code: def _sparse_argmax_nnz_row(csr_mat):
      """Return index of the maximum non-zero index in each row."""
      n_rows = csr_mat.shape[0]
      idx = np.empty(n_rows, dtype=np.int64)
      for k in range(n_rows):
          row = csr_mat[k].tocoo()
          idx[k] = row.col[np.argmax(row.data)]
      return idx
  
imports: import copy
  import os.path
  import warnings
  import numpy
  from scipy import sparse
  from .fixes import _get_img_fdata
  from .morph_map import read_morph_map
  from .parallel import parallel_func
  from .source_estimate import _BaseSourceEstimate, _BaseSurfaceSourceEstimate, _BaseVolSourceEstimate, _get_ico_tris
  from .source_space._source_space import SourceSpaces, _ensure_src, _grid_interp
  from .surface import _compute_nearest, mesh_edges, read_surface
  from .utils import BunchConst, ProgressBar, _check_fname, _check_option, _custom_lru_cache, _ensure_int, _import_h5io_funcs, _import_nibabel, _validate_type, check_version, fill_doc, get_subjects_dir, logger, use_log_level, verbose, warn
  from .utils import warn
label_desc: Use image node_id 20 for calling a global function with example usage: _sparse_argmax_nnz_row(csr_mat) and returns: idx