100 lines
4.0 KiB
Python
100 lines
4.0 KiB
Python
import os
|
|
from dataclasses import dataclass, field
|
|
|
|
from coqpit import Coqpit
|
|
from trainer import TrainerArgs, get_last_checkpoint
|
|
from trainer.io import copy_model_files
|
|
from trainer.logging import logger_factory
|
|
from trainer.logging.console_logger import ConsoleLogger
|
|
|
|
from TTS.config import load_config, register_config
|
|
from TTS.tts.utils.text.characters import parse_symbols
|
|
from TTS.utils.generic_utils import get_experiment_folder_path, get_git_branch
|
|
|
|
|
|
@dataclass
|
|
class TrainArgs(TrainerArgs):
|
|
config_path: str = field(default=None, metadata={"help": "Path to the config file."})
|
|
|
|
|
|
def getarguments():
|
|
train_config = TrainArgs()
|
|
parser = train_config.init_argparse(arg_prefix="")
|
|
return parser
|
|
|
|
|
|
def process_args(args, config=None):
|
|
"""Process parsed comand line arguments and initialize the config if not provided.
|
|
Args:
|
|
args (argparse.Namespace or dict like): Parsed input arguments.
|
|
config (Coqpit): Model config. If none, it is generated from `args`. Defaults to None.
|
|
Returns:
|
|
c (TTS.utils.io.AttrDict): Config paramaters.
|
|
out_path (str): Path to save models and logging.
|
|
audio_path (str): Path to save generated test audios.
|
|
c_logger (TTS.utils.console_logger.ConsoleLogger): Class that does
|
|
logging to the console.
|
|
dashboard_logger (WandbLogger or TensorboardLogger): Class that does the dashboard Logging
|
|
TODO:
|
|
- Interactive config definition.
|
|
"""
|
|
if isinstance(args, tuple):
|
|
args, coqpit_overrides = args
|
|
if args.continue_path:
|
|
# continue a previous training from its output folder
|
|
experiment_path = args.continue_path
|
|
args.config_path = os.path.join(args.continue_path, "config.json")
|
|
args.restore_path, best_model = get_last_checkpoint(args.continue_path)
|
|
if not args.best_path:
|
|
args.best_path = best_model
|
|
# init config if not already defined
|
|
if config is None:
|
|
if args.config_path:
|
|
# init from a file
|
|
config = load_config(args.config_path)
|
|
else:
|
|
# init from console args
|
|
from TTS.config.shared_configs import BaseTrainingConfig # pylint: disable=import-outside-toplevel
|
|
|
|
config_base = BaseTrainingConfig()
|
|
config_base.parse_known_args(coqpit_overrides)
|
|
config = register_config(config_base.model)()
|
|
# override values from command-line args
|
|
config.parse_known_args(coqpit_overrides, relaxed_parser=True)
|
|
experiment_path = args.continue_path
|
|
if not experiment_path:
|
|
experiment_path = get_experiment_folder_path(config.output_path, config.run_name)
|
|
audio_path = os.path.join(experiment_path, "test_audios")
|
|
config.output_log_path = experiment_path
|
|
# setup rank 0 process in distributed training
|
|
dashboard_logger = None
|
|
if args.rank == 0:
|
|
new_fields = {}
|
|
if args.restore_path:
|
|
new_fields["restore_path"] = args.restore_path
|
|
new_fields["github_branch"] = get_git_branch()
|
|
# if model characters are not set in the config file
|
|
# save the default set to the config file for future
|
|
# compatibility.
|
|
if config.has("characters") and config.characters is None:
|
|
used_characters = parse_symbols()
|
|
new_fields["characters"] = used_characters
|
|
copy_model_files(config, experiment_path, new_fields)
|
|
dashboard_logger = logger_factory(config, experiment_path)
|
|
c_logger = ConsoleLogger()
|
|
return config, experiment_path, audio_path, c_logger, dashboard_logger
|
|
|
|
|
|
def init_arguments():
|
|
train_config = TrainArgs()
|
|
parser = train_config.init_argparse(arg_prefix="")
|
|
return parser
|
|
|
|
|
|
def init_training(config: Coqpit = None):
|
|
"""Initialization of a training run."""
|
|
parser = init_arguments()
|
|
args = parser.parse_known_args()
|
|
config, OUT_PATH, AUDIO_PATH, c_logger, dashboard_logger = process_args(args, config)
|
|
return args[0], config, OUT_PATH, AUDIO_PATH, c_logger, dashboard_logger
|