code: def __init__(self, artifact_uri):
      super().__init__(artifact_uri)
      # Use an isolated thread pool executor for chunk uploads/downloads to avoid a deadlock
      # caused by waiting for a chunk-upload/download task within a file-upload/download task.
      # See https://superfastpython.com/threadpoolexecutor-deadlock/#Deadlock_1_Submit_and_Wait_for_a_Task_Within_a_Task
      # for more details
      self.chunk_thread_pool = self._create_thread_pool()
  
imports: import logging
  import math
  import os
  import posixpath
  from abc import abstractmethod
  from collections import namedtuple
  from concurrent.futures import as_completed
  from mlflow.environment_variables import MLFLOW_ENABLE_ARTIFACTS_PROGRESS_BAR, MLFLOW_ENABLE_MULTIPART_DOWNLOAD, MLFLOW_MULTIPART_DOWNLOAD_CHUNK_SIZE, MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE, MLFLOW_MULTIPART_UPLOAD_MINIMUM_FILE_SIZE
  from mlflow.exceptions import MlflowException
  from mlflow.store.artifact.artifact_repo import ArtifactRepository
  from mlflow.utils import chunk_list
  from mlflow.utils.file_utils import ArtifactProgressBar, download_chunk_retries, parallelized_download_file_using_http_uri, relative_path_to_artifact_path, remove_on_error
  from mlflow.utils.uri import is_fuse_or_uc_volumes_uri
label_desc: Use image node_id 1 to create a new CloudArtifactRepository object from inherited base classes: ArtifactRepository with example: obj = CloudArtifactRepository(artifact_uri)