torchrecipes/audio/source_separation/train_app.py [46:60]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        load_checkpoint_strict: bool = True,
        pretrained_checkpoint_path: Optional[str] = None,
        # pyre-fixme[2]: Parameter annotation cannot contain `Any`.
        callbacks: Optional[List[Any]] = None,
        tb_save_dir: Optional[str] = None,
    ) -> None:
        self.load_checkpoint_strict = load_checkpoint_strict
        self.pretrained_checkpoint_path = pretrained_checkpoint_path
        self.callbacks = callbacks
        self.tb_save_dir = tb_save_dir

        # This has to happen at last because it depends on the value above.
        super().__init__(module, trainer, datamodule)

    def get_data_module(self) -> Optional[LightningDataModule]:
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torchrecipes/vision/image_classification/train_app.py [42:56]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        load_checkpoint_strict: bool = True,
        pretrained_checkpoint_path: Optional[str] = None,
        # pyre-fixme[2]: Parameter annotation cannot contain `Any`.
        callbacks: Optional[List[Any]] = None,
        tb_save_dir: Optional[str] = None,
    ) -> None:
        self.load_checkpoint_strict = load_checkpoint_strict
        self.pretrained_checkpoint_path = pretrained_checkpoint_path
        self.callbacks = callbacks
        self.tb_save_dir = tb_save_dir

        # This has to happen at last because it depends on the value above.
        super().__init__(module, trainer, datamodule)

    def get_data_module(self) -> Optional[LightningDataModule]:
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