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mmpretrain.engine.hooks.class_num_check_hook 源代码

# Copyright (c) OpenMMLab. All rights reserved
from mmengine.hooks import Hook
from mmengine.utils import is_seq_of

from mmpretrain.registry import HOOKS


[文档]@HOOKS.register_module() class ClassNumCheckHook(Hook): """Class Number Check HOOK.""" def _check_head(self, runner, dataset): """Check whether the `num_classes` in head matches the length of `CLASSES` in `dataset`. Args: runner (obj:`Runner`): runner object. dataset (obj: `BaseDataset`): the dataset to check. """ model = runner.model if dataset.CLASSES is None: runner.logger.warning( f'Please set class information in `metainfo` ' f'in the {dataset.__class__.__name__} and' f'check if it is consistent with the `num_classes` ' f'of head') else: assert is_seq_of(dataset.CLASSES, str), \ (f'Class information in `metainfo` in ' f'{dataset.__class__.__name__} should be a tuple of str.') for _, module in model.named_modules(): if hasattr(module, 'num_classes'): assert module.num_classes == len(dataset.CLASSES), \ (f'The `num_classes` ({module.num_classes}) in ' f'{module.__class__.__name__} of ' f'{model.__class__.__name__} does not matches ' f'the length of class information in `metainfo` ' f'{len(dataset.CLASSES)}) in ' f'{dataset.__class__.__name__}')
[文档] def before_train(self, runner): """Check whether the training dataset is compatible with head. Args: runner (obj: `IterBasedRunner`): Iter based Runner. """ self._check_head(runner, runner.train_dataloader.dataset)
[文档] def before_val(self, runner): """Check whether the validation dataset is compatible with head. Args: runner (obj:`IterBasedRunner`): Iter based Runner. """ self._check_head(runner, runner.val_dataloader.dataset)
[文档] def before_test(self, runner): """Check whether the test dataset is compatible with head. Args: runner (obj:`IterBasedRunner`): Iter based Runner. """ self._check_head(runner, runner.test_dataloader.dataset)
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