metrics_adapter

orchard.tasks.classification.metrics_adapter

Classification Validation Metrics Adapter.

Wraps :func:orchard.trainer.engine.validate_epoch to satisfy :class:~orchard.core.task_protocols.TaskValidationMetrics.

ClassificationMetricsAdapter

Computes per-epoch classification metrics (loss, accuracy, AUC, F1).

compute_validation_metrics(model, val_loader, criterion, device)

Delegate to the existing validation engine.

Parameters:

Name	Type	Description	Default
model	Module	Neural network model to evaluate.	required
val_loader	DataLoader[Any]	Validation data provider.	required
criterion	Module	Loss function.	required
device	device	Hardware target.	required

Returns:

Type	Description
Mapping[str, float]	Immutable mapping with keys: loss, accuracy, auc, f1.

Source code in orchard/tasks/classification/metrics_adapter.py

def compute_validation_metrics(
    self,
    model: nn.Module,
    val_loader: DataLoader[Any],
    criterion: nn.Module,
    device: torch.device,
) -> Mapping[str, float]:
    """
    Delegate to the existing validation engine.

    Args:
        model: Neural network model to evaluate.
        val_loader: Validation data provider.
        criterion: Loss function.
        device: Hardware target.

    Returns:
        Immutable mapping with keys: loss, accuracy, auc, f1.
    """
    return validate_epoch(model, val_loader, criterion, device)