code: def huberLoss(label, output):
      if abs(label - output) > 1:
          return abs(label - output) - 0.5
      else:
          return 0.5 * (label - output) * (label - output)
  
file_path: ReAgent/reagent/evaluation/evaluator.py
imports: import logging
  from collections import Counter
  from typing import Dict, List, Optional
  import torch
  import torch.nn.functional
  from reagent.core.tracker import observable
  from reagent.evaluation.cpe import CpeDetails, CpeEstimateSet
  from reagent.evaluation.doubly_robust_estimator import DoublyRobustEstimator
  from reagent.evaluation.evaluation_data_page import EvaluationDataPage
  from reagent.evaluation.sequential_doubly_robust_estimator import SequentialDoublyRobustEstimator
  from reagent.evaluation.weighted_sequential_doubly_robust_estimator import WeightedSequentialDoublyRobustEstimator
label_desc: Use image node_id 6 for calling the Evaluator obj's underlying member method code with example usage: obj.huberLoss(label, output) and returns: unknown, unknown