hugegraph-ml/src/hugegraph_ml/tasks/node_classify.py [49:62]:
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            loss = self._model.loss(logits, labels)
            _, predicted = torch.max(logits, dim=1)
            accuracy = (predicted == labels).sum().item() / len(labels)
        return {"accuracy": accuracy, "loss": loss.item()}

    def train(
        self,
        lr: float = 1e-3,
        weight_decay: float = 0,
        n_epochs: int = 200,
        patience: int = float("inf"),
        early_stopping_monitor: Literal["loss", "accuracy"] = "loss",
        gpu: int = -1,
    ):
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hugegraph-ml/src/hugegraph_ml/tasks/node_classify_with_edge.py [57:70]:
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            loss = self._model.loss(logits, labels)
            _, predicted = torch.max(logits, dim=1)
            accuracy = (predicted == labels).sum().item() / len(labels)
        return {"accuracy": accuracy, "loss": loss.item()}

    def train(
        self,
        lr: float = 1e-3,
        weight_decay: float = 0,
        n_epochs: int = 200,
        patience: int = float("inf"),
        early_stopping_monitor: Literal["loss", "accuracy"] = "loss",
        gpu: int = -1,
    ):
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