torchtraining.iterations

class torchtraining.iterations.Eval(step: Any, module: torch.nn.modules.module.Module, data: Union[torch.utils.data.dataset.Dataset, torch.utils.data.dataloader.DataLoader], log: Union[int, str] = 'NONE', *args, **kwargs)

Bases: torchtraining.iterations.Iteration

Perform evaluation step until data is exhausted.

Provided module will be passed to every step.

Parameters

• step (torchtraining.steps.Step) – Single step to run. Usually subclass of torchtraining.steps.Step, but could be any Callable taking module and data arguments and returning anything.

• module (torch.nn.Module) – Torch module (or modules) passed to step during each call.

• data ([torch.utils.data.Dataset | torch.utils.data.DataLoader]) – Iterable object (usually data or dataloader) yielding data passed to step.

logstr | int, optional

Severity level for logging object’s actions. Available levels of logging:

• NONE 0

• TRACE 5

• DEBUG 10

• INFO 20

• SUCCESS 25

• WARNING 30

• ERROR 40

• CRITICAL 50

Default: NONE (no logging, 0 priority)

class torchtraining.iterations.Iteration(step: Any, module: torch.nn.modules.module.Module, data: Union[torch.utils.data.dataset.Dataset, torch.utils.data.dataloader.DataLoader], train: bool, log: Union[int, str] = 'NONE', *args, **kwargs)

Bases: torchtraining._base.Iteration

Perform step (train or eval) until data is exhausted.

Provided module will be passed to every step.

Parameters

• step (torchtraining.steps.Step) – Single step to run. Usually subclass of torchtraining.steps.Step, but could be any Callable taking module and data arguments and returning anything.

• module (torch.nn.Module) – Torch module (or modules) passed to step during each call.

• data ([torch.utils.data.Dataset | torch.utils.data.DataLoader]) – Iterable object (usually data or dataloader) yielding data passed to step.

train: bool

Whether module should be in training state (module.train()) with enabled gradient or in evaluation mode (module.eval()) with disabled gradient

logstr | int, optional

Severity level for logging object’s actions. Available levels of logging:

• NONE 0

• TRACE 5

• DEBUG 10

• INFO 20

• SUCCESS 25

• WARNING 30

• ERROR 40

• CRITICAL 50

Default: NONE (no logging, 0 priority)

forward(*args, **kwargs)

class torchtraining.iterations.Train(step: Any, module: torch.nn.modules.module.Module, data: Union[torch.utils.data.dataset.Dataset, torch.utils.data.dataloader.DataLoader], log: Union[int, str] = 'NONE', *args, **kwargs)

Bases: torchtraining.iterations.Iteration

Perform training step until data is exhausted.

Provided module will be passed to every step.

Parameters

• step (torchtraining.steps.Step) – Single step to run. Usually subclass of torchtraining.steps.Step, but could be any Callable taking module and data arguments and returning anything.

• module (torch.nn.Module) – Torch module (or modules) passed to step during each call.

• data ([torch.utils.data.Dataset | torch.utils.data.DataLoader]) – Iterable object (usually data or dataloader) yielding data passed to step.

logstr | int, optional

Severity level for logging object’s actions. Available levels of logging:

• NONE 0

• TRACE 5

• DEBUG 10

• INFO 20

• SUCCESS 25

• WARNING 30

• ERROR 40

• CRITICAL 50

Default: NONE (no logging, 0 priority)