from cogito.core.models import BaseTrainer

{% for route in routes %}
class {{ route.class_name }}(BaseTrainer):

    def setup(self):
        """
        This method is called once before training begins.
        """

        # TODO: (USER) Implement the setup method or remove it if not needed

        pass

    def train(self, data_path: str, epochs: int, batch_size: int, learning_rate: float) -> dict:
        """
        This method is called to perform model training.
        
        Parameters:
            data_path (str): Path to the training data.
            epochs (int): Number of training epochs.
            batch_size (int): Size of training batches.
            learning_rate (float): Learning rate for optimization.
            
        Returns:
            dict: Training metrics and results.
        """

        # TODO: (USER) Implement the training method
        # TODO: (USER) Return training metrics (loss, accuracy, etc.)
        return {
            "status": "success",
            "metrics": {
                "loss": 0.1,
                "accuracy": 0.95
            },
            "info": f"Trained on {data_path} for {epochs} epochs with batch size {batch_size} and learning rate {learning_rate}"
        }

{% endfor %} 