code: def _frame(data, window_length, hop_length):
      num_samples = data.shape[0]
      num_frames = 1 + int(
          math.floor((num_samples - window_length) / hop_length)
      )
      shape = (num_frames, window_length) + data.shape[1:]
      strides = (data.stride()[0] * hop_length,) + data.stride()
      return torch.as_strided(data, shape, strides)
  
file_path: audio/src/torchaudio/prototype/pipelines/_vggish/_vggish_impl.py
imports: import math
  import torch
label_desc: Use image node_id 3 for calling a global function with example usage: _frame(data, window_length, hop_length) and returns: torch