KenningΒΆ Introduction Kenning Kenning installation Kenning structure Kenning usage Example use case of Kenning Using Kenning as a library in Python scripts Adding new implementations Deep Learning deployment stack From training to deployment Dataset preparation Model preparation and training Model optimization Model compilation and deployment Defining optimization pipelines in Kenning JSON specification Model evaluation using its native framework Optimizing and running a model on a single device Compiling a model and running it remotely Using Kenning via command line arguments Command-line arguments for classes Model training In-framework inference performance measurements ONNX conversion Testing inference on target hardware Running inference Generating performance reports Kenning measurements Performance metrics ONNX support in deep learning frameworks ONNX support grid in deep learning frameworks ONNX conversion support grid Sample autogenerated report Pet Dataset classification using TVM-compiled TensorFlow model Inference performance metrics for build.local-cpu-tvm-tensorflow-classification.json Inference quality metrics for build.local-cpu-tvm-tensorflow-classification.json Creating applications with Kenning JSON structure KenningFlow execution Implemented Runners Developing Kenning blocks Model and I/O metadata Implementing a new Kenning component Implementing Kenning runtime blocks Kenning API Deployment API overview KenningFlow Runner Dataset ModelWrapper Optimizer Runtime RuntimeProtocol Measurements ONNXConversion DataProvider OutputCollector Last update: 2023-03-28