code: def _test_get_strided_helper(
      self, num_samples, window_size, window_shift, snip_edges
  ):
      waveform = torch.arange(num_samples).float()
      output = kaldi._get_strided(
          waveform, window_size, window_shift, snip_edges
      )
  
      # from NumFrames in feature-window.cc
      n = window_size
      if snip_edges:
          m = (
              0
              if num_samples < window_size
              else 1 + (num_samples - window_size) // window_shift
          )
      else:
          m = (num_samples + (window_shift // 2)) // window_shift
  
      self.assertTrue(output.dim() == 2)
      self.assertTrue(output.shape[0] == m and output.shape[1] == n)
  
      window = torch.empty((m, window_size))
  
      for r in range(m):
          extract_window(
              window, waveform, r, window_size, window_shift, snip_edges
          )
      self.assertEqual(window, output)
  
file_path: audio/test/torchaudio_unittest/compliance/kaldi/legacy_test.py
imports: import torch
  import torchaudio.compliance.kaldi
  from torchaudio_unittest import common_utils
label_desc: Use image node_id 1 for calling the Test_Kaldi obj's underlying member method code with example usage: obj._test_get_strided_helper(num_samples, window_size, window_shift, snip_edges) without return types