help='How to split the dataset')
parser.add_argument('--dataset_split_seed', type=int, default=98765)
parser.add_argument(
'--eval_set_size',
type=int,
default=500,
help=
'Size of val and test set. 500 for ML-1m and 10000 for ML-20m recommended')
################
# Dataloader
################
parser.add_argument('--dataloader_code',
type=str,
default='ae',
choices=DATALOADERS.keys())
parser.add_argument('--dataloader_random_seed', type=float, default=0.0)
parser.add_argument('--train_batch_size', type=int, default=64)
parser.add_argument('--val_batch_size', type=int, default=64)
parser.add_argument('--test_batch_size', type=int, default=64)
################
# Trainer
################
parser.add_argument('--trainer_code',
type=str,
default='vae',
choices=TRAINERS.keys())
# device #
parser.add_argument('--device',
type=str,
################
# Dataset
################
parser.add_argument('--dataset_code', type=str, default='ml-20m', choices=DATASETS.keys())
parser.add_argument('--min_rating', type=int, default=4, help='Only keep ratings greater than equal to this value')
parser.add_argument('--min_uc', type=int, default=5, help='Only keep users with more than min_uc ratings')
parser.add_argument('--min_sc', type=int, default=0, help='Only keep items with more than min_sc ratings')
parser.add_argument('--split', type=str, default='leave_one_out', help='How to split the datasets')
parser.add_argument('--dataset_split_seed', type=int, default=98765)
parser.add_argument('--eval_set_size', type=int, default=500,
help='Size of val and test set. 500 for ML-1m and 10000 for ML-20m recommended')
################
# Dataloader
################
parser.add_argument('--dataloader_code', type=str, default='bert', choices=DATALOADERS.keys())
parser.add_argument('--dataloader_random_seed', type=int, default=0.0)
parser.add_argument('--train_batch_size', type=int, default=64)
parser.add_argument('--val_batch_size', type=int, default=64)
parser.add_argument('--test_batch_size', type=int, default=64)
################
# NegativeSampler
################
parser.add_argument('--train_negative_sampler_code', type=str, default='random', choices=['popular', 'random'],
help='Method to sample negative items for training. Not used in bert')
parser.add_argument('--train_negative_sample_size', type=int, default=100)
parser.add_argument('--train_negative_sampling_seed', type=int, default=None)
parser.add_argument('--test_negative_sampler_code', type=str, default='random', choices=['popular', 'random'],
help='Method to sample negative items for evaluation')
parser.add_argument('--test_negative_sample_size', type=int, default=100)