training

superduper.ext.torch.training

`TorchTrainer`

TorchTrainer(self,
     identifier: str,
     db: dataclasses.InitVar[typing.Optional[ForwardRef('Datalayer')]] = None,
     uuid: str = None,
     *,
     artifacts: 'dc.InitVar[t.Optional[t.Dict]]' = None,
     key: 'ModelInputType',
     select: 'Query',
     transform: 't.Optional[t.Callable]' = None,
     metric_values: Dict = None,
     signature: 'Signature' = '*args',
     data_prefetch: 'bool' = False,
     prefetch_size: 'int' = 1000,
     prefetch_factor: 'int' = 100,
     in_memory: 'bool' = True,
     compute_kwargs: 't.Dict' = None,
     objective: Callable,
     loader_kwargs: Dict = None,
     max_iterations: int = 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000,
     no_improve_then_stop: int = 5,
     download: bool = False,
     validation_interval: int = 100,
     listen: str = 'objective',
     optimizer_cls: str = 'Adam',
     optimizer_kwargs: Dict = None,
     optimizer_state: Optional[Dict] = None,
     collate_fn: Optional[Callable] = None) -> None

Parameter	Description
identifier	Identifier of the leaf.
db	Datalayer instance.
uuid	UUID of the leaf.
artifacts	A dictionary of artifacts paths and `DataType` objects
key	Model input type key.
select	Model select query for training.
transform	(optional) transform callable.
metric_values	Metric values
signature	Model signature.
data_prefetch	Boolean for prefetching data before forward pass.
prefetch_size	Prefetch batch size.
prefetch_factor	Prefetch factor for data prefetching.
in_memory	If training in memory.
compute_kwargs	Kwargs for compute backend.
objective	Objective function
loader_kwargs	Kwargs for the dataloader
max_iterations	Maximum number of iterations
no_improve_then_stop	Number of iterations to wait for improvement before stopping
download	Whether to download the data
validation_interval	How often to validate
listen	Which metric to listen to for early stopping
optimizer_cls	Optimizer class
optimizer_kwargs	Kwargs for the optimizer
optimizer_state	Latest state of the optimizer for contined training
collate_fn	Collate function for the dataloader

Configuration for the PyTorch trainer.

TorchTrainer​

`TorchTrainer`