def fwfm_query_config(dataset_id: str, epochs: int, data_processor: DataProcessor) -> Tuple[
TrainConfig, EvalConfig]:
if not data_processor:
data_processor = ConcatDataProcessor()
train_config = TrainConfig(
dataset_id=dataset_id,
data_processor=data_processor,
model=fm.FwFMQuery,
epochs=epochs,
verbose=2,
)
eval_config = EvalConfig(
dataset_id=dataset_id,
model_name='fwfm_query',
verbose=0,
)
return train_config, eval_config
def nrmf_simple_all_config(dataset_id: str, epochs: int, data_processor) -> Tuple[
TrainConfig, EvalConfig]:
if not data_processor:
data_processor = ConcatDataProcessor()
train_config = TrainConfig(
dataset_id=dataset_id,
data_processor=data_processor,
model=nrmf.NRMFSimpleAll,
epochs=epochs,
verbose=2,
)
eval_config = EvalConfig(
dataset_id=dataset_id,
model_name='nrmf_simple_all',
verbose=0,
)
return train_config, eval_config
def ebr_config(dataset_id: str, epochs: int, data_processor: DataProcessor) -> Tuple[
TrainConfig, EvalConfig]:
if not data_processor:
data_processor = ConcatDataProcessor()
train_config = TrainConfig(
dataset_id=dataset_id,
data_processor=data_processor,
model=representation.EBR,
epochs=epochs,
verbose=2,
)
eval_config = EvalConfig(
dataset_id=dataset_id,
model_name='ebr',
verbose=0,
)
return train_config, eval_config
def naive_config(dataset_id: str, epochs: int, data_processor: DataProcessor) -> Tuple[
TrainConfig, EvalConfig]:
if not data_processor:
data_processor = ConcatDataProcessor()
train_config = TrainConfig(
dataset_id=dataset_id,
data_processor=data_processor,
model=naive.Naive,
epochs=epochs,
verbose=2,
)
eval_config = EvalConfig(
dataset_id=dataset_id,
model_name='naive',
verbose=0,
)
return train_config, eval_config