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import os,sys,pdb,torch |
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f0up_key=sys.argv[1] |
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input_path=sys.argv[2] |
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index_path=sys.argv[3] |
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npy_path=sys.argv[4] |
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opt_path=sys.argv[5] |
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model_path=sys.argv[6] |
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print(sys.argv) |
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sys.argv=['myinfer.py'] |
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now_dir=os.getcwd() |
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sys.path.append(now_dir) |
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from vc_infer_pipeline import VC |
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from infer_pack.models import SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFsid_nono |
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from my_utils import load_audio |
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from fairseq import checkpoint_utils |
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from scipy.io import wavfile |
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hubert_model=None |
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is_half=False |
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device="cuda" |
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def load_hubert(): |
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global hubert_model |
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(["hubert_base.pt"],suffix="",) |
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hubert_model = models[0] |
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hubert_model = hubert_model.to(device) |
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if(is_half):hubert_model = hubert_model.half() |
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else:hubert_model = hubert_model.float() |
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hubert_model.eval() |
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def vc_single(sid,input_audio,f0_up_key,f0_file,f0_method,file_index,file_big_npy,index_rate): |
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global tgt_sr,net_g,vc,hubert_model |
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if input_audio is None:return "You need to upload an audio", None |
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f0_up_key = int(f0_up_key) |
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audio=load_audio(input_audio,16000) |
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times = [0, 0, 0] |
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if(hubert_model==None):load_hubert() |
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if_f0 = cpt.get("f0", 1) |
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audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file) |
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print(times) |
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return audio_opt |
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def get_vc(sid): |
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global n_spk,tgt_sr,net_g,vc,cpt |
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person = "weights/%s" % (sid) |
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print("loading %s"%person) |
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cpt = torch.load(person, map_location="cpu") |
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tgt_sr = cpt["config"][-1] |
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cpt["config"][-3]=cpt["weight"]["emb_g.weight"].shape[0] |
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if_f0=cpt.get("f0",1) |
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if(if_f0==1): |
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net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half) |
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else: |
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net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"]) |
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del net_g.enc_q |
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print(net_g.load_state_dict(cpt["weight"], strict=False)) |
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net_g.eval().to(device) |
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if (is_half):net_g = net_g.half() |
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else:net_g = net_g.float() |
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vc = VC(tgt_sr, device, is_half) |
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n_spk=cpt["config"][-3] |
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get_vc(model_path) |
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wav_opt=vc_single(0,input_path,f0up_key,None,"harvest",index_path,npy_path,0.6) |
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wavfile.write(opt_path, tgt_sr, wav_opt) |
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