code: def get_pruned_index(self, mask):
      pruned_indexes = []
      shape = mask.size()
      for i in range(shape[0]):
          if torch.sum(mask[i]).item() == 0:
              pruned_indexes.append(i)
  
      return pruned_indexes
  
file_path: auptimizer/tests/compression/test_compression_utils.py
imports: import os
  import unittest
  from unittest import TestCase, main
  import torch
  import torch.nn
  import torchvision.models
  import numpy
  from aup.compression.torch import L1FilterPruner
  from aup.compression.torch.utils.shape_dependency import ChannelDependency
  from aup.compression.torch.utils.mask_conflict import fix_mask_conflict
  from aup.compression.torch.utils.counter import count_flops_params
label_desc: Use image node_id 2 for calling the AnalysisUtilsTest obj's underlying member method code with example usage: obj.get_pruned_index(mask) and returns: pruned_indexes