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from typing import Callable, Iterable
import torch
from torch.utils.data import Dataset
from libs.logging import Loggers
from libs.utils import Trainer, BaseConfig
class PosReconTrainer(Trainer):
def __init__(self, *args, **kwargs):
super(PosReconTrainer, self).__init__(*args, **kwargs)
@staticmethod
def _prepare_dataset(dataset_config: BaseConfig.DatasetConfig) -> tuple[Dataset, Dataset]:
pass
@staticmethod
def _init_models(dataset: str) -> Iterable[tuple[str, torch.nn.Module]]:
pass
@staticmethod
def _configure_optimizers(models: Iterable[tuple[str, torch.nn.Module]], optim_config: BaseConfig.OptimConfig) -> \
Iterable[tuple[str, torch.optim.Optimizer]]:
pass
def train(self, num_iters: int, loss_fn: Callable, logger: Loggers, device: torch.device):
pass
def eval(self, loss_fn: Callable, device: torch.device):
pass
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