code: def test_median_filter_equivalence(shape):
      x = torch.randn(*shape)
  
      for filter_width in [3, 5, 7, 13]:
          filtered_cpu = median_filter(x, filter_width)
          filtered_gpu = median_filter(x.cuda(), filter_width).cpu()
  
          assert np.allclose(filtered_cpu, filtered_gpu)
  
file_path: whisper/tests/test_timing.py
imports: import numpy
  import pytest
  import scipy.ndimage
  import torch
  from whisper.timing import dtw_cpu, dtw_cuda, median_filter
label_desc: Use image node_id 4 for calling a global function with example usage: test_median_filter_equivalence(shape) without return types