def test_experiment_restoration(nested_dict_config, tmpdir):
experiments_dir = tmpdir.join("experiments").strpath
# create an experiment
experiment = Experiment(nested_dict_config,
experiments_dir=experiments_dir)
experiment.register_directory("temp")
with pytest.raises(ValueError):
# since the experiment with the same identifier has been
# already created, experiment raises an error
experiment = Experiment(nested_dict_config,
experiments_dir=experiments_dir)
# test restoration from identifier
experiment = Experiment(resume_from=experiment.config.identifier,
experiments_dir=experiments_dir)
assert experiment.config.to_dict() == nested_dict_config
# test that `temp` is registered after restoration
assert os.path.isdir(experiment.temp)
# test restoration from directory
experiment = Experiment(resume_from=os.path.join(
experiments_dir, experiment.config.identifier))
assert experiment.config.to_dict() == nested_dict_config
# test that `temp` is registered after restoration
assert os.path.isdir(experiment.temp)
def test_experiment_register_directory(nested_dict_config, tmpdir):
experiments_dir = tmpdir.join("experiments").strpath
experiment = Experiment(nested_dict_config,
experiments_dir=experiments_dir)
experiment.register_directory("temp")
target = os.path.join(experiment.experiment_dir, "temp")
assert os.path.isdir(target)
assert experiment.temp == target
"batch_accumulation": args.batch_accumulation,
"batch_size": args.batch_size,
"warmup": args.warmup,
"lr": args.lr,
"folds": args.folds,
"max_sequence_length": args.max_sequence_length,
"max_title_length": args.max_title_length,
"max_question_length": args.max_question_length,
"max_answer_length": args.max_answer_length,
"head_tail": args.head_tail,
"label": args.label,
"_pseudo_file": args.pseudo_file,
"model_type": args.model_type,
}
experiment = Experiment(config, implicit_resuming=args.use_folds is not None)
experiment.register_directory("checkpoints")
experiment.register_directory("predictions")
def seed_everything(seed: int):
random.seed(seed)
os.environ["PYTHONHASHSEED"] = str(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.backends.cudnn.deterministic = True
logging.getLogger("transformers").setLevel(logging.ERROR)
seed_everything(args.seed)
# load the data
