def __init__(self, arguments_service: PretrainedArgumentsService,
dataloader_service: DataLoaderService,
loss_function: LossBase, optimizer: OptimizerBase,
log_service: LogService, file_service: FileService,
model: ModelBase):
self._arguments_service = arguments_service
self._model_path = file_service.get_checkpoints_path()
self._optimizer_base = optimizer
self._log_service = log_service
self._dataloader_service = dataloader_service
self._loss_function = loss_function
self._model = model.to(arguments_service.device)
self.data_loader_train: DataLoader = None
self.data_loader_validation: DataLoader = None
self._initial_patience = self._arguments_service.patience
# if we are going to fine-tune after initial convergence
# then we set a low patience first and use the real one in
# the second training iteration set
if self._arguments_service.fine_tune_after_convergence:
self._initial_patience = 5
