mabor::train

Struct TrainEpoch

pub struct TrainEpoch<B, TI>
where
    B: AutodiffBackend,
{ /* private fields */ }
Expand description

A training epoch.

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impl<B, TI> TrainEpoch<B, TI>
where B: AutodiffBackend,

pub fn new( dataloader: Vec<Arc<dyn DataLoader<B, TI>>>, epoch: usize, epoch_total: usize, grad_accumulation: Option<usize>, ) -> TrainEpoch<B, TI>

Constructs a new TrainEpoch.

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impl<B, TI> TrainEpoch<B, TI>
where B: AutodiffBackend,

pub fn run<LC, TO>( &mut self, model: <LC as LearnerComponents>::Model, optim: <LC as LearnerComponents>::Optimizer, scheduler: &mut <LC as LearnerComponents>::LrScheduler, processor: &mut <LC as LearnerComponents>::EventProcessor, interrupter: &TrainingInterrupter, ) -> (<LC as LearnerComponents>::Model, <LC as LearnerComponents>::Optimizer)
where LC: LearnerComponents<Backend = B>, <LC as LearnerComponents>::EventProcessor: EventProcessor<ItemTrain = TO>, <LC as LearnerComponents>::Model: TrainStep<TI, TO>,

Runs the training epoch.

§Arguments
  • model - The model to train.
  • optim - The optimizer to use.
  • scheduler - The learning rate scheduler to use.
  • processor - The event processor to use.
§Returns

The trained model and the optimizer.

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impl<B, TI> TrainEpoch<B, TI>
where B: AutodiffBackend,

pub fn run_multi_device<LC, TO>( &mut self, model: <LC as LearnerComponents>::Model, optim: <LC as LearnerComponents>::Optimizer, lr_scheduler: &mut <LC as LearnerComponents>::LrScheduler, processor: &mut <LC as LearnerComponents>::EventProcessor, devices: Vec<<<LC as LearnerComponents>::Backend as Backend>::Device>, interrupter: &TrainingInterrupter, ) -> (<LC as LearnerComponents>::Model, <LC as LearnerComponents>::Optimizer)
where LC: LearnerComponents<Backend = B>, <LC as LearnerComponents>::EventProcessor: EventProcessor<ItemTrain = TO>, <LC as LearnerComponents>::Model: TrainStep<TI, TO>, TO: Send + 'static, TI: Send + 'static,

Runs the training epoch on multiple devices.

§Arguments
  • model - The model to train.
  • optim - The optimizer to use.
  • lr_scheduler - The learning rate scheduler to use.
  • processor - The event processor to use.
  • devices - The devices to use.
§Returns

The trained model and the optimizer.

Auto Trait Implementations§

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impl<B, TI> Freeze for TrainEpoch<B, TI>

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impl<B, TI> !RefUnwindSafe for TrainEpoch<B, TI>

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impl<B, TI> !Send for TrainEpoch<B, TI>

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impl<B, TI> !Sync for TrainEpoch<B, TI>

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impl<B, TI> Unpin for TrainEpoch<B, TI>

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impl<B, TI> !UnwindSafe for TrainEpoch<B, TI>

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