class_docstr: STFT decoder for speech enhancement and separation
class_docstr_tok: ["STFT","decoder","for","speech","enhancement","and","separation"]
docstr: Reconfigure iSTFT window and hop lengths for a new sampling rate
  while keeping their duration fixed.
  
  Args:
      fs (int): new sampling rate
docstr_tok: ["Reconfigure","iSTFT","window","and","hop","lengths","for","a","new","sampling","rate","while","keeping","their","duration","fixed",".","Args",":","fs","(","int",")",":","new","sampling","rate"]
code: def _reconfig_for_fs(self, fs):
      """Reconfigure iSTFT window and hop lengths for a new sampling rate
      while keeping their duration fixed.
  
      Args:
          fs (int): new sampling rate
      """  # noqa: H405
      assert fs % self.default_fs == 0 or self.default_fs % fs == 0
      self.stft.n_fft = self.n_fft * fs // self.default_fs
      self.stft.win_length = self.win_length * fs // self.default_fs
      self.stft.hop_length = self.hop_length * fs // self.default_fs
  
file_path: espnet/espnet2/enh/decoder/stft_decoder.py
imports: import torch
  import torch_complex
  from packaging.version import parse
  from torch_complex.tensor import ComplexTensor
  from espnet2.enh.decoder.abs_decoder import AbsDecoder
  from espnet2.enh.layers.complex_utils import is_torch_complex_tensor
  from espnet2.layers.stft import Stft
label_desc: Use image node_id 4 for calling the STFTDecoder obj's underlying member method code with example usage: obj._reconfig_for_fs(fs) without return types