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https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
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optimize: move vc_infer_pipeline to lib.train
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parent
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commit
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2
app.py
2
app.py
@ -7,7 +7,7 @@ import librosa
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import numpy as np
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import numpy as np
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import logging
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import logging
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from fairseq import checkpoint_utils
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from fairseq import checkpoint_utils
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from vc_infer_pipeline import VC
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from lib.train.vc_infer_pipeline import VC
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import traceback
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import traceback
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from config import defaultconfig as config
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from config import defaultconfig as config
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from lib.infer_pack.models import (
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from lib.infer_pack.models import (
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@ -35,7 +35,7 @@ from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
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from infer_uvr5 import _audio_pre_, _audio_pre_new
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from infer_uvr5 import _audio_pre_, _audio_pre_new
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from lib.audio import load_audio
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from lib.audio import load_audio
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from lib.train.process_ckpt import change_info, extract_small_model, merge, show_info
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from lib.train.process_ckpt import change_info, extract_small_model, merge, show_info
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from vc_infer_pipeline import VC
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from lib.train.vc_infer_pipeline import VC
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from sklearn.cluster import MiniBatchKMeans
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from sklearn.cluster import MiniBatchKMeans
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logging.getLogger("numba").setLevel(logging.WARNING)
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logging.getLogger("numba").setLevel(logging.WARNING)
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@ -109,7 +109,7 @@ print(sys.argv)
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config = Config(device, is_half)
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config = Config(device, is_half)
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now_dir = os.getcwd()
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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sys.path.append(now_dir)
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from vc_infer_pipeline import VC
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from lib.train.vc_infer_pipeline import VC
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from lib.infer_pack.models import (
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from lib.infer_pack.models import (
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SynthesizerTrnMs256NSFsid,
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SynthesizerTrnMs256NSFsid,
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SynthesizerTrnMs256NSFsid_nono,
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SynthesizerTrnMs256NSFsid_nono,
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@ -7,7 +7,7 @@ from lib.infer_pack.models import (
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SynthesizerTrnMs768NSFsid,
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SynthesizerTrnMs768NSFsid,
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SynthesizerTrnMs768NSFsid_nono,
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SynthesizerTrnMs768NSFsid_nono,
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)
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)
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from vc_infer_pipeline import VC
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from lib.train.vc_infer_pipeline import VC
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from multiprocessing import cpu_count
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from multiprocessing import cpu_count
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import numpy as np
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import numpy as np
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import torch
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import torch
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