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n2n_configs

N2NAdvancedConfig #

Bases: AdvancedConfig

N2N advanced configuration.

Source code in src/careamics_napari/careamics_utils/n2n_configs.py 
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class N2NAdvancedConfig(AdvancedConfig):
    """N2N advanced configuration."""

    n_channels_in: int = 1
    """Number of input channels."""

    n_channels_out: int = 1
    """Number of output channels."""

n_channels_in = 1 class-attribute instance-attribute #

Number of input channels.

n_channels_out = 1 class-attribute instance-attribute #

Number of output channels.

get_default_n2n_config() #

Return a default N2N configuration.

Source code in src/careamics_napari/careamics_utils/n2n_configs.py 
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def get_default_n2n_config() -> BaseConfig:
    """Return a default N2N configuration."""
    num_workers = get_num_workers()

    config = create_n2n_configuration(
        experiment_name="careamics_care",
        data_type="array",
        axes="YX",
        patch_size=[64, 64],
        batch_size=16,
        num_epochs=30,
        independent_channels=True,
        train_dataloader_params={"num_workers": num_workers},
        val_dataloader_params={"num_workers": num_workers},
        logger="tensorboard",
    )
    config = BaseConfig(**config.model_dump(), needs_gt=True)

    return config