cli.shared.types.train package

cli.shared.types.train.training module

class cli.shared.types.train.training.Training(epochs: int, learning_rate: float, optimizer: str, criterion: str, save_final_model: bool, save_model_path: str, save_model_name: str, save_checkpoint: bool, save_checkpoint_path: str, save_checkpoint_name: str, checkpoint_interval: int, load_checkpoint: bool, load_checkpoint_path: str, verbose: bool, scheduler: str | None = None, scheduler_kwargs: dict | None = None, optimizer_kwargs: dict | None = None)

Bases: object

This dataclass is used to store the configuration of the training.

checkpoint_interval: int

criterion: str

epochs: int

learning_rate: float

load_checkpoint: bool

load_checkpoint_path: str

optimizer: str

optimizer_kwargs: dict | None = None

save_checkpoint: bool

save_checkpoint_name: str

save_checkpoint_path: str

save_final_model: bool

save_model_name: str

save_model_path: str

scheduler: str | None = None

scheduler_kwargs: dict | None = None

verbose: bool

class cli.shared.types.train.training.TrainingCliConfigType(model: ModelCliConfigType, dataset: DatasetCliConfigType, dataloader: DataLoaderCliConfigType, training: Training, device: DeviceConfig)

Bases: object

This dataclass is used to store the configuration of the training CLI.

dataloader: DataLoaderCliConfigType

dataset: DatasetCliConfigType

device: DeviceConfig

model: ModelCliConfigType

training: Training