Files
2026-07-13 13:17:40 +08:00

37 lines
1.1 KiB
Python

from abc import ABC, abstractmethod
from config import BenchmarkConfig
from dataloader_factory import BaseDataLoaderFactory
class BenchmarkFactory(ABC):
def __init__(self, benchmark_config: BenchmarkConfig):
self.benchmark_config = benchmark_config
self.dataloader_factory = self.get_dataloader_factory()
self.dataset_creation_time = 0
@abstractmethod
def get_dataloader_factory(self) -> BaseDataLoaderFactory:
"""Create the appropriate dataloader factory for this benchmark."""
raise NotImplementedError
# TODO: These can probably be moved to the train loop runner,
# since xgboost does not require instantiating the model
# and loss function in this way.
@abstractmethod
def get_model(self):
raise NotImplementedError
@abstractmethod
def get_loss_fn(self):
raise NotImplementedError
def get_train_dataloader(self):
return self.dataloader_factory.get_train_dataloader()
def get_val_dataloader(self):
return self.dataloader_factory.get_val_dataloader()
def get_dataloader_metrics(self):
return self.dataloader_factory.get_metrics()