code: def _preprocess_data(self, data, mask):
      from .._ops import _sparse_coo_where, _sparse_csr_where
  
      if data.layout != mask.layout:
          raise TypeError("data and mask must have the same layout.")
      if data.layout == torch.sparse_coo:
          data = data.coalesce()
          mask = mask.coalesce()
          if data._nnz() != mask._nnz():
              data = _sparse_coo_where(mask, data, torch.tensor(0))
      elif data.layout == torch.sparse_csr:
          if data._nnz() != mask._nnz():
              data = _sparse_csr_where(mask, data, torch.tensor(0))
  
      # Have to pick awkward names to not conflict with existing fields such as data
      self._masked_data = data.clone()
      self._masked_mask = mask.clone()
  
imports: import warnings
  import torch
  from torch.overrides import get_default_nowrap_functions
label_desc: Use image node_id 2 for calling the MaskedTensor obj's underlying member method code with example usage: obj._preprocess_data(data, mask) without return types