Simple Ensemble

Ensemble methods are simple and effective ways to improve the performance of machine learning models. They combine the outputs of multiple models to create a stronger model.

Examples

from fusion_bench.method import EnsembleAlgorithm

# Instantiate the EnsembleAlgorithm
algorithm = EnsembleAlgorithm()

# Assume we have a list of PyTorch models (nn.Module instances) that we want to ensemble.
models = [...]

# Run the algorithm on the models.
merged_model = algorithm.run(models)

Code Integration

Configuration template for the ensemble algorithm:

config/method/simple_ensemble.yaml

name: simple_ensemble

create a simple ensemble of CLIP-ViT models for image classification

fusion_bench method=simple_ensemble \
  modelpool=clip-vit-base-patch32_TA8 \
  taskpool=clip-vit-classification_TA8