Workflow for Deep Learning Code Generation with MATLAB Coder
With MATLAB® Coder™, you can generate code for prediction from a pretrained convolutional neural network (CNN), targeting an embedded platform that uses an Intel® processor or an ARM® processor. The generated code calls the Intel MKL-DNN or ARM Compute Library to apply high performance.
You can also use MATLAB Coder to generate generic C or C++ code for deep learning networks. Such C or C++ code does not depend on any third-party libraries.
Get a trained network by using Deep Learning Toolbox™. Construct and train the network or use a pretrained network. For more information, see:
The network must be supported for code generation. See Networks and Layers Supported for Code Generation.
Load a network object from the trained network.
Generate C++ code for the trained network by using
codegenor the MATLAB Coder app. See:
- Deep Learning in MATLAB (Deep Learning Toolbox)
- Learn About Convolutional Neural Networks (Deep Learning Toolbox)
- Prerequisites for Deep Learning with MATLAB Coder
- Code Generation for Deep Learning Networks with MKL-DNN
- Deep Learning Code Generation on Intel Targets for Different Batch Sizes
- Code Generation for Deep Learning Networks with ARM Compute Library
- Code Generation for Deep Learning on ARM Targets
- Deep Learning Prediction with ARM Compute Using codegen
- Generate Generic C/C++ Code for Deep Learning Networks
- Deep Learning with GPU Coder (GPU Coder)