code: def get_indices_sparse(data):
      """
      Is faster than np.argwhere. Used in loss functions like swav loss, etc
      """
      cols = np.arange(data.size)
      M = csr_matrix(
          (cols, (data.ravel(), cols)),
          shape=(data.max() + 1, data.size),
      )
      return [np.unravel_index(row.data, data.shape) for row in M]
  
imports: import collections
  import collections.abc
  import logging
  import os
  import random
  import sys
  import tempfile
  import time
  from functools import partial, wraps
  from typing import Tuple
  import numpy
  import pkg_resources
  import torch
  import torch.multiprocessing
  from iopath.common.file_io import g_pathmgr
  from scipy.sparse import csr_matrix
  from vissl.utils.extract_features_utils import ExtractedFeaturesLoader
label_desc: Use image node_id 11 for calling a global function with example usage: get_indices_sparse(data) and returns: unknown