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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 tasks.

fusion_bench \
  method=ensemble/simple_ensemble \
  modelpool=CLIPVisionModelPool/clip-vit-base-patch32_TA8 \
  taskpool=CLIPVisionModelTaskPool/clip-vit-classification_TA8

Implementation Details