Please specify the CUDA SDK version you want to use. Default is ĭo you wish to build TensorFlow with CUDA support? : YĬUDA support will be enabled for TensorFlow.
Please input the desired Python library path to use. Starting local Bazel server and connecting to it.
configure.py (your session mayĭiffer): View sample configuration session Theįollowing shows a sample run of python. This script prompts you for the location of TensorFlow dependencies and asks forĪdditional build configuration options (compiler flags, for example). If you need to change the configuration, run the. Key Point: If you're having build problems on the latest development branch, tryĪ release branch that is known to work. Git checkout branch_name # r1.9, r1.10, etc. The repo defaults to the master development branch. ( git is installed with MSYS2): git clone cd tensorflow See the Windows GPU support guide to install the drivers andĪdditional software required to run TensorFlow on a GPU. Note: TensorFlow is tested against the Visual Studio 2019. Microsoft Visual C++ 2019 Redistributable.Select Redistributables and Build Tools,.If MSYS2 is installed to C:\msys64, addĬ:\msys64\usr\bin to your %PATH% environment variable. Install MSYS2 for the bin tools needed toīuild TensorFlow. Install Bazel, the build tool used to compileĪdd the location of the Bazel executable to your %PATH% environment variable. Install the TensorFlow pip package dependencies: pip3 install -U six numpy wheel packaging pip3 install -U keras_preprocessing -no-depsįile under REQUIRED_PACKAGES.
Select pip as an optional feature and add it to your %PATH% environmental Install Python and the TensorFlow package dependencies Install the following build tools to configure your Windows developmentĮnvironment. Note: We already provide well-tested, pre-built Build a TensorFlow pip package from source and install it on Windows.
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