code: def _ispectro(
      z: torch.Tensor,
      hop_length: int = 0,
      length: int = 0,
      pad: int = 0,
  ) -> torch.Tensor:
      other = list(z.shape[:-2])
      freqs = int(z.shape[-2])
      frames = int(z.shape[-1])
  
      n_fft = 2 * freqs - 2
      z = z.view(-1, freqs, frames)
      win_length = n_fft // (1 + pad)
      x = torch.istft(
          z,
          n_fft,
          hop_length,
          window=torch.hann_window(win_length).to(z.real),
          win_length=win_length,
          normalized=True,
          length=length,
          center=True,
      )
      _, length = x.shape
      other.append(length)
      return x.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 4 for calling a global function with example usage: _ispectro(z, hop_length, length, pad) and returns: x