code: def get_calibration_cls(
      feature: str, calibration_method: str
  ) -> Type["CalibrationModule"]:
      """Get calibration class for specified feature type and calibration method."""
      if not calibration_method:
          return None
      if feature in calibration_registry:
          if calibration_method in calibration_registry[feature]:
              return calibration_registry[feature][calibration_method]
          else:
              raise ValueError(
                  f"Calibration method {calibration_method} not supported for {feature} output features"
              )
      else:
          raise ValueError(
              f"Calibration not yet supported for {feature} output features"
          )
      return None
  
imports: import logging
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import List, Type, Union
  import numpy
  import torch
  import torch.nn
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import BINARY, CATEGORY
  from ludwig.utils.registry import DEFAULT_KEYS, Registry
label_desc: Use image node_id 2 for calling a global function with example usage: get_calibration_cls(feature, calibration_method) and returns: None, None, calibration_registry