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import torch | |
if torch.cuda.is_available() and torch.cuda.get_device_name().endswith("[ZLUDA]"): | |
_torch_stft = torch.stft | |
def z_stft( | |
audio: torch.Tensor, | |
n_fft: int, | |
hop_length: int = None, | |
win_length: int = None, | |
window: torch.Tensor = None, | |
center: bool = True, | |
pad_mode: str = "reflect", | |
normalized: bool = False, | |
onesided: bool = None, | |
return_complex: bool = None, | |
): | |
sd = audio.device | |
return _torch_stft( | |
audio.to("cpu"), | |
n_fft=n_fft, | |
hop_length=hop_length, | |
win_length=win_length, | |
window=window.to("cpu"), | |
center=center, | |
pad_mode=pad_mode, | |
normalized=normalized, | |
onesided=onesided, | |
return_complex=return_complex, | |
).to(sd) | |
def z_jit(f, *_, **__): | |
f.graph = torch._C.Graph() | |
return f | |
# hijacks | |
torch.stft = z_stft | |
torch.jit.script = z_jit | |
# disabling unsupported cudnn | |
torch.backends.cudnn.enabled = False | |
torch.backends.cuda.enable_flash_sdp(False) | |
torch.backends.cuda.enable_math_sdp(True) | |
torch.backends.cuda.enable_mem_efficient_sdp(False) | |