code: def register_calibration(
      name: str, features: Union[str, List[str]], default=False
  ):
      """Registers a calibration implementation for a list of features."""
      if isinstance(features, str):
          features = [features]
  
      def wrap(cls):
          for feature in features:
              feature_registry = calibration_registry.get(feature, {})
              feature_registry[name] = cls
              if default:
                  for key in DEFAULT_KEYS:
                      feature_registry[key] = cls
              calibration_registry[feature] = feature_registry
          return cls
  
      return wrap
  
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 1 for calling a global function with example usage: register_calibration(name, features, default) and returns: wrap, cls