Checkpoints

Checkpoints

When creating a new VFL training session, you can pass a previous training session ID and round ID as a checkpoint. The model will be loaded from this checkpoint for the new training session.

You can also download round-specific model coefficients through the SDK interface. Coefficients are saved to the federated server after each round in addition to at the end of a session.

Run a session to determine a checkpoint of interest

checkpoint_vfl_train_session = client.create_vfl_session(
            name="Testing checkpointing in VFL",
            description="Running a VFL train session to find a checkpoint",
            prl_session_id=prl_session.id,              # must be a succesful PRL session ID that matches the datasets used in this session
            vfl_mode="train",
            min_num_clients=2,
            num_rounds=num_rounds,
            package_name="VflGlm",
            data_config=data_config,
            model_config=model_config,
        ).start()

checkpoint_vfl_train_session.id

Get metrics for the session

metrics = checkpoint_vfl_train_session.metrics().as_dict()
        metrics

Start a new session from a checkpoint

To start a new session from a previous checkpoint, specify the training_session_id and the training_round_id from the previous session of interest.

Example:

vfl_train_session = client.create_vfl_session(
            name="VFL train session with checkpoint",
            description="vfl train session with checkpoint",
            prl_session_id=prl_session.id,
            training_session_id=checkpoint_vfl_train_session.id,
            training_round_id=2,
            vfl_mode="train",
            min_num_clients=2,
            num_rounds=num_rounds,
            package_name="VflGlm",
            data_config=data_config,
            model_config=model_config,
        ).start()

vfl_train_session.id

Using best training model for prediction

You can pass a desired model round ID from a successful VFL train session to be used as a starting point in a VFL predict session. This enables you to run predict session with the best model from training.

Example:

vfl_predict_session = client.create_vfl_session(
            name="Prediction from best trained model",
            description="Using a specific model round from training to perform a prediction.",
            prl_session_id=prl_session.id,
            training_session_id=vfl_train_session.id,           #specify the training session ID
            training_round_id=2,                                #specify the round ID of the best training model
            vfl_mode="predict",
            data_config=data_config,
        ).start()

vfl_predict_session.id
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