code: def disable_discrete_autologging(
      flavors_to_disable: List[str],
  ) -> None:
      """
      Context manager for disabling specific autologging integrations temporarily while another
      flavor's autologging is activated. This context wrapper is useful in the event that, for
      example, a particular library calls upon another library within a training API that has a
      current MLflow autologging integration.
      For instance, the transformers library's Trainer class, when running metric scoring,
      builds a sklearn model and runs evaluations as part of its accuracy scoring. Without this
      temporary autologging disabling, a new run will be generated that contains a sklearn model
      that holds no use for tracking purposes as it is only used during the metric evaluation phase
      of training.
  
      Args:
          flavors_to_disable: A list of flavors that need to be temporarily disabled while
              executing another flavor's autologging to prevent spurious run
              logging of unrelated models, metrics, and parameters.
      """
      enabled_flavors = []
      for flavor in flavors_to_disable:
          if not autologging_is_disabled(flavor):
              enabled_flavors.append(flavor)
              autolog_func = getattr(mlflow, flavor)
              autolog_func.autolog(disable=True)
      yield
      for flavor in enabled_flavors:
          autolog_func = getattr(mlflow, flavor)
          autolog_func.autolog(disable=False)
  
imports: import contextlib
  import inspect
  import logging
  import time
  from typing import List
  import mlflow
  from mlflow.entities import Metric
  from mlflow.tracking.client import MlflowClient
  from mlflow.utils.validation import MAX_METRICS_PER_BATCH
  from mlflow.utils.autologging_utils.client import MlflowAutologgingQueueingClient
  from mlflow.utils.autologging_utils.events import AutologgingEventLogger
  from mlflow.utils.autologging_utils.logging_and_warnings import set_mlflow_events_and_warnings_behavior_globally, set_non_mlflow_warnings_behavior_for_current_thread
  from mlflow.utils.autologging_utils.safety import ExceptionSafeAbstractClass, ExceptionSafeClass, PatchFunction, exception_safe_function_for_class, is_testing, picklable_exception_safe_function, revert_patches, safe_patch, update_wrapper_extended, with_managed_run
  from mlflow.utils.autologging_utils.versioning import FLAVOR_TO_MODULE_NAME_AND_VERSION_INFO_KEY, get_min_max_version_and_pip_release, is_flavor_supported_for_associated_package_versions
label_desc: Use image node_id 11 for calling a global function with example usage: disable_discrete_autologging(flavors_to_disable) without return types