NNI provides an easy way to adopt an approach to set up parameter tuning algorithms, we call them Tuner.
Tuner receives metrics from Trial to evaluate the performance of a specific parameters/architecture configuration. Tuner sends the next hyper-parameter or architecture configuration to Trial.
Overview <Tuner/BuiltinTuner> TPE <Tuner/HyperoptTuner> Random Search <Tuner/HyperoptTuner> Anneal <Tuner/HyperoptTuner> Naive Evolution <Tuner/EvolutionTuner> SMAC <Tuner/SmacTuner> Metis Tuner <Tuner/MetisTuner> Batch Tuner <Tuner/BatchTuner> Grid Search <Tuner/GridsearchTuner> GP Tuner <Tuner/GPTuner> Network Morphism <Tuner/NetworkmorphismTuner> Hyperband <Tuner/HyperbandAdvisor> BOHB <Tuner/BohbAdvisor> PPO Tuner <Tuner/PPOTuner> PBT Tuner <Tuner/PBTTuner>