ModusToolbox™ Machine Learning
ModusToolbox™ Machine Learning (ML) enables you to rapidly evaluate and deploy Machine Learning models on Infineon MCUs. ModusToolbox™ ML is designed to work seamlessly with the ModusToolbox™ ecosystem and can be dropped into existing projects to enable machine learning tasks on low-power edge devices.
Easy Integration and Flexible Tools
ModusToolbox™ ML tools enables you to:
- Import models from popular training frameworks such as TensorFlow™
- Optimize the model for embedded platforms to reduce the size and complexity
- Validate the performance of the optimized model by checking performance against test data
- Generate optimized model code and libraries which are integrated with the ModusToolbox™ flow
Optimized for Embedded Performance
ModusToolbox™ ML includes an embedded inference engine which supports optimized implementations of most popular Neural Network operators such as 1D/2D convolutions, a variety of activation functions as well as support for more complex operators for RNN networks such as GRU.
ModusToolbox™ ML adds configurators, tools, code examples and supporting libraries to help quickly get started with Machine Learning Model deployment on Infineon MCU’s.
The ModusToobox™ ML 1.2 release brings in a set of great new features and improvements to make the deployment and validation of Deep Learning models on the PSoC™ 6 platform even easier. The major updates to this release are:
- Data streaming for on-device validation
- Size optimization option during model conversion
- Improved cycle, accuracy for 8-bit models
- New kernels
- LSTM, and Dilated CNN’s
- Limited support for Lambda Layers - reduce_max, reduce_min, reduce_prod, reduce_mean
- Import from Keras(H5) type file models
- Validation GUI for various quantization levels
- Supported operators and kernels
To get started with ModusToolbox™ ML, please download the latest version of ModusToolbox™ software and patches and get the below hardware evaluation kits:
Please follow the steps in the ModusToolbox™ ML User Guide listed in the documentation which will guide you through the setup.