code: def test_read_flo(tmpdir):
      path = tmpdir / "test.flo"
      make_fake_flo_file(3, 4, path)
  
      with open(path, "rb") as file:
          actual = read_flo(file)
  
      expected = torch.from_numpy(
          read_flo_ref(path).astype("f4", copy=False)
      )
  
      torch.testing.assert_close(actual, expected)
  
imports: import gzip
  import pathlib
  import sys
  import numpy
  import pytest
  import torch
  from datasets_utils import make_fake_flo_file, make_tar
  from torchdata.datapipes.iter import FileOpener, TarArchiveLoader
  from torchvision.datasets._optical_flow import _read_flo
  from torchvision.datasets.utils import _decompress
  from torchvision.prototype.datasets.utils import Dataset, GDriveResource, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import fromfile, read_flo
label_desc: Use image node_id 2 for calling a global function with example usage: test_read_flo(tmpdir) without return types