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)
