def config_main(args, unknown_args):
"""Yaml config catalyst-dl run entry point."""
args, config = parse_args_uargs(args, unknown_args)
set_global_seed(args.seed)
prepare_cudnn(args.deterministic, args.benchmark)
runner: ConfigRunner = get_config_runner(expdir=args.expdir, config=config)
if get_rank() <= 0:
dump_environment(logdir=runner.logdir, config=config, configs_path=args.configs)
dump_code(expdir=args.expdir, logdir=runner.logdir)
runner.run()
def objective(trial: optuna.trial):
trial, trial_config = _process_trial_config(trial, config.copy())
runner: ConfigRunner = get_config_runner(expdir=Path(args.expdir), config=trial_config)
# @TODO: here we need better solution.
runner._trial = trial # noqa: WPS437
if get_rank() <= 0:
dump_environment(logdir=runner.logdir, config=config, configs_path=args.configs)
dump_code(expdir=args.expdir, logdir=runner.logdir)
runner.run()
return trial.best_score
def objective(trial: optuna.trial):
trial, trial_config = _process_trial_config(trial, config.copy())
experiment, runner, trial_config = prepare_config_api_components(
expdir=expdir, config=trial_config)
# @TODO: here we need better solution.
experiment._trial = trial # noqa: WPS437
if experiment.logdir is not None and get_rank() <= 0:
dump_environment(trial_config, experiment.logdir, args.configs)
dump_code(args.expdir, experiment.logdir)
runner.run_experiment(experiment)
return runner.best_valid_metrics[runner.main_metric]
def main_worker(cfg: DictConfig):
set_global_seed(cfg.args.seed)
prepare_cudnn(cfg.args.deterministic, cfg.args.benchmark)
import_module(hydra.utils.to_absolute_path(cfg.args.expdir))
experiment = hydra.utils.instantiate(cfg.experiment, cfg=cfg)
runner = hydra.utils.instantiate(cfg.runner)
if experiment.logdir is not None and get_rank() <= 0:
dump_environment(cfg, experiment.logdir)
dump_code(
hydra.utils.to_absolute_path(cfg.args.expdir), experiment.logdir
)
runner.run_experiment(experiment)
def main_worker(args, unknown_args):
"""Runs main worker thread from model training."""
args, config = parse_args_uargs(args, unknown_args)
set_global_seed(args.seed)
prepare_cudnn(args.deterministic, args.benchmark)
config.setdefault("distributed_params", {})["apex"] = args.apex
config.setdefault("distributed_params", {})["amp"] = args.amp
experiment, runner, config = prepare_config_api_components(expdir=Path(
args.expdir),
config=config)
if experiment.logdir is not None and get_rank() <= 0:
dump_environment(config, experiment.logdir, args.configs)
dump_code(args.expdir, experiment.logdir)
runner.run_experiment(experiment)
def main(cfg: DictConfig):
"""
Hydra config catalyst-dl run entry point
Args:
cfg: (DictConfig) configuration
"""
cfg = prepare_hydra_config(cfg)
set_global_seed(cfg.args.seed)
prepare_cudnn(cfg.args.deterministic, cfg.args.benchmark)
import_module(hydra.utils.to_absolute_path(cfg.args.expdir))
runner = hydra.utils.instantiate(cfg.runner, cfg=cfg)
if get_rank() <= 0:
dump_environment(logdir=runner.logdir, config=cfg)
dump_code(expdir=hydra.utils.to_absolute_path(cfg.args.expdir),
logdir=runner.logdir)
runner.run()
