mirror of
https://github.com/w-okada/voice-changer.git
synced 2025-01-08 11:57:48 +08:00
logger, handle creating pipeline exception
This commit is contained in:
w-okada
parent
d2a2826a82
commit
f96b4c2414
@ -39,3 +39,13 @@ class VoiceChangerIsNotSelectedException(Exception):
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class WeightDownladException(Exception):
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def __str__(self):
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return repr("Failed to download weight.")
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class PipelineCreateException(Exception):
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def __str__(self):
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return repr("Failed to create Pipeline.")
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class PipelineNotInitializedException(Exception):
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def __str__(self):
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return repr("Pipeline is not initialized.")
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@ -1,4 +1,3 @@
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import logging
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import sys
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from distutils.util import strtobool
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@ -25,10 +24,10 @@ from const import (
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)
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import subprocess
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import multiprocessing as mp
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from mods.log_control import setup_loggers
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from mods.log_control import VoiceChangaerLogger
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setup_loggers(f"Booting PHASE :{__name__}")
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logger = logging.getLogger("vcclient")
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logger = VoiceChangaerLogger.get_instance().getLogger()
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logger.debug(f"---------------- Booting PHASE :{__name__} -----------------")
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def setupArgParser():
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@ -62,22 +61,23 @@ def printMessage(message, level=0):
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pf = platform.system()
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if pf == "Windows":
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if level == 0:
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print(f"{message}")
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message = f"{message}"
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elif level == 1:
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print(f" {message}")
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message = f" {message}"
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elif level == 2:
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print(f" {message}")
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message = f" {message}"
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else:
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print(f" {message}")
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message = f" {message}"
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else:
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if level == 0:
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print(f"\033[17m{message}\033[0m")
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message = f"\033[17m{message}\033[0m"
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elif level == 1:
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print(f"\033[34m {message}\033[0m")
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message = f"\033[34m {message}\033[0m"
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elif level == 2:
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print(f"\033[32m {message}\033[0m")
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message = f"\033[32m {message}\033[0m"
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else:
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print(f"\033[47m {message}\033[0m")
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message = f"\033[47m {message}\033[0m"
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logger.info(message)
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parser = setupArgParser()
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@ -112,7 +112,7 @@ def localServer(logLevel: str = "critical"):
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log_level=logLevel,
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)
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except Exception as e:
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print("[Voice Changer] Web Server Launch Exception", e)
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logger.error(f"[Voice Changer] Web Server Launch Exception, {e}")
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if __name__ == "MMVCServerSIO":
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@ -129,7 +129,7 @@ if __name__ == "__mp_main__":
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if __name__ == "__main__":
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mp.freeze_support()
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logger.info(args)
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logger.debug(args)
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printMessage(f"PYTHON:{sys.version}", level=2)
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printMessage("Voice Changerを起動しています。", level=2)
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@ -139,14 +139,12 @@ if __name__ == "__main__":
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except WeightDownladException:
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printMessage("RVC用のモデルファイルのダウンロードに失敗しました。", level=2)
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printMessage("failed to download weight for rvc", level=2)
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logger.warn("failed to download weight for rvc")
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# ダウンロード(Sample)
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try:
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downloadInitialSamples(args.sample_mode, args.model_dir)
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except Exception as e:
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print("[Voice Changer] loading sample failed", e)
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logger.warn(f"[Voice Changer] loading sample failed {e}",)
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printMessage(f"[Voice Changer] loading sample failed {e}", level=2)
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# PORT = args.p
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@ -232,7 +230,7 @@ if __name__ == "__main__":
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log_level=args.logLevel,
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)
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except Exception as e:
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print("[Voice Changer] Web Server Launch Exception", e)
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logger.error(f"[Voice Changer] Web Server(https) Launch Exception, {e}")
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else:
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p = mp.Process(name="p", target=localServer, args=(args.logLevel,))
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@ -241,13 +239,13 @@ if __name__ == "__main__":
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if sys.platform.startswith("win"):
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process = subprocess.Popen([NATIVE_CLIENT_FILE_WIN, "--disable-gpu", "-u", f"http://localhost:{PORT}/"])
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return_code = process.wait()
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print("client closed.")
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logger.info("client closed.")
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p.terminate()
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elif sys.platform.startswith("darwin"):
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process = subprocess.Popen([NATIVE_CLIENT_FILE_MAC, "--disable-gpu", "-u", f"http://localhost:{PORT}/"])
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return_code = process.wait()
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print("client closed.")
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logger.info("client closed.")
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p.terminate()
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except Exception as e:
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print(e)
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logger.error(f"[Voice Changer] Launch Exception, {e}")
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@ -2,6 +2,10 @@ import requests # type: ignore
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import os
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from tqdm import tqdm
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from mods.log_control import VoiceChangaerLogger
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logger = VoiceChangaerLogger.get_instance().getLogger()
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def download(params):
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url = params["url"]
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@ -31,7 +35,7 @@ def download(params):
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f.write(chunk)
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except Exception as e:
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print(e)
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logger.warning(e)
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def download_no_tqdm(params):
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@ -51,6 +55,6 @@ def download_no_tqdm(params):
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if countToDot % 1024 == 0:
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print(".", end="", flush=True)
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print("+", end="", flush=True)
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logger.info(f"[Voice Changer] download sample catalog. {saveTo}")
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except Exception as e:
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print(e)
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logger.warning(e)
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@ -6,17 +6,20 @@ from typing import Any, Tuple
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from const import RVCSampleMode, getSampleJsonAndModelIds
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from data.ModelSample import ModelSamples, generateModelSample
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from data.ModelSlot import DiffusionSVCModelSlot, ModelSlot, RVCModelSlot
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from mods.log_control import VoiceChangaerLogger
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from voice_changer.DiffusionSVC.DiffusionSVCModelSlotGenerator import DiffusionSVCModelSlotGenerator
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from voice_changer.ModelSlotManager import ModelSlotManager
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from voice_changer.RVC.RVCModelSlotGenerator import RVCModelSlotGenerator
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from downloader.Downloader import download, download_no_tqdm
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logger = VoiceChangaerLogger.get_instance().getLogger()
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def downloadInitialSamples(mode: RVCSampleMode, model_dir: str):
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sampleJsonUrls, sampleModels = getSampleJsonAndModelIds(mode)
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sampleJsons = _downloadSampleJsons(sampleJsonUrls)
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if os.path.exists(model_dir):
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print("[Voice Changer] model_dir is already exists. skip download samples.")
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logger.info("[Voice Changer] model_dir is already exists. skip download samples.")
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return
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samples = _generateSampleList(sampleJsons)
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slotIndex = list(range(len(sampleModels)))
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@ -85,7 +88,7 @@ def _downloadSamples(samples: list[ModelSamples], sampleModelIds: list[Tuple[str
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match = True
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break
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if match is False:
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print(f"[Voice Changer] initiail sample not found. {targetSampleId}")
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logger.warn(f"[Voice Changer] initiail sample not found. {targetSampleId}")
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continue
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# 検出されたら、、、
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@ -194,10 +197,10 @@ def _downloadSamples(samples: list[ModelSamples], sampleModelIds: list[Tuple[str
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slotInfo.isONNX = slotInfo.modelFile.endswith(".onnx")
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modelSlotManager.save_model_slot(targetSlotIndex, slotInfo)
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else:
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print(f"[Voice Changer] {sample.voiceChangerType} is not supported.")
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logger.warn(f"[Voice Changer] {sample.voiceChangerType} is not supported.")
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# ダウンロード
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print("[Voice Changer] Downloading model files...")
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logger.info("[Voice Changer] Downloading model files...")
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if withoutTqdm:
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with ThreadPoolExecutor() as pool:
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pool.map(download_no_tqdm, downloadParams)
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@ -206,7 +209,7 @@ def _downloadSamples(samples: list[ModelSamples], sampleModelIds: list[Tuple[str
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pool.map(download, downloadParams)
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# メタデータ作成
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print("[Voice Changer] Generating metadata...")
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logger.info("[Voice Changer] Generating metadata...")
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for targetSlotIndex in slotIndex:
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slotInfo = modelSlotManager.get_slot_info(targetSlotIndex)
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if slotInfo.voiceChangerType == "RVC":
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@ -1,12 +1,12 @@
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import logging
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import os
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from concurrent.futures import ThreadPoolExecutor
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from downloader.Downloader import download
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from mods.log_control import VoiceChangaerLogger
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from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
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from Exceptions import WeightDownladException
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logger = logging.getLogger("vcclient")
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logger = VoiceChangaerLogger.get_instance().getLogger()
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def downloadWeight(voiceChangerParams: VoiceChangerParams):
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@ -120,7 +120,7 @@ def downloadWeight(voiceChangerParams: VoiceChangerParams):
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for weight in weight_files:
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if os.path.exists(weight):
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file_size = os.path.getsize(weight)
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logger.info(f"weight file [{weight}]: {file_size}")
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logger.debug(f"weight file [{weight}]: {file_size}")
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else:
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logger.warn(f"weight file is missing. {weight}")
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logger.warning(f"weight file is missing. {weight}")
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raise WeightDownladException()
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@ -8,40 +8,123 @@ class UvicornSuppressFilter(logging.Filter):
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return False
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class NullHandler(logging.Handler):
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def emit(self, record):
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pass
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class VoiceChangaerLogger:
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_instance = None
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@classmethod
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def get_instance(cls):
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if cls._instance is None:
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cls._instance = cls()
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return cls._instance
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def __init__(self):
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# logger = logging.getLogger("uvicorn.error")
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# logger.addFilter(UvicornSuppressFilter())
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# logging.basicConfig(filename='myapp.log', level=logging.INFO)
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# logging.basicConfig(level=logging.NOTSET)
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logging.root.handlers = [NullHandler()]
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logger = logging.getLogger("fairseq.tasks.hubert_pretraining")
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logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("fairseq.models.hubert.hubert")
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logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("fairseq.tasks.text_to_speech")
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logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.ssa")
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logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.interpreter")
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logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.byteflow")
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logger.addFilter(UvicornSuppressFilter())
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# logger.propagate = False
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logger = logging.getLogger("multipart.multipart")
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logger.propagate = False
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logging.getLogger("asyncio").setLevel(logging.WARNING)
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logger = logging.getLogger("vcclient")
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logger.setLevel(logging.DEBUG)
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if not logger.handlers:
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# pass
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# file_handler = logging.FileHandler('vvclient.log', encoding='utf-8', mode='w')
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file_handler = logging.FileHandler('vvclient.log', encoding='utf-8')
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file_formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(process)d - %(message)s')
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file_handler.setFormatter(file_formatter)
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file_handler.setLevel(logging.DEBUG)
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logger.addHandler(file_handler)
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stream_formatter = logging.Formatter('%(message)s')
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stream_handler = logging.StreamHandler()
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stream_handler.setFormatter(stream_formatter)
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stream_handler.setLevel(logging.INFO)
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logger.addHandler(stream_handler)
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self.logger = logger
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def getLogger(self):
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return self.logger
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def setup_loggers(startMessage: str):
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# logger = logging.getLogger("uvicorn.error")
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pass
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# # logger = logging.getLogger("uvicorn.error")
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# # logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("fairseq.tasks.hubert_pretraining")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("fairseq.tasks.hubert_pretraining")
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logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("fairseq.models.hubert.hubert")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("fairseq.models.hubert.hubert")
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logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("fairseq.tasks.text_to_speech")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("fairseq.tasks.text_to_speech")
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logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("numba.core.ssa")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.ssa")
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logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("numba.core.interpreter")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.interpreter")
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logger.addFilter(UvicornSuppressFilter())
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# logger = logging.getLogger("numba.core.byteflow")
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# logger.addFilter(UvicornSuppressFilter())
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logger = logging.getLogger("numba.core.byteflow")
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logger.addFilter(UvicornSuppressFilter())
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# # logger.propagate = False
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# logger = logging.getLogger("multipart.multipart")
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# logger.propagate = False
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logger = logging.getLogger("multipart.multipart")
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logger.propagate = False
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# logging.getLogger("asyncio").setLevel(logging.WARNING)
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logging.getLogger("asyncio").setLevel(logging.WARNING)
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# logger = logging.getLogger("vcclient")
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# logger.setLevel(logging.DEBUG)
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logger = logging.getLogger("vcclient")
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logger.setLevel(logging.INFO)
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fh = logging.FileHandler('vvclient.log', encoding='utf-8')
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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fh.setFormatter(formatter)
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fh.setLevel(logging.INFO)
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logger.addHandler(fh)
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logger.info(f"Start Logging, {startMessage}")
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# if not logger.handlers:
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# # file_handler = logging.FileHandler('vvclient.log', encoding='utf-8', mode='w')
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# file_handler = logging.FileHandler('vvclient.log', encoding='utf-8')
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# file_formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(process)d - %(message)s')
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# file_handler.setFormatter(file_formatter)
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# file_handler.setLevel(logging.INFO)
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# logger.addHandler(file_handler)
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# stream_formatter = logging.Formatter('%(message)s')
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# stream_handler = logging.StreamHandler()
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# stream_handler.setFormatter(stream_formatter)
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# stream_handler.setLevel(logging.DEBUG)
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# logger.addHandler(stream_handler)
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# logger.info(f"Start Logging, {startMessage}")
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@ -1,6 +1,7 @@
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from dataclasses import asdict
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import numpy as np
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from data.ModelSlot import DiffusionSVCModelSlot
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from mods.log_control import VoiceChangaerLogger
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from voice_changer.DiffusionSVC.DiffusionSVCSettings import DiffusionSVCSettings
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from voice_changer.DiffusionSVC.inferencer.InferencerManager import InferencerManager
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from voice_changer.DiffusionSVC.pipeline.Pipeline import Pipeline
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@ -13,12 +14,14 @@ from voice_changer.RVC.embedder.EmbedderManager import EmbedderManager
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# from voice_changer.RVC.onnxExporter.export2onnx import export2onnx
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from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
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from Exceptions import DeviceCannotSupportHalfPrecisionException
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from Exceptions import DeviceCannotSupportHalfPrecisionException, PipelineCreateException
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logger = VoiceChangaerLogger.get_instance().getLogger()
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class DiffusionSVC(VoiceChangerModel):
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def __init__(self, params: VoiceChangerParams, slotInfo: DiffusionSVCModelSlot):
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print("[Voice Changer] [DiffusionSVC] Creating instance ")
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logger.info("[Voice Changer] [DiffusionSVC] Creating instance ")
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self.deviceManager = DeviceManager.get_instance()
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EmbedderManager.initialize(params)
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PitchExtractorManager.initialize(params)
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@ -36,10 +39,14 @@ class DiffusionSVC(VoiceChangerModel):
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self.slotInfo = slotInfo
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def initialize(self):
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print("[Voice Changer] [DiffusionSVC] Initializing... ")
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logger.info("[Voice Changer] [DiffusionSVC] Initializing... ")
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# pipelineの生成
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self.pipeline = createPipeline(self.slotInfo, self.settings.gpu, self.settings.f0Detector, self.inputSampleRate, self.outputSampleRate)
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try:
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self.pipeline = createPipeline(self.slotInfo, self.settings.gpu, self.settings.f0Detector, self.inputSampleRate, self.outputSampleRate)
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except PipelineCreateException as e: # NOQA
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logger.error("[Voice Changer] pipeline create failed. check your model is valid.")
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return
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# その他の設定
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self.settings.tran = self.slotInfo.defaultTune
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@ -47,7 +54,7 @@ class DiffusionSVC(VoiceChangerModel):
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self.settings.kStep = self.slotInfo.defaultKstep
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self.settings.speedUp = self.slotInfo.defaultSpeedup
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print("[Voice Changer] [DiffusionSVC] Initializing... done")
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logger.info("[Voice Changer] [DiffusionSVC] Initializing... done")
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def setSamplingRate(self, inputSampleRate, outputSampleRate):
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self.inputSampleRate = inputSampleRate
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@ -55,7 +62,7 @@ class DiffusionSVC(VoiceChangerModel):
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self.initialize()
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|
||||
def update_settings(self, key: str, val: int | float | str):
|
||||
print("[Voice Changer][DiffusionSVC]: update_settings", key, val)
|
||||
logger.info(f"[Voice Changer][DiffusionSVC]: update_settings {key}:{val}")
|
||||
if key in self.settings.intData:
|
||||
setattr(self.settings, key, int(val))
|
||||
if key == "gpu":
|
||||
@ -174,7 +181,7 @@ class DiffusionSVC(VoiceChangerModel):
|
||||
result = audio_out.detach().cpu().numpy()
|
||||
return result
|
||||
except DeviceCannotSupportHalfPrecisionException as e: # NOQA
|
||||
print("[Device Manager] Device cannot support half precision. Fallback to float....")
|
||||
logger.warn("[Device Manager] Device cannot support half precision. Fallback to float....")
|
||||
self.deviceManager.setForceTensor(True)
|
||||
self.initialize()
|
||||
# raise e
|
||||
|
||||
@ -8,6 +8,7 @@ from Exceptions import (
|
||||
HalfPrecisionChangingException,
|
||||
NotEnoughDataExtimateF0,
|
||||
)
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
from voice_changer.DiffusionSVC.inferencer.Inferencer import Inferencer
|
||||
from voice_changer.DiffusionSVC.pitchExtractor.PitchExtractor import PitchExtractor
|
||||
|
||||
@ -17,9 +18,8 @@ from voice_changer.common.VolumeExtractor import VolumeExtractor
|
||||
from torchaudio.transforms import Resample
|
||||
|
||||
from voice_changer.utils.Timer import Timer
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger("vcclient")
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
class Pipeline(object):
|
||||
@ -60,17 +60,11 @@ class Pipeline(object):
|
||||
self.resamplerIn = resamplerIn
|
||||
self.resamplerOut = resamplerOut
|
||||
|
||||
print("VOLUME EXTRACTOR", self.volumeExtractor)
|
||||
print("GENERATE INFERENCER", self.inferencer)
|
||||
print("GENERATE EMBEDDER", self.embedder)
|
||||
print("GENERATE PITCH EXTRACTOR", self.pitchExtractor)
|
||||
logger.info("VOLUME EXTRACTOR" + str(self.volumeExtractor))
|
||||
logger.info("GENERATE INFERENCER" + str(self.inferencer))
|
||||
logger.info("GENERATE EMBEDDER" + str(self.embedder))
|
||||
logger.info("GENERATE PITCH EXTRACTOR" + str(self.pitchExtractor))
|
||||
|
||||
|
||||
|
||||
self.targetSR = targetSR
|
||||
self.device = device
|
||||
self.isHalf = False
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
import traceback
|
||||
from Exceptions import PipelineCreateException
|
||||
from data.ModelSlot import DiffusionSVCModelSlot
|
||||
from voice_changer.DiffusionSVC.inferencer.InferencerManager import InferencerManager
|
||||
from voice_changer.DiffusionSVC.pipeline.Pipeline import Pipeline
|
||||
@ -22,6 +23,7 @@ def createPipeline(modelSlot: DiffusionSVCModelSlot, gpu: int, f0Detector: str,
|
||||
except Exception as e:
|
||||
print("[Voice Changer] exception! loading inferencer", e)
|
||||
traceback.print_exc()
|
||||
raise PipelineCreateException("[Voice Changer] exception! loading inferencer")
|
||||
|
||||
# Embedder 生成
|
||||
try:
|
||||
@ -34,6 +36,7 @@ def createPipeline(modelSlot: DiffusionSVCModelSlot, gpu: int, f0Detector: str,
|
||||
except Exception as e:
|
||||
print("[Voice Changer] exception! loading embedder", e)
|
||||
traceback.print_exc()
|
||||
raise PipelineCreateException("[Voice Changer] exception! loading embedder")
|
||||
|
||||
# pitchExtractor
|
||||
pitchExtractor = PitchExtractorManager.getPitchExtractor(f0Detector, gpu)
|
||||
|
||||
@ -1,5 +1,8 @@
|
||||
import wave
|
||||
import os
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
class IORecorder:
|
||||
@ -19,10 +22,10 @@ class IORecorder:
|
||||
|
||||
def _clearFile(self, filename: str):
|
||||
if os.path.exists(filename):
|
||||
print("[IORecorder] delete old analyze file.", filename)
|
||||
logger.info(f"[IORecorder] delete old analyze file. {filename}")
|
||||
os.remove(filename)
|
||||
else:
|
||||
print("[IORecorder] old analyze file not exist.", filename)
|
||||
logger.info(f"[IORecorder] old analyze file not exist. {filename}")
|
||||
|
||||
def writeInput(self, wav):
|
||||
self.fi.writeframes(wav)
|
||||
|
||||
@ -4,8 +4,11 @@ from dataclasses import dataclass, field
|
||||
import numpy as np
|
||||
|
||||
from const import ServerAudioDeviceType
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
# from const import SERVER_DEVICE_SAMPLE_RATES
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
@dataclass
|
||||
class ServerAudioDevice:
|
||||
@ -56,8 +59,8 @@ def list_audio_device():
|
||||
try:
|
||||
audioDeviceList = sd.query_devices()
|
||||
except Exception as e:
|
||||
print("[Voice Changer] ex:query_devices")
|
||||
print(e)
|
||||
logger.error("[Voice Changer] ex:query_devices")
|
||||
logger.exception(e)
|
||||
raise e
|
||||
|
||||
inputAudioDeviceList = [d for d in audioDeviceList if d["max_input_channels"] > 0]
|
||||
|
||||
@ -4,6 +4,7 @@ import numpy as np
|
||||
from const import SERVER_DEVICE_SAMPLE_RATES
|
||||
|
||||
from queue import Queue
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
from voice_changer.Local.AudioDeviceList import checkSamplingRate, list_audio_device
|
||||
import time
|
||||
@ -17,6 +18,8 @@ from typing import Union
|
||||
from typing import Literal, TypeAlias
|
||||
AudioDeviceKind: TypeAlias = Literal["input", "output"]
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
@dataclass
|
||||
class ServerDeviceSettings:
|
||||
|
||||
@ -4,7 +4,7 @@ import sys
|
||||
import json
|
||||
import logging
|
||||
|
||||
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
# logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
logger = logging
|
||||
|
||||
hann_window = {}
|
||||
|
||||
@ -1,11 +1,12 @@
|
||||
import logging
|
||||
from const import UPLOAD_DIR
|
||||
from data.ModelSlot import ModelSlots, loadAllSlotInfo, saveSlotInfo
|
||||
import json
|
||||
import os
|
||||
import shutil
|
||||
|
||||
logger = logging.getLogger("vcclient")
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
class ModelSlotManager:
|
||||
@ -14,7 +15,7 @@ class ModelSlotManager:
|
||||
def __init__(self, model_dir: str):
|
||||
self.model_dir = model_dir
|
||||
self.modelSlots = loadAllSlotInfo(self.model_dir)
|
||||
logger.info(f"[MODEL SLOT INFO] {self.modelSlots}")
|
||||
logger.debug(f"[MODEL SLOT INFO] {self.modelSlots}")
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls, model_dir: str):
|
||||
@ -41,7 +42,7 @@ class ModelSlotManager:
|
||||
self._save_model_slot(slotIndex, slotInfo)
|
||||
|
||||
def update_model_info(self, newData: str):
|
||||
print("[Voice Changer] UPDATE MODEL INFO", newData)
|
||||
logger.info(f"[Voice Changer] UPDATE MODEL INFO, {newData}")
|
||||
newDataDict = json.loads(newData)
|
||||
slotInfo = self._load_model_slot(newDataDict["slot"])
|
||||
if newDataDict["key"] == "speakers":
|
||||
@ -64,4 +65,5 @@ class ModelSlotManager:
|
||||
setattr(slotInfo, paramsDict["name"], storePath)
|
||||
self._save_model_slot(paramsDict["slot"], slotInfo)
|
||||
except Exception as e:
|
||||
print("Exception::::", e)
|
||||
logger.info(f"[Voice Changer] Exception: {e}")
|
||||
logger.error(e)
|
||||
|
||||
@ -1,25 +1,9 @@
|
||||
# import sys
|
||||
# import os
|
||||
from dataclasses import asdict
|
||||
import numpy as np
|
||||
import torch
|
||||
import torchaudio
|
||||
from data.ModelSlot import RVCModelSlot
|
||||
|
||||
|
||||
# # avoiding parse arg error in RVC
|
||||
# sys.argv = ["MMVCServerSIO.py"]
|
||||
|
||||
# if sys.platform.startswith("darwin"):
|
||||
# baseDir = [x for x in sys.path if x.endswith("Contents/MacOS")]
|
||||
# if len(baseDir) != 1:
|
||||
# print("baseDir should be only one ", baseDir)
|
||||
# sys.exit()
|
||||
# modulePath = os.path.join(baseDir[0], "RVC")
|
||||
# sys.path.append(modulePath)
|
||||
# else:
|
||||
# sys.path.append("RVC")
|
||||
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
from voice_changer.RVC.RVCSettings import RVCSettings
|
||||
from voice_changer.RVC.embedder.EmbedderManager import EmbedderManager
|
||||
@ -31,18 +15,20 @@ from voice_changer.RVC.pipeline.PipelineGenerator import createPipeline
|
||||
from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
|
||||
from voice_changer.RVC.pipeline.Pipeline import Pipeline
|
||||
|
||||
from Exceptions import DeviceCannotSupportHalfPrecisionException
|
||||
from Exceptions import DeviceCannotSupportHalfPrecisionException, PipelineCreateException, PipelineNotInitializedException
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
class RVC(VoiceChangerModel):
|
||||
def __init__(self, params: VoiceChangerParams, slotInfo: RVCModelSlot):
|
||||
print("[Voice Changer] [RVC] Creating instance ")
|
||||
logger.info("[Voice Changer] [RVC] Creating instance ")
|
||||
self.deviceManager = DeviceManager.get_instance()
|
||||
EmbedderManager.initialize(params)
|
||||
PitchExtractorManager.initialize(params)
|
||||
self.settings = RVCSettings()
|
||||
self.params = params
|
||||
self.pitchExtractor = PitchExtractorManager.getPitchExtractor(self.settings.f0Detector, self.settings.gpu)
|
||||
# self.pitchExtractor = PitchExtractorManager.getPitchExtractor(self.settings.f0Detector, self.settings.gpu)
|
||||
|
||||
self.pipeline: Pipeline | None = None
|
||||
|
||||
@ -54,19 +40,23 @@ class RVC(VoiceChangerModel):
|
||||
# self.initialize()
|
||||
|
||||
def initialize(self):
|
||||
print("[Voice Changer] [RVC] Initializing... ")
|
||||
logger.info("[Voice Changer][RVC] Initializing... ")
|
||||
|
||||
# pipelineの生成
|
||||
self.pipeline = createPipeline(self.slotInfo, self.settings.gpu, self.settings.f0Detector)
|
||||
try:
|
||||
self.pipeline = createPipeline(self.slotInfo, self.settings.gpu, self.settings.f0Detector)
|
||||
except PipelineCreateException as e: # NOQA
|
||||
logger.error("[Voice Changer] pipeline create failed. check your model is valid.")
|
||||
return
|
||||
|
||||
# その他の設定
|
||||
self.settings.tran = self.slotInfo.defaultTune
|
||||
self.settings.indexRatio = self.slotInfo.defaultIndexRatio
|
||||
self.settings.protect = self.slotInfo.defaultProtect
|
||||
print("[Voice Changer] [RVC] Initializing... done")
|
||||
logger.info("[Voice Changer] [RVC] Initializing... done")
|
||||
|
||||
def update_settings(self, key: str, val: int | float | str):
|
||||
print("[Voice Changer][RVC]: update_settings", key, val)
|
||||
logger.info(f"[Voice Changer][RVC]: update_settings {key}:{val}")
|
||||
if key in self.settings.intData:
|
||||
setattr(self.settings, key, int(val))
|
||||
if key == "gpu":
|
||||
@ -88,6 +78,8 @@ class RVC(VoiceChangerModel):
|
||||
if self.pipeline is not None:
|
||||
pipelineInfo = self.pipeline.getPipelineInfo()
|
||||
data["pipelineInfo"] = pipelineInfo
|
||||
else:
|
||||
data["pipelineInfo"] = "None"
|
||||
return data
|
||||
|
||||
def get_processing_sampling_rate(self):
|
||||
@ -146,6 +138,9 @@ class RVC(VoiceChangerModel):
|
||||
return (self.audio_buffer, self.pitchf_buffer, self.feature_buffer, convertSize, vol, outSize)
|
||||
|
||||
def inference(self, data):
|
||||
if self.pipeline is None:
|
||||
logger.info("[Voice Changer] Pipeline is not initialized.111")
|
||||
raise PipelineNotInitializedException()
|
||||
audio = data[0]
|
||||
pitchf = data[1]
|
||||
feature = data[2]
|
||||
@ -192,7 +187,7 @@ class RVC(VoiceChangerModel):
|
||||
|
||||
return result
|
||||
except DeviceCannotSupportHalfPrecisionException as e: # NOQA
|
||||
print("[Device Manager] Device cannot support half precision. Fallback to float....")
|
||||
logger.warn("[Device Manager] Device cannot support half precision. Fallback to float....")
|
||||
self.deviceManager.setForceTensor(True)
|
||||
self.initialize()
|
||||
# raise e
|
||||
@ -222,7 +217,7 @@ class RVC(VoiceChangerModel):
|
||||
modelSlot = self.slotInfo
|
||||
|
||||
if modelSlot.isONNX:
|
||||
print("[Voice Changer] export2onnx, No pyTorch filepath.")
|
||||
logger.warn("[Voice Changer] export2onnx, No pyTorch filepath.")
|
||||
return {"status": "ng", "path": ""}
|
||||
|
||||
if self.pipeline is not None:
|
||||
|
||||
@ -20,7 +20,7 @@ from .config import TrainConfig
|
||||
matplotlib.use("Agg")
|
||||
logging.getLogger("matplotlib").setLevel(logging.WARNING)
|
||||
|
||||
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
# logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
logger = logging
|
||||
|
||||
|
||||
|
||||
@ -10,6 +10,7 @@ from Exceptions import (
|
||||
HalfPrecisionChangingException,
|
||||
NotEnoughDataExtimateF0,
|
||||
)
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
from voice_changer.RVC.embedder.Embedder import Embedder
|
||||
from voice_changer.RVC.inferencer.Inferencer import Inferencer
|
||||
@ -17,9 +18,8 @@ from voice_changer.RVC.inferencer.OnnxRVCInferencer import OnnxRVCInferencer
|
||||
from voice_changer.RVC.inferencer.OnnxRVCInferencerNono import OnnxRVCInferencerNono
|
||||
|
||||
from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger("vcclient")
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
class Pipeline(object):
|
||||
@ -49,9 +49,6 @@ class Pipeline(object):
|
||||
self.embedder = embedder
|
||||
self.inferencer = inferencer
|
||||
self.pitchExtractor = pitchExtractor
|
||||
print("GENERATE INFERENCER", self.inferencer)
|
||||
print("GENERATE EMBEDDER", self.embedder)
|
||||
print("GENERATE PITCH EXTRACTOR", self.pitchExtractor)
|
||||
logger.info("GENERATE INFERENCER" + str(self.inferencer))
|
||||
logger.info("GENERATE EMBEDDER" + str(self.embedder))
|
||||
logger.info("GENERATE PITCH EXTRACTOR" + str(self.pitchExtractor))
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
import os
|
||||
import traceback
|
||||
import faiss
|
||||
from Exceptions import PipelineCreateException
|
||||
from data.ModelSlot import RVCModelSlot
|
||||
|
||||
from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
|
||||
@ -20,6 +21,7 @@ def createPipeline(modelSlot: RVCModelSlot, gpu: int, f0Detector: str):
|
||||
except Exception as e:
|
||||
print("[Voice Changer] exception! loading inferencer", e)
|
||||
traceback.print_exc()
|
||||
raise PipelineCreateException("[Voice Changer] exception! loading inferencer")
|
||||
|
||||
# Embedder 生成
|
||||
try:
|
||||
@ -30,8 +32,9 @@ def createPipeline(modelSlot: RVCModelSlot, gpu: int, f0Detector: str):
|
||||
dev,
|
||||
)
|
||||
except Exception as e:
|
||||
print("[Voice Changer] exception! loading embedder", e, dev)
|
||||
print("[Voice Changer] exception! loading embedder", e, dev)
|
||||
traceback.print_exc()
|
||||
raise PipelineCreateException("[Voice Changer] exception! loading embedder")
|
||||
|
||||
# pitchExtractor
|
||||
pitchExtractor = PitchExtractorManager.getPitchExtractor(f0Detector, gpu)
|
||||
|
||||
@ -7,7 +7,7 @@ import numpy as np
|
||||
from sklearn.cluster import KMeans, MiniBatchKMeans
|
||||
import tqdm
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
#logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
import time
|
||||
|
||||
|
||||
@ -15,7 +15,7 @@ import torch
|
||||
|
||||
MATPLOTLIB_FLAG = False
|
||||
|
||||
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
# logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
|
||||
logger = logging
|
||||
|
||||
f0_bin = 256
|
||||
|
||||
@ -1,14 +1,13 @@
|
||||
import logging
|
||||
from typing import Any, Union, cast
|
||||
|
||||
from const import TMP_DIR
|
||||
import torch
|
||||
import os
|
||||
import traceback
|
||||
import numpy as np
|
||||
from dataclasses import dataclass, asdict, field
|
||||
import resampy
|
||||
import onnxruntime
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
from voice_changer.IORecorder import IORecorder
|
||||
|
||||
@ -22,13 +21,14 @@ from Exceptions import (
|
||||
NoModeLoadedException,
|
||||
NotEnoughDataExtimateF0,
|
||||
ONNXInputArgumentException,
|
||||
PipelineNotInitializedException,
|
||||
VoiceChangerIsNotSelectedException,
|
||||
)
|
||||
from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
|
||||
|
||||
STREAM_INPUT_FILE = os.path.join(TMP_DIR, "in.wav")
|
||||
STREAM_OUTPUT_FILE = os.path.join(TMP_DIR, "out.wav")
|
||||
logger = logging.getLogger("vcclient")
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
@dataclass
|
||||
@ -81,7 +81,6 @@ class VoiceChanger(VoiceChangerIF):
|
||||
self.mps_enabled: bool = getattr(torch.backends, "mps", None) is not None and torch.backends.mps.is_available()
|
||||
self.onnx_device = onnxruntime.get_device()
|
||||
|
||||
print(f"VoiceChanger Initialized (GPU_NUM(cuda):{self.gpu_num}, mps_enabled:{self.mps_enabled}, onnx_device:{self.onnx_device})")
|
||||
logger.info(f"VoiceChanger Initialized (GPU_NUM(cuda):{self.gpu_num}, mps_enabled:{self.mps_enabled}, onnx_device:{self.onnx_device})")
|
||||
|
||||
def setModel(self, model: Any):
|
||||
@ -104,7 +103,7 @@ class VoiceChanger(VoiceChangerIF):
|
||||
|
||||
def update_settings(self, key: str, val: Any):
|
||||
if self.voiceChanger is None:
|
||||
print("[Voice Changer] Voice Changer is not selected.")
|
||||
logger.warn("[Voice Changer] Voice Changer is not selected.")
|
||||
return self.get_info()
|
||||
|
||||
if key == "serverAudioStated" and val == 0:
|
||||
@ -168,8 +167,7 @@ class VoiceChanger(VoiceChangerIF):
|
||||
]
|
||||
)
|
||||
|
||||
print(f"Generated Strengths: for prev:{self.np_prev_strength.shape}, for cur:{self.np_cur_strength.shape}")
|
||||
|
||||
logger.info(f"Generated Strengths: for prev:{self.np_prev_strength.shape}, for cur:{self.np_cur_strength.shape}")
|
||||
# ひとつ前の結果とサイズが変わるため、記録は消去する。
|
||||
if hasattr(self, "np_prev_audio1") is True:
|
||||
delattr(self, "np_prev_audio1")
|
||||
@ -247,7 +245,7 @@ class VoiceChanger(VoiceChangerIF):
|
||||
|
||||
result = output_wav
|
||||
else:
|
||||
print("[Voice Changer] warming up... generating sola buffer.")
|
||||
logger.info("[Voice Changer] warming up... generating sola buffer.")
|
||||
result = np.zeros(4096).astype(np.int16)
|
||||
|
||||
if hasattr(self, "sola_buffer") is True and sola_offset < sola_search_frame:
|
||||
@ -304,29 +302,31 @@ class VoiceChanger(VoiceChangerIF):
|
||||
return outputData, perf
|
||||
|
||||
except NoModeLoadedException as e:
|
||||
print("[Voice Changer] [Exception]", e)
|
||||
logger.warn(f"[Voice Changer] [Exception], {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except ONNXInputArgumentException as e:
|
||||
print("[Voice Changer] [Exception] onnx are waiting valid input.", e)
|
||||
logger.warn(f"[Voice Changer] [Exception] onnx are waiting valid input., {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except HalfPrecisionChangingException:
|
||||
print("[Voice Changer] Switching model configuration....")
|
||||
logger.warn("[Voice Changer] Switching model configuration....")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except NotEnoughDataExtimateF0:
|
||||
print("[Voice Changer] warming up... waiting more data.")
|
||||
logger.warn("[Voice Changer] warming up... waiting more data.")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except DeviceChangingException as e:
|
||||
print("[Voice Changer] embedder:", e)
|
||||
logger.warn(f"[Voice Changer] embedder: {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except VoiceChangerIsNotSelectedException:
|
||||
print("[Voice Changer] Voice Changer is not selected. Wait a bit and if there is no improvement, please re-select vc.")
|
||||
logger.warn("[Voice Changer] Voice Changer is not selected. Wait a bit and if there is no improvement, please re-select vc.")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except DeviceCannotSupportHalfPrecisionException:
|
||||
# RVC.pyでfallback処理をするので、ここはダミーデータ返すだけ。
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except PipelineNotInitializedException:
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except Exception as e:
|
||||
print("[Voice Changer] VC PROCESSING EXCEPTION!!!", e)
|
||||
print(traceback.format_exc())
|
||||
logger.warn(f"[Voice Changer] VC PROCESSING EXCEPTION!!! {e}")
|
||||
logger.exception(e)
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
|
||||
def export2onnx(self):
|
||||
@ -336,7 +336,7 @@ class VoiceChanger(VoiceChangerIF):
|
||||
|
||||
def merge_models(self, request: str):
|
||||
if self.voiceChanger is None:
|
||||
print("[Voice Changer] Voice Changer is not selected.")
|
||||
logger.info("[Voice Changer] Voice Changer is not selected.")
|
||||
return
|
||||
self.voiceChanger.merge_models(request)
|
||||
return self.get_info()
|
||||
@ -348,7 +348,7 @@ PRINT_CONVERT_PROCESSING: bool = False
|
||||
|
||||
def print_convert_processing(mess: str):
|
||||
if PRINT_CONVERT_PROCESSING is True:
|
||||
print(mess)
|
||||
logger.info(mess)
|
||||
|
||||
|
||||
def pad_array(arr: AudioInOut, target_length: int):
|
||||
|
||||
@ -5,6 +5,7 @@ import shutil
|
||||
import threading
|
||||
import numpy as np
|
||||
from downloader.SampleDownloader import downloadSample, getSampleInfos
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
from voice_changer.Local.ServerDevice import ServerDevice, ServerDeviceCallbacks
|
||||
from voice_changer.ModelSlotManager import ModelSlotManager
|
||||
from voice_changer.RVC.RVCModelMerger import RVCModelMerger
|
||||
@ -23,6 +24,9 @@ from typing import Callable
|
||||
from typing import Any
|
||||
|
||||
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
@dataclass()
|
||||
class GPUInfo:
|
||||
id: int
|
||||
@ -123,7 +127,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
def loadModel(self, params: LoadModelParams):
|
||||
if params.isSampleMode:
|
||||
# サンプルダウンロード
|
||||
print("[Voice Changer] sample download....", params)
|
||||
logger.info(f"[Voice Changer] sample download...., {params}")
|
||||
downloadSample(self.params.sample_mode, params.sampleId, self.params.model_dir, params.slot, params.params)
|
||||
self.modelSlotManager.getAllSlotInfo(reload=True)
|
||||
info = {"status": "OK"}
|
||||
@ -132,7 +136,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
# アップローダ
|
||||
# ファイルをslotにコピー
|
||||
for file in params.files:
|
||||
print("FILE", file)
|
||||
logger.info(f"FILE: {file}")
|
||||
srcPath = os.path.join(UPLOAD_DIR, file.dir, file.name)
|
||||
dstDir = os.path.join(
|
||||
self.params.model_dir,
|
||||
@ -141,7 +145,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
)
|
||||
dstPath = os.path.join(dstDir, file.name)
|
||||
os.makedirs(dstDir, exist_ok=True)
|
||||
print(f"move to {srcPath} -> {dstPath}")
|
||||
logger.info(f"move to {srcPath} -> {dstPath}")
|
||||
shutil.move(srcPath, dstPath)
|
||||
file.name = dstPath
|
||||
|
||||
@ -176,7 +180,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
|
||||
slotInfo = DiffusionSVCModelSlotGenerator.loadModel(params)
|
||||
self.modelSlotManager.save_model_slot(params.slot, slotInfo)
|
||||
print("params", params)
|
||||
logger.info(f"params, {params}")
|
||||
|
||||
def get_info(self):
|
||||
data = asdict(self.settings)
|
||||
@ -206,52 +210,52 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
def generateVoiceChanger(self, val: int):
|
||||
slotInfo = self.modelSlotManager.get_slot_info(val)
|
||||
if slotInfo is None:
|
||||
print(f"[Voice Changer] model slot is not found {val}")
|
||||
logger.info(f"[Voice Changer] model slot is not found {val}")
|
||||
return
|
||||
elif slotInfo.voiceChangerType == "RVC":
|
||||
print("................RVC")
|
||||
logger.info("................RVC")
|
||||
from voice_changer.RVC.RVC import RVC
|
||||
|
||||
self.voiceChangerModel = RVC(self.params, slotInfo)
|
||||
self.voiceChanger = VoiceChanger(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
elif slotInfo.voiceChangerType == "MMVCv13":
|
||||
print("................MMVCv13")
|
||||
logger.info("................MMVCv13")
|
||||
from voice_changer.MMVCv13.MMVCv13 import MMVCv13
|
||||
|
||||
self.voiceChangerModel = MMVCv13(slotInfo)
|
||||
self.voiceChanger = VoiceChanger(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
elif slotInfo.voiceChangerType == "MMVCv15":
|
||||
print("................MMVCv15")
|
||||
logger.info("................MMVCv15")
|
||||
from voice_changer.MMVCv15.MMVCv15 import MMVCv15
|
||||
|
||||
self.voiceChangerModel = MMVCv15(slotInfo)
|
||||
self.voiceChanger = VoiceChanger(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
elif slotInfo.voiceChangerType == "so-vits-svc-40":
|
||||
print("................so-vits-svc-40")
|
||||
logger.info("................so-vits-svc-40")
|
||||
from voice_changer.SoVitsSvc40.SoVitsSvc40 import SoVitsSvc40
|
||||
|
||||
self.voiceChangerModel = SoVitsSvc40(self.params, slotInfo)
|
||||
self.voiceChanger = VoiceChanger(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
elif slotInfo.voiceChangerType == "DDSP-SVC":
|
||||
print("................DDSP-SVC")
|
||||
logger.info("................DDSP-SVC")
|
||||
from voice_changer.DDSP_SVC.DDSP_SVC import DDSP_SVC
|
||||
|
||||
self.voiceChangerModel = DDSP_SVC(self.params, slotInfo)
|
||||
self.voiceChanger = VoiceChanger(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
elif slotInfo.voiceChangerType == "Diffusion-SVC":
|
||||
print("................Diffusion-SVC")
|
||||
logger.info("................Diffusion-SVC")
|
||||
from voice_changer.DiffusionSVC.DiffusionSVC import DiffusionSVC
|
||||
|
||||
self.voiceChangerModel = DiffusionSVC(self.params, slotInfo)
|
||||
self.voiceChanger = VoiceChangerV2(self.params)
|
||||
self.voiceChanger.setModel(self.voiceChangerModel)
|
||||
else:
|
||||
print(f"[Voice Changer] unknown voice changer model: {slotInfo.voiceChangerType}")
|
||||
logger.info(f"[Voice Changer] unknown voice changer model: {slotInfo.voiceChangerType}")
|
||||
if hasattr(self, "voiceChangerModel"):
|
||||
del self.voiceChangerModel
|
||||
return
|
||||
@ -263,7 +267,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
newVal = int(val)
|
||||
if key == "modelSlotIndex":
|
||||
newVal = newVal % 1000
|
||||
print(f"[Voice Changer] model slot is changed {self.settings.modelSlotIndex} -> {newVal}")
|
||||
logger.info(f"[Voice Changer] model slot is changed {self.settings.modelSlotIndex} -> {newVal}")
|
||||
self.generateVoiceChanger(newVal)
|
||||
# キャッシュ設定の反映
|
||||
for k, v in self.stored_setting.items():
|
||||
@ -282,7 +286,7 @@ class VoiceChangerManager(ServerDeviceCallbacks):
|
||||
if hasattr(self, "voiceChanger") is True:
|
||||
return self.voiceChanger.on_request(receivedData)
|
||||
else:
|
||||
print("Voice Change is not loaded. Did you load a correct model?")
|
||||
logger.info("Voice Change is not loaded. Did you load a correct model?")
|
||||
return np.zeros(1).astype(np.int16), []
|
||||
|
||||
def export2onnx(self):
|
||||
|
||||
@ -9,16 +9,15 @@
|
||||
|
||||
'''
|
||||
|
||||
import logging
|
||||
from typing import Any, Union
|
||||
|
||||
from const import TMP_DIR
|
||||
import torch
|
||||
import os
|
||||
import traceback
|
||||
import numpy as np
|
||||
from dataclasses import dataclass, asdict, field
|
||||
import onnxruntime
|
||||
from mods.log_control import VoiceChangaerLogger
|
||||
|
||||
from voice_changer.IORecorder import IORecorder
|
||||
|
||||
@ -38,7 +37,7 @@ from voice_changer.utils.VoiceChangerParams import VoiceChangerParams
|
||||
|
||||
STREAM_INPUT_FILE = os.path.join(TMP_DIR, "in.wav")
|
||||
STREAM_OUTPUT_FILE = os.path.join(TMP_DIR, "out.wav")
|
||||
logger = logging.getLogger("vcclient")
|
||||
logger = VoiceChangaerLogger.get_instance().getLogger()
|
||||
|
||||
|
||||
@dataclass
|
||||
@ -91,7 +90,6 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
self.mps_enabled: bool = getattr(torch.backends, "mps", None) is not None and torch.backends.mps.is_available()
|
||||
self.onnx_device = onnxruntime.get_device()
|
||||
|
||||
print(f"VoiceChangerV2 Initialized (GPU_NUM(cuda):{self.gpu_num}, mps_enabled:{self.mps_enabled}, onnx_device:{self.onnx_device})")
|
||||
logger.info(f"VoiceChangerV2 Initialized (GPU_NUM(cuda):{self.gpu_num}, mps_enabled:{self.mps_enabled}, onnx_device:{self.onnx_device})")
|
||||
|
||||
def setModel(self, model: VoiceChangerModel):
|
||||
@ -117,7 +115,7 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
|
||||
def update_settings(self, key: str, val: Any):
|
||||
if self.voiceChanger is None:
|
||||
print("[Voice Changer] Voice Changer is not selected.")
|
||||
logger.warn("[Voice Changer] Voice Changer is not selected.")
|
||||
return self.get_info()
|
||||
|
||||
if key == "serverAudioStated" and val == 0:
|
||||
@ -183,7 +181,7 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
]
|
||||
)
|
||||
|
||||
print(f"Generated Strengths: for prev:{self.np_prev_strength.shape}, for cur:{self.np_cur_strength.shape}")
|
||||
logger.info(f"Generated Strengths: for prev:{self.np_prev_strength.shape}, for cur:{self.np_cur_strength.shape}")
|
||||
|
||||
# ひとつ前の結果とサイズが変わるため、記録は消去する。
|
||||
if hasattr(self, "np_prev_audio1") is True:
|
||||
@ -243,7 +241,7 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
|
||||
result = output_wav
|
||||
else:
|
||||
print("[Voice Changer] warming up... generating sola buffer.")
|
||||
logger.info("[Voice Changer] warming up... generating sola buffer.")
|
||||
result = np.zeros(4096).astype(np.int16)
|
||||
|
||||
if hasattr(self, "sola_buffer") is True and sola_offset < sola_search_frame:
|
||||
@ -281,29 +279,29 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
return outputData, perf
|
||||
|
||||
except NoModeLoadedException as e:
|
||||
print("[Voice Changer] [Exception]", e)
|
||||
logger.warn(f"[Voice Changer] [Exception], {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except ONNXInputArgumentException as e:
|
||||
print("[Voice Changer] [Exception] onnx are waiting valid input.", e)
|
||||
logger.warn(f"[Voice Changer] [Exception] onnx are waiting valid input., {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except HalfPrecisionChangingException:
|
||||
print("[Voice Changer] Switching model configuration....")
|
||||
logger.warn("[Voice Changer] Switching model configuration....")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except NotEnoughDataExtimateF0:
|
||||
print("[Voice Changer] warming up... waiting more data.")
|
||||
logger.warn("[Voice Changer] warming up... waiting more data.")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except DeviceChangingException as e:
|
||||
print("[Voice Changer] embedder:", e)
|
||||
logger.warn(f"[Voice Changer] embedder: {e}")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except VoiceChangerIsNotSelectedException:
|
||||
print("[Voice Changer] Voice Changer is not selected. Wait a bit and if there is no improvement, please re-select vc.")
|
||||
logger.warn("[Voice Changer] Voice Changer is not selected. Wait a bit and if there is no improvement, please re-select vc.")
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except DeviceCannotSupportHalfPrecisionException:
|
||||
# RVC.pyでfallback処理をするので、ここはダミーデータ返すだけ。
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
except Exception as e:
|
||||
print("[Voice Changer] VC PROCESSING EXCEPTION!!!", e)
|
||||
print(traceback.format_exc())
|
||||
logger.warn(f"[Voice Changer] VC PROCESSING EXCEPTION!!! {e}")
|
||||
logger.exception(e)
|
||||
return np.zeros(1).astype(np.int16), [0, 0, 0]
|
||||
|
||||
def export2onnx(self):
|
||||
@ -313,7 +311,7 @@ class VoiceChangerV2(VoiceChangerIF):
|
||||
|
||||
def merge_models(self, request: str):
|
||||
if self.voiceChanger is None:
|
||||
print("[Voice Changer] Voice Changer is not selected.")
|
||||
logger.info("[Voice Changer] Voice Changer is not selected.")
|
||||
return
|
||||
self.voiceChanger.merge_models(request)
|
||||
return self.get_info()
|
||||
@ -325,7 +323,7 @@ PRINT_CONVERT_PROCESSING: bool = False
|
||||
|
||||
def print_convert_processing(mess: str):
|
||||
if PRINT_CONVERT_PROCESSING is True:
|
||||
print(mess)
|
||||
logger.info(mess)
|
||||
|
||||
|
||||
def pad_array(arr: AudioInOut, target_length: int):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user