198 lines
7.4 KiB
Python
198 lines
7.4 KiB
Python
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import argparse
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import os
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from argparse import RawTextHelpFormatter
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import torch
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from tqdm import tqdm
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from TTS.config import load_config
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from TTS.config.shared_configs import BaseDatasetConfig
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from TTS.tts.datasets import load_tts_samples
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from TTS.tts.utils.managers import save_file
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from TTS.tts.utils.speakers import SpeakerManager
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def compute_embeddings(
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model_path,
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config_path,
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output_path,
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old_speakers_file=None,
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old_append=False,
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config_dataset_path=None,
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formatter_name=None,
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dataset_name=None,
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dataset_path=None,
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meta_file_train=None,
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meta_file_val=None,
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disable_cuda=False,
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no_eval=False,
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):
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use_cuda = torch.cuda.is_available() and not disable_cuda
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if config_dataset_path is not None:
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c_dataset = load_config(config_dataset_path)
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meta_data_train, meta_data_eval = load_tts_samples(c_dataset.datasets, eval_split=not no_eval)
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else:
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c_dataset = BaseDatasetConfig()
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c_dataset.formatter = formatter_name
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c_dataset.dataset_name = dataset_name
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c_dataset.path = dataset_path
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if meta_file_train is not None:
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c_dataset.meta_file_train = meta_file_train
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if meta_file_val is not None:
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c_dataset.meta_file_val = meta_file_val
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meta_data_train, meta_data_eval = load_tts_samples(c_dataset, eval_split=not no_eval)
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if meta_data_eval is None:
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samples = meta_data_train
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else:
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samples = meta_data_train + meta_data_eval
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encoder_manager = SpeakerManager(
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encoder_model_path=model_path,
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encoder_config_path=config_path,
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d_vectors_file_path=old_speakers_file,
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use_cuda=use_cuda,
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)
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class_name_key = encoder_manager.encoder_config.class_name_key
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# compute speaker embeddings
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if old_speakers_file is not None and old_append:
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speaker_mapping = encoder_manager.embeddings
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else:
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speaker_mapping = {}
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for fields in tqdm(samples):
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class_name = fields[class_name_key]
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audio_file = fields["audio_file"]
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embedding_key = fields["audio_unique_name"]
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# Only update the speaker name when the embedding is already in the old file.
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if embedding_key in speaker_mapping:
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speaker_mapping[embedding_key]["name"] = class_name
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continue
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if old_speakers_file is not None and embedding_key in encoder_manager.clip_ids:
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# get the embedding from the old file
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embedd = encoder_manager.get_embedding_by_clip(embedding_key)
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else:
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# extract the embedding
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embedd = encoder_manager.compute_embedding_from_clip(audio_file)
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# create speaker_mapping if target dataset is defined
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speaker_mapping[embedding_key] = {}
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speaker_mapping[embedding_key]["name"] = class_name
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speaker_mapping[embedding_key]["embedding"] = embedd
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if speaker_mapping:
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# save speaker_mapping if target dataset is defined
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if os.path.isdir(output_path):
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mapping_file_path = os.path.join(output_path, "speakers.pth")
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else:
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mapping_file_path = output_path
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if os.path.dirname(mapping_file_path) != "":
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os.makedirs(os.path.dirname(mapping_file_path), exist_ok=True)
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save_file(speaker_mapping, mapping_file_path)
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print("Speaker embeddings saved at:", mapping_file_path)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="""Compute embedding vectors for each audio file in a dataset and store them keyed by `{dataset_name}#{file_path}` in a .pth file\n\n"""
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"""
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Example runs:
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python TTS/bin/compute_embeddings.py --model_path speaker_encoder_model.pth --config_path speaker_encoder_config.json --config_dataset_path dataset_config.json
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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
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""",
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formatter_class=RawTextHelpFormatter,
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)
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parser.add_argument(
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"--model_path",
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type=str,
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help="Path to model checkpoint file. It defaults to the released speaker encoder.",
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default="https://github.com/coqui-ai/TTS/releases/download/speaker_encoder_model/model_se.pth.tar",
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)
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parser.add_argument(
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"--config_path",
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type=str,
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help="Path to model config file. It defaults to the released speaker encoder config.",
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default="https://github.com/coqui-ai/TTS/releases/download/speaker_encoder_model/config_se.json",
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)
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parser.add_argument(
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"--config_dataset_path",
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type=str,
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help="Path to dataset config file. You either need to provide this or `formatter_name`, `dataset_name` and `dataset_path` arguments.",
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default=None,
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)
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parser.add_argument(
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"--output_path",
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type=str,
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help="Path for output `pth` or `json` file.",
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default="speakers.pth",
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)
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parser.add_argument(
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"--old_file",
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type=str,
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help="The old existing embedding file, from which the embeddings will be directly loaded for already computed audio clips.",
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default=None,
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)
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parser.add_argument(
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"--old_append",
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help="Append new audio clip embeddings to the old embedding file, generate a new non-duplicated merged embedding file. Default False",
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default=False,
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action="store_true",
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)
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parser.add_argument("--disable_cuda", type=bool, help="Flag to disable cuda.", default=False)
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parser.add_argument("--no_eval", help="Do not compute eval?. Default False", default=False, action="store_true")
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parser.add_argument(
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"--formatter_name",
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type=str,
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help="Name of the formatter to use. You either need to provide this or `config_dataset_path`",
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default=None,
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)
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parser.add_argument(
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"--dataset_name",
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type=str,
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help="Name of the dataset to use. You either need to provide this or `config_dataset_path`",
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default=None,
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)
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parser.add_argument(
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"--dataset_path",
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type=str,
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help="Path to the dataset. You either need to provide this or `config_dataset_path`",
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default=None,
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)
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parser.add_argument(
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"--meta_file_train",
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type=str,
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help="Path 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`",
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default=None,
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)
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parser.add_argument(
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"--meta_file_val",
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type=str,
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help="Path 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`",
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default=None,
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)
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args = parser.parse_args()
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compute_embeddings(
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args.model_path,
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args.config_path,
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args.output_path,
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old_speakers_file=args.old_file,
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old_append=args.old_append,
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config_dataset_path=args.config_dataset_path,
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formatter_name=args.formatter_name,
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dataset_name=args.dataset_name,
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dataset_path=args.dataset_path,
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meta_file_train=args.meta_file_train,
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meta_file_val=args.meta_file_val,
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disable_cuda=args.disable_cuda,
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no_eval=args.no_eval,
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)
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