- Macos cmake command not found how to#
- Macos cmake command not found install#
- Macos cmake command not found windows 10#
The native flatc binary needs to be provided along with the DTFLITE_HOST_TOOLS_DIR= pointing to the directory containing tensorflow_src/tensorflow/lite/tools/cmake/native_tools/flatbuffersįor the TF Lite cross-compilation itself, additional parameter to a directory containing other natively-built tools instead of the CMakeīuild directory): cmake -DCMAKE_INSTALL_PREFIX=.
Macos cmake command not found install#
It is also possible to install the flatc to a custom installation location tensorflow_src/tensorflow/lite/tools/cmake/native_tools/flatbuffers mkdir flatc-native-build & cd flatc-native-buildĬmake. Tensorflow/lite/tools/cmake/native_tools/flatbuffers to build the flatcĬompiler with CMake in advance in a separate build directory using the host For this purpose, there is a CMakeLists located in Specifics of kernel (unit) tests cross-compilationĬross-compilation of the unit tests requires flatc compiler for the hostĪrchitecture.
cmake -DCMAKE_TOOLCHAIN_FILE=/build/cmake/ \ DCMAKE_TOOLCHAIN_FILE flag mentioned above. tensorflow/lite/įor Android cross-compilation, you need to installĪndroid NDK and provide the NDK path with ARM64 SDK or NDK in Android's case) with -DCMAKE_TOOLCHAIN_FILEįlag. In order to cross-compile the TF Lite, you namely need to provide the path to You can use CMake to build binaries for ARM64 or Android target architectures. To learn more about handling and locating packages. DFlatbuffers_DIR=/lib/cmake/flatbuffers \ tensorflow_src/tensorflow/lite -DTFLITE_ENABLE_INSTALL=ON \ Variables to point to your library installations. Use the -DCMAKE_FIND_PACKAGE_PREFER_CONFIG=ON and set the _DIR These will also need to used by the project that depends on TF Lite. You should ideally also provide your own versions of library dependencies. To build an installable package that can be used as a dependency by anotherĬMake project with find_package(tensorflow-lite CONFIG), use the tensorflow_src/tensorflow/lite -DTFLITE_KERNEL_TEST=on Unit test cross-compilation specifics can beįound in the next subsection. In order to be able to run kernel tests, you need to provide tensorflow_src/tensorflow/lite -DCMAKE_BUILD_TYPE=Debug If you need to produce a debug build which has symbol information, you need to Your workstation, simply run the following command. It generates an optimized release binary by default. Run CMake tool with configurations Release build Create CMake build directory mkdir tflite_build Note: If you're using the TensorFlow Docker image, the repo is already Clone TensorFlow repository git clone tensorflow_src The official cmake installation guide Step 2. On Ubuntu, you can simply run the following Note: This feature is available since version 2.4.
Macos cmake command not found windows 10#
, macOS Catalina (x86_64), Windows 10 and TensorFlow devel Docker image The following instructions have been tested on Ubuntu 16.04.3 64-bit PC (AMD64)
Macos cmake command not found how to#
This page describes how to build and use the TensorFlow Lite library with
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