def main(args, unknown_args): args, config = parse_args_uargs(args, unknown_args) set_global_seed(args.seed) prepare_cudnn(args.deterministic, args.benchmark) if args.logdir is not None: os.makedirs(args.logdir, exist_ok=True) dump_environment(config, args.logdir, args.configs) if args.expdir is not None: module = import_module(expdir=args.expdir) # noqa: F841 if args.logdir is not None: dump_code(args.expdir, args.logdir) env = ENVIRONMENTS.get_from_params(**config["environment"]) algorithm_name = config["algorithm"].pop("algorithm") if algorithm_name in OFFPOLICY_ALGORITHMS_NAMES: ALGORITHMS = OFFPOLICY_ALGORITHMS trainer_fn = OffpolicyTrainer sync_epoch = False elif algorithm_name in ONPOLICY_ALGORITHMS_NAMES: ALGORITHMS = ONPOLICY_ALGORITHMS trainer_fn = OnpolicyTrainer sync_epoch = True else: # @TODO: add registry for algorithms, trainers, samplers raise NotImplementedError() db_server = DATABASES.get_from_params( **config.get("db", {}), sync_epoch=sync_epoch ) algorithm_fn = ALGORITHMS.get(algorithm_name) algorithm = algorithm_fn.prepare_for_trainer(env_spec=env, config=config) if args.resume is not None: checkpoint = utils.load_checkpoint(filepath=args.resume) checkpoint = utils.any2device(checkpoint, utils.get_device()) algorithm.unpack_checkpoint( checkpoint=checkpoint, with_optimizer=False ) monitoring_params = config.get("monitoring_params", None) trainer = trainer_fn( algorithm=algorithm, env_spec=env, db_server=db_server, logdir=args.logdir, monitoring_params=monitoring_params, **config["trainer"], ) trainer.run()
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(args, unknown_args): args, config = parse_args_uargs(args, unknown_args) set_global_seed(args.seed) Experiment, Runner = import_experiment_and_runner(Path(args.expdir)) experiment = Experiment(config) runner = Runner() if experiment.logdir is not None: dump_config(config, experiment.logdir, args.configs) dump_code(args.expdir, experiment.logdir) runner.run_experiment(experiment, check=args.check)
def main(args, unknown_args): args, config = parse_args_uargs(args, unknown_args) set_global_seed(args.seed) prepare_cudnn(args.deterministic, args.benchmark) Experiment, Runner = import_experiment_and_runner(Path(args.expdir)) experiment = Experiment(config) runner = Runner() if experiment.logdir is not None: dump_environment(config, experiment.logdir, args.configs) dump_code(args.expdir, experiment.logdir) runner.run_experiment(experiment, check=args.check)
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(args, unknown_args): """Run the ``catalyst-dl run`` script""" args, config = parse_args_uargs(args, unknown_args) set_global_seed(args.seed) prepare_cudnn(args.deterministic, args.benchmark) Experiment, Runner = import_experiment_and_runner(Path(args.expdir)) runner_params = config.pop("runner_params", {}) or {} experiment = Experiment(config) runner = Runner(**runner_params) if experiment.logdir is not None: dump_environment(config, experiment.logdir, args.configs) dump_code(args.expdir, experiment.logdir) check_run = safitty.get(config, "args", "check", default=False) runner.run_experiment(experiment, check=check_run)