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| import os | |
| import sys | |
| import torch | |
| JSON_AS_ASCII = False | |
| MAX_CONTENT_LENGTH = 5242880 | |
| # Flask debug mode | |
| DEBUG = False | |
| # Server port | |
| PORT = 23456 | |
| # Absolute path of vits-simple-api | |
| ABS_PATH = os.path.dirname(os.path.realpath(__file__)) | |
| # Upload path | |
| UPLOAD_FOLDER = ABS_PATH + "/upload" | |
| # Cahce path | |
| CACHE_PATH = ABS_PATH + "/cache" | |
| # Logs path | |
| LOGS_PATH = ABS_PATH + "/logs" | |
| # Set the number of backup log files to keep. | |
| LOGS_BACKUPCOUNT = 30 | |
| # If CLEAN_INTERVAL_SECONDS <= 0, the cleaning task will not be executed. | |
| CLEAN_INTERVAL_SECONDS = 3600 | |
| # save audio to CACHE_PATH | |
| SAVE_AUDIO = False | |
| # zh ja ko en... If it is empty, it will be read based on the text_cleaners specified in the config.json. | |
| LANGUAGE_AUTOMATIC_DETECT = [] | |
| # Set to True to enable API Key authentication | |
| API_KEY_ENABLED = False | |
| # API_KEY is required for authentication | |
| API_KEY = "api-key" | |
| # logging_level:DEBUG/INFO/WARNING/ERROR/CRITICAL | |
| LOGGING_LEVEL = "DEBUG" | |
| # Language identification library. Optional fastlid, langid | |
| LANGUAGE_IDENTIFICATION_LIBRARY = "langid" | |
| # To use the english_cleaner, you need to install espeak and provide the path of libespeak-ng.dll as input here. | |
| # If ESPEAK_LIBRARY is set to empty, it will be read from the environment variable. | |
| # For windows : "C:/Program Files/eSpeak NG/libespeak-ng.dll" | |
| ESPEAK_LIBRARY = "" | |
| # Fill in the model path here | |
| MODEL_LIST = [ | |
| # VITS | |
| # [ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/1374_epochs.pth", ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/config.json"], | |
| # [ABS_PATH + "/Model/Zero_no_tsukaima/1158_epochs.pth", ABS_PATH + "/Model/Zero_no_tsukaima/config.json"], | |
| # [ABS_PATH + "/Model/g/G_953000.pth", ABS_PATH + "/Model/g/config.json"], | |
| # [ABS_PATH + "/Model/vits_chinese/vits_bert_model.pth", ABS_PATH + "/Model/vits_chinese/bert_vits.json"], | |
| # HuBert-VITS (Need to configure HUBERT_SOFT_MODEL) | |
| # [ABS_PATH + "/Model/louise/360_epochs.pth", ABS_PATH + "/Model/louise/config.json"], | |
| # W2V2-VITS (Need to configure DIMENSIONAL_EMOTION_NPY) | |
| # [ABS_PATH + "/Model/w2v2-vits/1026_epochs.pth", ABS_PATH + "/Model/w2v2-vits/config.json"], | |
| # Bert-VITS2 | |
| # [ABS_PATH + "/Model/bert_vits2/G_9000.pth", ABS_PATH + "/Model/bert_vits2/config.json"], | |
| ] | |
| # hubert-vits: hubert soft model | |
| HUBERT_SOFT_MODEL = ABS_PATH + "/Model/hubert-soft-0d54a1f4.pt" | |
| # w2v2-vits: Dimensional emotion npy file | |
| # load single npy: ABS_PATH+"/all_emotions.npy | |
| # load mutiple npy: [ABS_PATH + "/emotions1.npy", ABS_PATH + "/emotions2.npy"] | |
| # load mutiple npy from folder: ABS_PATH + "/Model/npy" | |
| DIMENSIONAL_EMOTION_NPY = ABS_PATH + "/Model/npy" | |
| # w2v2-vits: Need to have both `model.onnx` and `model.yaml` files in the same path. | |
| # DIMENSIONAL_EMOTION_MODEL = ABS_PATH + "/Model/model.yaml" | |
| DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| """ | |
| Default parameter | |
| """ | |
| ID = 0 | |
| FORMAT = "wav" | |
| LANG = "AUTO" | |
| LENGTH = 1 | |
| NOISE = 0.33 | |
| NOISEW = 0.4 | |
| # 长文本分段阈值，max<=0表示不分段. | |
| # Batch processing threshold. Text will not be processed in batches if max<=0 | |
| MAX = 50 | |
| # Bert_VITS2 | |
| SDP_RATIO = 0.2 | |