Example

Example of a simple algorithm for image classification.

This can be run from the command-line like so:

python project/main.py algorithm=example

ExampleAlgorithm

Bases: LightningModule

Example learning algorithm for image classification.

__init__

__init__(
    datamodule: ImageClassificationDataModule,
    network: _Config[Module],
    optimizer: _PartialConfig[Optimizer] = AdamConfig(
        lr=0.0003
    ),
    init_seed: int = 42,
)

Create a new instance of the algorithm.

Parameters:

Name	Type	Description	Default
datamodule	ImageClassificationDataModule	Object used to load train/val/test data. See the lightning docs for LightningDataModule for more info.	required
network	_Config[Module]	The config of the network to instantiate and train.	required
optimizer	_PartialConfig[Optimizer]	The config for the Optimizer. Instantiating this will return a function (a functools.partial) that will create the Optimizer given the hyper-parameters.	AdamConfig(lr=0.0003)
init_seed	int	The seed to use when initializing the weights of the network.	42

forward

forward(input: Tensor) -> Tensor

Forward pass of the network.

configure_optimizers

configure_optimizers()

Creates the optimizers.

See lightning.pytorch.core.LightningModule.configure_optimizers for more information.

configure_callbacks

configure_callbacks() -> Sequence[Callback] | Callback

Creates callbacks to be used by default during training.