Source code for mmengine.runner.base_loop
# Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from typing import Any, Dict, Union
from torch.utils.data import DataLoader
[docs]class BaseLoop(metaclass=ABCMeta):
"""Base loop class.
All subclasses inherited from ``BaseLoop`` should overwrite the
:meth:`run` method.
Args:
runner (Runner): A reference of runner.
dataloader (Dataloader or dict): An iterator to generate one batch of
dataset each iteration.
"""
def __init__(self, runner, dataloader: Union[DataLoader, Dict]) -> None:
self._runner = runner
if isinstance(dataloader, dict):
# Determine whether or not different ranks use different seed.
diff_rank_seed = runner._randomness_cfg.get(
'diff_rank_seed', False)
self.dataloader = runner.build_dataloader(
dataloader, seed=runner.seed, diff_rank_seed=diff_rank_seed)
else:
self.dataloader = dataloader
@property
def runner(self):
return self._runner