code: def read_file(folder: str, prefix: str, name: str) -> Tensor:
      path = osp.join(folder, f"ind.{prefix.lower()}.{name}")
  
      if name == "test.index":
          return read_txt_array(path, dtype=torch.long)
  
      with fsspec.open(path, "rb") as f:
          warnings.filterwarnings(
              "ignore", ".*`scipy.sparse.csr` name.*"
          )
          out = pickle.load(f, encoding="latin1")
  
      if name == "graph":
          return out
  
      out = out.todense() if hasattr(out, "todense") else out
      out = torch.from_numpy(out).to(torch.float)
      return out
  
file_path: pytorch_geometric/torch_geometric/io/planetoid.py
imports: import os.path
  import warnings
  from itertools import repeat
  from typing import Dict, List, Optional
  import fsspec
  import torch
  from torch import Tensor
  from torch_geometric.data import Data
  from torch_geometric.io import read_txt_array
  from torch_geometric.utils import coalesce, index_to_mask, remove_self_loops, to_torch_csr_tensor
label_desc: Use image node_id 2 for calling a global function with example usage: read_file(folder, prefix, name) and returns: out, read_txt_array, out