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Trainer

Struct Trainer 

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pub struct Trainer { /* private fields */ }
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High-level trainer that wraps optimizer + loss + callbacks configuration.

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impl Trainer

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pub fn new(config: TrainerConfig) -> Self

Create a new trainer with the given configuration.

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pub fn add_callback(&mut self, cb: Box<dyn TrainingCallback>) -> &mut Self

Add a callback (EarlyStopping, BestModelCheckpoint, etc.).

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pub fn fit( &mut self, model: &mut SequentialModel, graph: &mut Graph, inputs: &Tensor, targets: &Tensor, ) -> Result<TrainResult, ModelError>

Train the model on the given data.

inputs and targets are combined into a SupervisedDataset. For each epoch the method runs a full pass over mini-batches, computes the loss, back-propagates, and steps the optimizer. Callbacks are invoked after every epoch and may request early stopping.

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