ride.lifecycle

Module Contents

Classes

Lifecycle

Adds train, val, and test lifecycle methods with cross_entropy loss

Functions

prefix_keys(→ Dict)
detach_to_cpu(x)
cat_steps(steps)

Attributes

loss_names
logger

ride.lifecycle.loss_names

ride.lifecycle.logger

class ride.lifecycle.Lifecycle(hparams=None, *args, **kwargs)

Bases: ride.metrics.MetricMixin

Adds train, val, and test lifecycle methods with cross_entropy loss

During its traning_epoch_end(epoch) lifecycle method, it will call on_traning_epoch_end for all superclasses of its child class

hparams: Ellipsis

forward: Callable[[torch.Tensor], torch.Tensor]

_epoch: int

classmethod _metrics()

validate_attributes()

static configs() → ride.core.Configs

metrics_step(preds: torch.Tensor, targets: torch.Tensor, **kwargs) → ride.metrics.MetricDict

common_step(pred, target, prefix='train/', log=False)

common_epoch_end(step_outputs, prefix='train/', exclude_keys={'pred', 'target'})

preprocess_batch(batch)

training_step(batch, batch_idx=None)

training_epoch_end(step_outputs)

validation_step(batch, batch_idx=None)

validation_epoch_end(step_outputs)

test_step(batch, batch_idx=None)

test_epoch_end(step_outputs)

ride.lifecycle.prefix_keys(prefix: str, dictionary: Dict) → Dict

ride.lifecycle.detach_to_cpu(x: Union[torch.Tensor, Sequence[torch.Tensor], Dict[Any, torch.Tensor]])

ride.lifecycle.cat_steps(steps: Sequence[Union[torch.Tensor, Sequence[torch.Tensor], Dict[Any, torch.Tensor]]])