![]() For cuda 8, the dev version of skcuda (will be released as 0.5.2) is needed for cusolver: pip install pycuda pip install git+. Quick install pip install pycuda scikit-cuda. Required for some extra operations on the GPU like fft and solvers. Required for GPU/CPU code generation on CUDA and OpenCL devices (see: GpuArray Backend). Highly recommended Required for GPU code generation/execution on NVIDIA gpus. LaTeX and dvipng are also necessary for math to show up as images. Theano can fall back on a NumPy-based Python execution model, but a C compiler allows for vastly faster execution.įor building the documentation. GCC compiler with g++ (version >= 4.2.*), and Python development files Alternatively, we suggest to install OpenBLAS, with the development headers ( -dev, -devel, depending on your Linux distribution). Recommended: MKL, which is free through Conda with mkl-service package. Python = 2.7* or ( >= 3.4 and = 1.9.1 = 0.14 =0.8 could work, but earlier versions have known bugs with sparse matrices.īLAS installation (with Level 3 functionality) We only support the installation of the requirements through conda. ![]() ![]() If you want to install the bleeding-edge or development version of Theano from GitHub, please make sure you are reading the latest version of this page. ![]()
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