From eb546d360728770dd001314066f99bd2cd40ce50 Mon Sep 17 00:00:00 2001 From: Plachta Date: Tue, 14 Feb 2023 18:12:41 +0800 Subject: [PATCH] upload files --- VC_inference.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/VC_inference.py b/VC_inference.py index 317a082..45b5991 100644 --- a/VC_inference.py +++ b/VC_inference.py @@ -14,7 +14,7 @@ from models_infer import SynthesizerTrn from text import text_to_sequence import gradio as gr import torchaudio - +device = "cuda:0" if torch.cuda.is_available() else "cpu" def get_text(text, hps): text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners) if hps.data.add_blank: @@ -37,14 +37,14 @@ def create_vc_fn(model, hps, speaker_ids): if sampling_rate != hps.data.sampling_rate: audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=hps.data.sampling_rate) with no_grad(): - y = torch.FloatTensor(audio) + y = torch.FloatTensor(audio).to(device) y = y.unsqueeze(0) spec = spectrogram_torch(y, hps.data.filter_length, hps.data.sampling_rate, hps.data.hop_length, hps.data.win_length, - center=False) - spec_lengths = LongTensor([spec.size(-1)]) - sid_src = LongTensor([original_speaker_id]) - sid_tgt = LongTensor([target_speaker_id]) + center=False).to(device) + spec_lengths = LongTensor([spec.size(-1)]).to(device) + sid_src = LongTensor([original_speaker_id]).to(device) + sid_tgt = LongTensor([target_speaker_id]).to(device) audio = model.voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt)[0][ 0, 0].data.cpu().float().numpy() del y, spec, spec_lengths, sid_src, sid_tgt @@ -54,11 +54,11 @@ def create_vc_fn(model, hps, speaker_ids): if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--model_dir", default="./G_latest.pth", help="directory to your fine-tuned model") - parser.add_argument("--share", default=True, help="make link public (used in colab)") + parser.add_argument("--share", default=False, help="make link public (used in colab)") args = parser.parse_args() hps = utils.get_hparams_from_file("./configs/finetune_speaker.json") - device = "cpu" + net_g = SynthesizerTrn( len(hps.symbols),