Tensorflow: Difference between revisions
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]; | ]; | ||
shellHook = '' | shellHook = '' | ||
export LD_LIBRARY_PATH= | export LD_LIBRARY_PATH=${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.cudatoolkit_10_1}/lib:${pkgs.cudnn_cudatoolkit_10_1}/lib:${pkgs.cudatoolkit_10_1.lib}/lib:$LD_LIBRARY_PATH | ||
alias pip="PIP_PREFIX='$(pwd)/_build/pip_packages' TMPDIR='$HOME' \pip" | alias pip="PIP_PREFIX='$(pwd)/_build/pip_packages' TMPDIR='$HOME' \pip" | ||
export PYTHONPATH="$(pwd)/_build/pip_packages/lib/python3.7/site-packages:$PYTHONPATH" | export PYTHONPATH="$(pwd)/_build/pip_packages/lib/python3.7/site-packages:$PYTHONPATH" |
Revision as of 02:04, 23 February 2020
Tensorflow
There several possible ways to install tensorflow. Nixpkgs provides multiple versions, however, it is often desirable to be able to install the latest nightly from pip. This can accomplished in the following ways:
- By making a nix-shell
with import <nixpkgs> {};
mkShell {
name = "tensorflow-cuda-shell";
buildInputs = with python3.pkgs; [
pip
numpy
setuptools
];
shellHook = ''
export LD_LIBRARY_PATH=${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.cudatoolkit_10_1}/lib:${pkgs.cudnn_cudatoolkit_10_1}/lib:${pkgs.cudatoolkit_10_1.lib}/lib:$LD_LIBRARY_PATH
alias pip="PIP_PREFIX='$(pwd)/_build/pip_packages' TMPDIR='$HOME' \pip"
export PYTHONPATH="$(pwd)/_build/pip_packages/lib/python3.7/site-packages:$PYTHONPATH"
export PATH="$(pwd)/_build/pip_packages/bin:$PATH"
unset SOURCE_DATE_EPOCH
'';
}
Within this shell, pip install tf-nightly should work and provide GPU support. The cuda toolkit version can be changed to correspond with the matching tensorflow version.