code: def _spectro(
      x: torch.Tensor,
      n_fft: int = 512,
      hop_length: int = 0,
      pad: int = 0,
  ) -> torch.Tensor:
      other = list(x.shape[:-1])
      length = int(x.shape[-1])
      x = x.reshape(-1, length)
      z = torch.stft(
          x,
          n_fft * (1 + pad),
          hop_length,
          window=torch.hann_window(n_fft).to(x),
          win_length=n_fft,
          normalized=True,
          center=True,
          return_complex=True,
          pad_mode="reflect",
      )
      _, freqs, frame = z.shape
      other.extend([freqs, frame])
      return z.view(other)
  
imports: import math
  import typing
  from typing import Any, Dict, List, Optional
  import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 3 for calling a global function with example usage: _spectro(x, n_fft, hop_length, pad) and returns: z