How do I build TensorFlow Lite for Deep Learning C++ code generation and deployment?
I see a few deep learning networks supported for code generation using MATLAB Coder:
- Deep Learning Networks and Layers Supported for C++ Code Generation
I’m looking to generate code from my deep learning network (like ResNet, GoogLeNet, SqueezeNet, VGG-16/19, etc) to run on boards supported by TensorFlow Lite using MATLAB Coder. What are the steps to do this?
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Use on Windows targets (For Release 2022b and newer)
To generate and run C++ code that performs inference with TensorFlow Lite models on Windows targets, you must have the?TensorFlow Lite library on the Windows hardware. To build the TensorFlow Lite library version 2.4.1 for Windows targets on your host Windows platform, execute the following steps.
Requirements:
- To build the TensorFlow Lite dynamic library, you must install bazel (version 3.1.0 to 3.99.0) on the host Windows computer. See this link for more information: Installing Bazel on Windows
- You may need to add PYTHON_BIN_PATH to the bazel command if Bazel is not able to find the python paths
- Start the process of bazel-build from the Developer Command Prompt terminals provided with Visual Studio installations
Build Instructions:
1. Open Command Prompt
2. Execute the following commands:
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