code: def filter_adj(
      row: Tensor, col: Tensor, edge_attr: OptTensor, mask: Tensor
  ) -> Tuple[Tensor, Tensor, OptTensor]:
      return (
          row[mask],
          col[mask],
          None if edge_attr is None else edge_attr[mask],
      )
  
file_path: pytorch_geometric/torch_geometric/utils/dropout.py
imports: from typing import Optional, Tuple
  import torch
  from torch import Tensor
  import torch_geometric.typing
  from torch_geometric import is_compiling
  from torch_geometric.deprecation import deprecated
  from torch_geometric.typing import OptTensor
  from torch_geometric.utils import cumsum, degree, sort_edge_index, subgraph
  from torch_geometric.utils.num_nodes import maybe_num_nodes
label_desc: Use image node_id 1 for calling a global function with example usage: filter_adj(row, col, edge_attr, mask) and returns: row,  col,  unknown