code: def create_class_indices_mapping(labels):
      unique_labels, inverse = torch.unique(labels, return_inverse=True)
      mapping = {
          unique_labels[i]: (inverse == i).nonzero()
          for i in range(len(unique_labels))
      }
      return mapping
  
imports: import argparse
  from functools import partial
  import json
  import logging
  import os
  import sys
  from typing import List, Optional
  import torch
  from torch.nn.functional import one_hot, softmax
  import dinov2.distributed
  from dinov2.data import SamplerType, make_data_loader, make_dataset
  from dinov2.data.transforms import make_classification_eval_transform
  from dinov2.eval.metrics import AccuracyAveraging, build_topk_accuracy_metric
  from dinov2.eval.setup import get_args_parser
  from dinov2.eval.setup import setup_and_build_model
  from dinov2.eval.utils import ModelWithNormalize, evaluate, extract_features
label_desc: Use image node_id 4 for calling a global function with example usage: create_class_indices_mapping(labels) and returns: mapping