Transductive Trainer

class hivegraph.engine.transductive.TransductiveTrainer(model: Module, dataset: Dataset, device: str = 'cpu', random_state: int = 42)

Bases: BaseTrainer

fit(epochs: int, batch_size: int, optimizer: Optimizer, verbose: bool, log_to_wandb: bool) → None

Trains the model on the given dataset

Parameters:

• epochs (int) – Number of epochs

• batch_size (int) – batch size

• optimizer (torch.optim.Optimizer) – Optimizer

• verbose (bool) – Whether to print stats, defaults to True

• log_to_wandb (bool) – Whether to log stats to wandb, defaults to False

train_step(train_dataloder: Iterable, optimizer: Optimizer, **kwargs) → float

Performs a single training step

Parameters:

• train_dataloder (Iterable) – Training Dataloader

• optimizer (torch.optim.Optimizer) – Optimizer

Returns:

Training Loss

Return type:

float