o j@sddlZddlZddlmZddlZddlmZddlmZddlmZddl m Z ddl m Z ddl mZ        d0d d Zed krejd edZejdedddejdedddejdedddejdedddejdedddejddd dd ejd!ed"d dejd#d$d dd ejd%ed&ddejd'ed(ddejd)ed*ddejd+ed,ddejd-ed.ddeZeejejejejejejejejej ej!ej"ej#ej$d/ dSdS)1N)RawTextHelpFormatter)tqdm) load_config)BaseDatasetConfig)load_tts_samples) save_file)SpeakerManagerFc Cstjo| } |durt|}t|j| d\}}n#t}||_||_||_ | dur.| |_ | dur5| |_ t|| d\}}|durE|}n||}t |||| d}|j j}|dur_|r_|j}ni}t|D]=}||}|d}|d}||vr~|||d<qe|dur||jvr||}n||}i||<|||d<|||d<qe|rtj |rtj |d}n|}tj |dkrtjtj |d d t||td |dSdS) N) eval_split)encoder_model_pathencoder_config_pathd_vectors_file_pathuse_cuda audio_fileaudio_unique_namename embedding speakers.pthT)exist_okzSpeaker embeddings saved at:)torchcuda is_availablerrdatasetsr formatter dataset_namepathmeta_file_train meta_file_valrencoder_configclass_name_key embeddingsrclip_idsget_embedding_by_clipcompute_embedding_from_cliposisdirjoindirnamemakedirsrprint) model_path config_path output_pathold_speakers_file old_appendconfig_dataset_pathformatter_namer dataset_pathrr disable_cudano_evalr c_datasetmeta_data_trainmeta_data_evalsamplesencoder_managerrspeaker_mappingfields class_namer embedding_keyembeddmapping_file_pathr?M/home/kuhnn/.local/lib/python3.10/site-packages/TTS/bin/compute_embeddings.pycompute_embeddingss`        rA__main__a~Compute embedding vectors for each audio file in a dataset and store them keyed by `{dataset_name}#{file_path}` in a .pth file Example runs: python TTS/bin/compute_embeddings.py --model_path speaker_encoder_model.pth --config_path speaker_encoder_config.json --config_dataset_path dataset_config.json python TTS/bin/compute_embeddings.py --model_path speaker_encoder_model.pth --config_path speaker_encoder_config.json --formatter_name coqui --dataset_path /path/to/vctk/dataset --dataset_name my_vctk --meta_file_train /path/to/vctk/metafile_train.csv --meta_file_val /path/to/vctk/metafile_eval.csv ) descriptionformatter_classz --model_pathzKPath to model checkpoint file. It defaults to the released speaker encoder.zXhttps://github.com/coqui-ai/TTS/releases/download/speaker_encoder_model/model_se.pth.tar)typehelpdefaultz --config_pathzNPath to model config file. It defaults to the released speaker encoder config.zVhttps://github.com/coqui-ai/TTS/releases/download/speaker_encoder_model/config_se.jsonz--config_dataset_pathz~Path to dataset config file. You either need to provide this or `formatter_name`, `dataset_name` and `dataset_path` arguments.z --output_pathz%Path for output `pth` or `json` file.rz --old_fileztThe old existing embedding file, from which the embeddings will be directly loaded for already computed audio clips.z --old_appendz~Append new audio clip embeddings to the old embedding file, generate a new non-duplicated merged embedding file. Default False store_true)rFrGactionz--disable_cudazFlag to disable cuda.z --no_evalz#Do not compute eval?. Default Falsez--formatter_namezVName of the formatter to use. You either need to provide this or `config_dataset_path`z--dataset_namezTName of the dataset to use. You either need to provide this or `config_dataset_path`z--dataset_pathzMPath to the dataset. You either need to provide this or `config_dataset_path`z--meta_file_trainzPath to the train meta file. If not set, dataset formatter uses the default metafile if it is defined in the formatter. You either need to provide this or `config_dataset_path`z--meta_file_valzPath to the evaluation meta file. If not set, dataset formatter uses the default metafile if it is defined in the formatter. You either need to provide this or `config_dataset_path`) r-r.r/r0rr1rrr2r3) NFNNNNNNFF)%argparser$rrr TTS.configrTTS.config.shared_configsrTTS.tts.datasetsrTTS.tts.utils.managersrTTS.tts.utils.speakersrrA__name__ArgumentParserparser add_argumentstrbool parse_argsargsr*r+r,old_filer.r/r0rr1rrr2r3r?r?r?r@s        W