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Workflow for Deep Learning Code Generation with MATLAB Coder

With MATLAB® Coder™, you can generate code for prediction from a pretrained neural network, 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 third-party libraries.

  1. 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.

  2. Load a network object from the trained network.

    See Load Pretrained Networks for Code Generation.

  3. Generate C++ code for the trained network by using codegen or the MATLAB Coder app. See:

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