code: def get_mlflow_run_params_for_fn_args(
      fn, args, kwargs, unlogged=None
  ):
      """Given arguments explicitly passed to a function, generate a dictionary of MLflow Run
      parameter key / value pairs.
  
      Args:
          fn: function whose parameters are to be logged.
          args: arguments explicitly passed into fn. If `fn` is defined on a class,
              `self` should not be part of `args`; the caller is responsible for
              filtering out `self` before calling this function.
          kwargs: kwargs explicitly passed into fn.
          unlogged: parameters not to be logged.
  
      Returns:
          A dictionary of MLflow Run parameter key / value pairs.
      """
      unlogged = unlogged or []
      param_spec = inspect.signature(fn).parameters
      # Filter out `self` from the signature under the assumption that it is not contained
      # within the specified `args`, as stipulated by the documentation
      relevant_params = [
          param for param in param_spec.values() if param.name != "self"
      ]
  
      # Fetch the parameter names for specified positional arguments from the function
      # signature & create a mapping from positional argument name to specified value
      params_to_log = {
          param_info.name: param_val
          for param_info, param_val in zip(
              list(relevant_params)[: len(args)], args
          )
      }
      # Add all user-specified keyword arguments to the set of parameters to log
      params_to_log.update(kwargs)
      # Add parameters that were not explicitly specified by the caller to the mapping,
      # using their default values
      params_to_log.update(
          {
              param.name: param.default
              for param in list(relevant_params)[len(args) :]
              if param.name not in kwargs
          }
      )
      # Filter out any parameters that should not be logged, as specified by the `unlogged` parameter
      return {
          key: value
          for key, value in params_to_log.items()
          if key not in unlogged
      }
  
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 1 for calling a global function with example usage: get_mlflow_run_params_for_fn_args(fn, args, kwargs, unlogged) and returns: unknown