code: def _select_strategy_for_resolving_required_args(
      task: str,
  ) -> Callable:
      """Helper function that selects the strategy for resolving required arguments for each issue type.
  
      Each strategy resolves the required arguments for each issue type.
  
      This is a helper function that filters out any issue manager
      that does not have the required arguments.
  
      This does not consider custom hyperparameters for each issue type.
  
      Parameters
      ----------
      task : str
          The type of machine learning task that the dataset is used for.
  
      Returns
      -------
      args_dict :
          Dictionary of required arguments for each issue type, if available.
      """
      strategies = {
          "classification": _resolve_required_args_for_classification,
          "regression": _resolve_required_args_for_regression,
      }
      selected_strategy = strategies.get(task, None)
      if selected_strategy is None:
          raise ValueError(
              f"No strategy for resolving required arguments for task '{task}'"
          )
      return selected_strategy
  
file_path: cleanlab/cleanlab/datalab/internal/issue_finder.py
imports: from __future__ import annotations
  import warnings
  from typing import TYPE_CHECKING, Any, Dict, Optional
  import numpy
  from scipy.sparse import csr_matrix
  from cleanlab.datalab.internal.issue_manager_factory import _IssueManagerFactory, list_default_issue_types
  from cleanlab.datalab.internal.model_outputs import MultiClassPredProbs, RegressionPredictions
label_desc: Use image node_id 3 for calling a global function with example usage: _select_strategy_for_resolving_required_args(task) and returns: selected_strategy