logging
  from abc import ABCMeta, abstractmethod
  from time import sleep, time
  from mlflow.entities.model_registry import ModelVersionTag
  from mlflow.entities.model_registry.model_version_status import ModelVersionStatus
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import RESOURCE_ALREADY_EXISTS, ErrorCode
  from mlflow.utils.annotations import developer_stable
label_desc: Use image node_id 1 to create a new AbstractStore object  with example: obj = AbstractStore(store_uri, tracking_uri)