Tutorials ========= Aidge 101 --------- To get started with Aidge, please follow the Aidge demonstration tutorial. This tutorial demonstrates the basic features of the Aidge Framework, importing an ONNX, transforming a neural network graph, performing inference and a cpp export. .. nbgallery:: load_and_run.nblink Aidge DNN fonctionnalities -------------------------- - Manipulating databases and creating batches of data - Train a Deep Neural Network - Provide an operator implementation using Python or meta-operators - Perform advanced graph matching with the Graph Regular Expression tool .. nbgallery:: database.nblink learning.nblink ONNX.nblink graph_regex.nblink DNN Optimization ---------------- - Perform post Training Quantization - Perform Convolution tiling .. nbgallery:: ptq.nblink tiling.nblink DNN export ---------- .. nbgallery:: export_cpp.nblink - `Exercise on adding a custom implementation for a cpp export `_ - `Export your DNN with TensorRT `_ - `Export your DNN for an STM32 `_ Tutorial on adding the C++ Aidge -------------------------------- You can extend our operator coverage by adding an operator and its implementation in the C++ Aidge library. The `Add an operator and its implementation Tutorial `_ details the steps to follow. For more information on contributing to Aidge, please refer to the `wiki `_. If you encounter any difficulty with the Tutorials, please create an issue `here `_.