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New Feature:

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- contentvec onnx
This commit is contained in:
w-okada 2023-07-08 03:18:23 +09:00
parent 900525e584
commit caa8c99f14
7 changed files with 68 additions and 19 deletions
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2
server/downloader/SampleDownloader.py
View File

@ -169,5 +169,5 @@ def _downloadSamples(samples: list[ModelSamples], sampleModelIds: list[Tuple[str
slotInfo = RVCModelSlotGenerator._setInfoByONNX(slotInfo)
else:
slotInfo = RVCModelSlotGenerator._setInfoByPytorch(slotInfo)
modelSlotManager.save_model_slot(targetSlotIndex, slotInfo)

11
server/downloader/WeightDownloader.py
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@ -7,6 +7,7 @@ from Exceptions import WeightDownladException
def downloadWeight(voiceChangerParams: VoiceChangerParams):
content_vec_500_onnx = voiceChangerParams.content_vec_500_onnx
hubert_base = voiceChangerParams.hubert_base
hubert_base_jp = voiceChangerParams.hubert_base_jp
hubert_soft = voiceChangerParams.hubert_soft
@ -67,7 +68,6 @@ def downloadWeight(voiceChangerParams: VoiceChangerParams):
"position": 5,
}
)
if os.path.exists(crepe_onnx_tiny) is False:
downloadParams.append(
{
@ -77,6 +77,15 @@ def downloadWeight(voiceChangerParams: VoiceChangerParams):
}
)
if os.path.exists(content_vec_500_onnx) is False:
downloadParams.append(
{
"url": "https://huggingface.co/wok000/weights_gpl/resolve/main/content-vec/contentvec-f.onnx",
"saveTo": content_vec_500_onnx,
"position": 7,
}
)
with ThreadPoolExecutor() as pool:
pool.map(download, downloadParams)

15
server/voice_changer/RVC/embedder/Embedder.py
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@ -1,18 +1,19 @@
from typing import Any, Protocol
from typing import Any
import torch
from torch import device
from const import EmbedderType
from voice_changer.RVC.embedder.EmbedderProtocol import EmbedderProtocol
class Embedder(Protocol):
embedderType: EmbedderType = "hubert_base"
file: str
isHalf: bool = True
dev: device
class Embedder(EmbedderProtocol):
def __init__(self):
self.embedderType: EmbedderType = "hubert_base"
self.file: str
self.dev: device
model: Any | None = None
self.model: Any | None = None
def loadModel(self, file: str, dev: device, isHalf: bool = True):
...

28
server/voice_changer/RVC/embedder/EmbedderManager.py
View File

@ -5,6 +5,7 @@ from voice_changer.RVC.embedder.Embedder import Embedder
from voice_changer.RVC.embedder.FairseqContentvec import FairseqContentvec
from voice_changer.RVC.embedder.FairseqHubert import FairseqHubert
from voice_changer.RVC.embedder.FairseqHubertJp import FairseqHubertJp
from voice_changer.RVC.embedder.OnnxContentvec import OnnxContentvec
from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
@ -27,10 +28,11 @@ class EmbedderManager:
print("[Voice Changer] generate new embedder. (not match)")
cls.currentEmbedder = cls.loadEmbedder(embederType, isHalf, dev)
else:
cls.currentEmbedder.setDevice(dev)
cls.currentEmbedder.setHalf(isHalf)
# print("[Voice Changer] generate new embedder. (ANYWAY)", isHalf)
# cls.currentEmbedder = cls.loadEmbedder(embederType, file, isHalf, dev)
print("[Voice Changer] generate new embedder. (anyway)")
cls.currentEmbedder = cls.loadEmbedder(embederType, isHalf, dev)
# cls.currentEmbedder.setDevice(dev)
# cls.currentEmbedder.setHalf(isHalf)
return cls.currentEmbedder
@classmethod
@ -38,13 +40,23 @@ class EmbedderManager:
cls, embederType: EmbedderType, isHalf: bool, dev: device
) -> Embedder:
if embederType == "hubert_base":
file = cls.params.hubert_base
return FairseqHubert().loadModel(file, dev, isHalf)
try:
file = cls.params.content_vec_500_onnx
return OnnxContentvec().loadModel(file, dev)
except Exception as e:
print(e)
file = cls.params.hubert_base
return FairseqHubert().loadModel(file, dev, isHalf)
elif embederType == "hubert-base-japanese":
file = cls.params.hubert_base_jp
return FairseqHubertJp().loadModel(file, dev, isHalf)
elif embederType == "contentvec":
file = cls.params.hubert_base
return FairseqContentvec().loadModel(file, dev, isHalf)
try:
file = cls.params.content_vec_500_onnx
return OnnxContentvec().loadModel(file, dev)
except Exception as e:
print(e)
file = cls.params.hubert_base
return FairseqContentvec().loadModel(file, dev, isHalf)
else:
return FairseqHubert().loadModel(file, dev, isHalf)

15
server/voice_changer/RVC/embedder/EmbedderProtocol.py Normal file
View File

@ -0,0 +1,15 @@
from typing import Protocol
import torch
from torch import device
class EmbedderProtocol(Protocol):
def loadModel(self, file: str, dev: device, isHalf: bool = True):
...
def extractFeatures(
self, feats: torch.Tensor, embOutputLayer=9, useFinalProj=True
) -> torch.Tensor:
...

13
server/voice_changer/RVC/embedder/OnnxContentvec.py Normal file
View File

@ -0,0 +1,13 @@
import torch
from voice_changer.RVC.embedder.Embedder import Embedder
class OnnxContentvec(Embedder):
def loadModel(self, file: str, dev: torch.device) -> Embedder:
raise Exception("Not implemented")
def extractFeatures(
self, feats: torch.Tensor, embOutputLayer=9, useFinalProj=True
) -> torch.Tensor:
raise Exception("Not implemented")

3
server/voice_changer/RVC/pipeline/Pipeline.py
View File

@ -209,14 +209,13 @@ class Pipeline(object):
# apply silent front for inference
if type(self.inferencer) in [OnnxRVCInferencer, OnnxRVCInferencerNono]:
npyOffset = math.floor(silence_front * 16000) // 360
feats = feats[:, npyOffset * 2 :, :]
feats = feats[:, npyOffset * 2 :, :] # NOQA
feats_len = feats.shape[1]
if pitch is not None and pitchf is not None:
pitch = pitch[:, -feats_len:]
pitchf = pitchf[:, -feats_len:]
p_len = torch.tensor([feats_len], device=self.device).long()
# 推論実行
try: