stft requires the return_complex parameter be given for real inputs, and will further require that return_complex=True in a future PyTorch release

[Snailgoo]

python3 evaluation.py --test_dir testdata/ --model_path ckpt/D2Former_epoch_77_0.055 --save_dir saved_tracks_best
audio_path: testdata/noisy/p287_001_noisy.wav
Traceback (most recent call last):
File "/D2Former/evaluation.py", line 102, in
evaluation(args.model_path, noisy_dir, clean_dir, args.save_tracks, args.save_dir, out_file)
File "/D2Former/evaluation.py", line 72, in evaluation
est_audio, length = enhance_one_track(model, noisy_path, saved_dir, 16000*8, n_fft, n_fft//4, save_tracks)
File "/py310_audio/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/D2Former/evaluation.py", line 36, in enhance_one_track
noisy_spec = torch.stft(noisy, n_fft, hop, window=torch.hamming_window(n_fft).cuda(), onesided=True)
File "/py310_audio/lib/python3.10/site-packages/torch/functional.py", line 650, in stft
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
RuntimeError: stft requires the return_complex parameter be given for real inputs, and will further require that return_complex=True in a future PyTorch release.

[Snailgoo]

follow the [Bug] RuntimeError: stft requires the return_complex parameter be given for real inputs #2449 [https://github.com/coqui-ai/TTS/issues/2449#top](coqui-ai/TTS#2449 (comment))
python3.10/site-packages/torch/functional.py:
at line 641:
insert this before return statement:
if not return_complex:
return torch.view_as_real(_VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
normalized, onesided, return_complex=True))
and not worked, new bugs :
Traceback (most recent call last):
File "/D2Former/evaluation.py", line 102, in
evaluation(args.model_path, noisy_dir, clean_dir, args.save_tracks, args.save_dir, out_file)
File "/D2Former/evaluation.py", line 72, in evaluation
est_audio, length = enhance_one_track(model, noisy_path, saved_dir, 16000*8, n_fft, n_fft//4, save_tracks)
File "/py310_audio/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/D2Former/evaluation.py", line 42, in enhance_one_track
est_audio = torch.istft(est_spec_uncompress, n_fft, hop, window=torch.hamming_window(n_fft).cuda(),
RuntimeError: istft requires a complex-valued input tensor matching the output from stft with return_complex=True.