Multi-trial NAS

In multi-trial NAS, users need model evaluator to evaluate the performance of each sampled model, and need an exploration strategy to sample models from a defined model space. Here, users could use NNI provided model evaluators or write their own model evalutor. They can simply choose a exploration strategy. Advanced users can also customize new exploration strategy. For a simple example about how to run a multi-trial NAS experiment, please refer to Quick Start.

• Model Evaluators
  • Customize Evaluator with Any Function
  • Evaluators with PyTorch-Lightning
• Exploration Strategies
  • Usage of Exploration Strategy
  • Supported Exploration Strategies
  • Customize Exploration Strategy
• Execution Engines
  • Pure-python Execution Engine
  • Graph-based Execution Engine
  • CGO Execution Engine (experimental)
• Serialization