{"id":13658406,"url":"https://github.com/mind/wheels","last_synced_at":"2025-04-04T09:08:05.397Z","repository":{"id":88708627,"uuid":"92563888","full_name":"mind/wheels","owner":"mind","description":"Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)","archived":false,"fork":false,"pushed_at":"2019-07-15T09:57:22.000Z","size":40,"stargazers_count":884,"open_issues_count":20,"forks_count":107,"subscribers_count":56,"default_branch":"master","last_synced_at":"2025-03-28T08:05:56.321Z","etag":null,"topics":["ai","avx","avx2","cuda","fma","gpu","machine-learning","ml","optimization","sse41","sse42","tensorflow","wheel"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mind.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2017-05-27T02:22:08.000Z","updated_at":"2025-03-10T17:50:17.000Z","dependencies_parsed_at":null,"dependency_job_id":"1aab307f-6506-4b4f-965d-241d6653949f","html_url":"https://github.com/mind/wheels","commit_stats":null,"previous_names":[],"tags_count":62,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mind%2Fwheels","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mind%2Fwheels/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mind%2Fwheels/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mind%2Fwheels/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mind","download_url":"https://codeload.github.com/mind/wheels/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247149501,"owners_count":20891954,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","avx","avx2","cuda","fma","gpu","machine-learning","ml","optimization","sse41","sse42","tensorflow","wheel"],"created_at":"2024-08-02T05:00:59.342Z","updated_at":"2025-04-04T09:08:05.373Z","avatar_url":"https://github.com/mind.png","language":null,"funding_links":[],"categories":["Others (28)"],"sub_categories":[],"readme":"# TensorFlow Optimized Wheels\n\nCustom builds for TensorFlow with platform optimizations, including SSE, AVX and FMA. If you are seeing messages like the following with the stock `pip install tensorflow`, you've come to the right place.\n\n```\nThe TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.\nThe TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.\nThe TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.\nThe TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.\n\nor:\nYour CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA\n```\n\nThese wheels are built for use on [TinyMind](https://www.tinymind.com), the cloud machine learning platform. If you want to install them on your own Linux box (Ubuntu 16.04 LTS), you can do so with:\n\n```sh\n# RELEASE is the git tag like tf1.1-cpu. WHEEL is the full wheel name.\npip --no-cache-dir install https://github.com/mind/wheels/releases/download/{RELEASE}/{WHEEL}\n```\n\nThe list of all wheels can be found in the [releases page](https://github.com/mind/wheels/releases).\n\n## Versions\n\nClick on the links below to jump to specific release versions. Again, they are built for Ubuntu 16.04 LTS unless otherwise noted.\n\nTF | Builds\n-----------|-------\n1.1 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.1-cpu), [GPU](https://github.com/mind/wheels/releases/tag/tf1.1-gpu)\n1.2 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.2-cpu), [GPU (Python 3.6 only)](https://github.com/mind/wheels/releases/tag/tf1.2-gpu)\n1.2.1 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.2.1-cpu), [GPU](https://github.com/mind/wheels/releases/tag/tf1.2.1-gpu)\n1.3 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.3-cpu), [GPU with MPI](https://github.com/mind/wheels/releases/tag/tf1.3-gpu)\n1.3.1 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.3.1-cpu), [CPU Debug](https://github.com/mind/wheels/releases/tag/tf1.3-cpu-debug), [GPU](https://github.com/mind/wheels/releases/tag/tf1.3.1-gpu), [GPU with MPI](https://github.com/mind/wheels/releases/tag/tf1.3-gpu-mpi)\n1.4 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.4-cpu), [CPU Debug](https://github.com/mind/wheels/releases/tag/tf1.4-cpu-debug), [CPU macOS](https://github.com/mind/wheels/releases/tag/tf1.4-cpu-mac), GPU ([CUDA 8](https://github.com/mind/wheels/releases/tag/tf1.4-gpu), [CUDA 9 for Compute 3.7](https://github.com/mind/wheels/releases/tag/tf1.4-gpu-cuda9-37), [CUDA 9 for Compute 3.7/6.0/7.0](https://github.com/mind/wheels/releases/tag/tf1.4-gpu-cuda9), [CUDA 9 generic](https://github.com/mind/wheels/releases/tag/tf1.4-gpu-cuda9-generic), [CUDA 9 without MKL](https://github.com/mind/wheels/releases/tag/tf1.4-gpu-cuda9-nomkl))\n1.4.1 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.4.1-cpu), GPU ([CUDA 8](https://github.com/mind/wheels/releases/tag/tf1.4.1-gpu), [CUDA 9](https://github.com/mind/wheels/releases/tag/tf1.4.1-gpu-cuda9), [CUDA 9.1](https://github.com/mind/wheels/releases/tag/tf1.4.1-gpu-cuda91))\n1.5 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.5-cpu), GPU ([CUDA 9](https://github.com/mind/wheels/releases/tag/tf1.5-gpu), [CUDA 9 without MKL](https://github.com/mind/wheels/releases/tag/tf1.5-gpu-nomkl), [CUDA 9.1](https://github.com/mind/wheels/releases/tag/tf1.5-gpu-cuda91), [CUDA 9.1 without MKL](https://github.com/mind/wheels/releases/tag/tf1.5-gpu-cuda91-nomkl))\n1.6 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.6-cpu), GPU ([CUDA 9.1](https://github.com/mind/wheels/releases/tag/tf1.6-gpu-cuda91), [CUDA 9.1 without MKL](https://github.com/mind/wheels/releases/tag/tf1.6-gpu-cuda91-nomkl))\n1.7 | [CPU](https://github.com/mind/wheels/releases/tag/tf1.7-cpu), GPU ([CUDA 9](https://github.com/mind/wheels/releases/tag/tf1.7-gpu-nomkl), [CUDA 9.1, cuDNN 7.1](https://github.com/mind/wheels/releases/tag/tf1.7-gpu-cuda91-nomkl))\n\nPlease note that your machine needs to have a relatively new Intel CPU (and Nvidia GPU if you use the GPU version) to be compatible with the wheels below. If the hardware is not up-to-date, the wheels will not work.\n\nWheels for TensorFlow 1.4.1 and above contain support for GCP, S3 and Hadoop. Compilation flags include:\n\n```\n--config=opt --config=cuda --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0 --copt=-mavx --copt=-msse4.1 --copt=-msse4.2 --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both\n```\n\nWheels you will most likely need are listed below. Need something or a wheel doesn't work for you? File an issue. (Unfortunately, we won't be able to accommodate for requests for Windows wheels, as we don't have Windows machines ourselves.)\n\nVersion | Python | Arch | Link\n--------|--------|------|-----\n1.1 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.1-cpu/tensorflow-1.1.0-cp27-cp27mu-linux_x86_64.whl\n1.1 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.1-cpu/tensorflow-1.1.0-cp35-cp35m-linux_x86_64.whl\n1.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.1-cpu/tensorflow-1.1.0-cp36-cp36m-linux_x86_64.whl\n1.1 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.1-gpu/tensorflow-1.1.0-cp27-cp27mu-linux_x86_64.whl\n1.1 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.1-gpu/tensorflow-1.1.0-cp35-cp35m-linux_x86_64.whl\n1.1 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.1-gpu/tensorflow-1.1.0-cp36-cp36m-linux_x86_64.whl\n1.2 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.2-cpu/tensorflow-1.2.0-cp27-cp27mu-linux_x86_64.whl\n1.2 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.2-cpu/tensorflow-1.2.0-cp35-cp35m-linux_x86_64.whl\n1.2 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.2-cpu/tensorflow-1.2.0-cp36-cp36m-linux_x86_64.whl\n1.2 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.2-gpu/tensorflow-1.2.0-cp36-cp36m-linux_x86_64.whl\n1.2.1 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.2.1-cpu/tensorflow-1.2.1-cp27-cp27mu-linux_x86_64.whl\n1.2.1 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.2.1-cpu/tensorflow-1.2.1-cp35-cp35m-linux_x86_64.whl\n1.2.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.2.1-cpu/tensorflow-1.2.1-cp36-cp36m-linux_x86_64.whl\n1.2.1 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.2.1-gpu/tensorflow-1.2.1-cp27-cp27mu-linux_x86_64.whl\n1.2.1 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.2.1-gpu/tensorflow-1.2.1-cp35-cp35m-linux_x86_64.whl\n1.2.1 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.2.1-gpu/tensorflow-1.2.1-cp36-cp36m-linux_x86_64.whl\n1.3 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.3-cpu/tensorflow-1.3.0-cp27-cp27mu-linux_x86_64.whl\n1.3 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.3-cpu/tensorflow-1.3.0-cp35-cp35m-linux_x86_64.whl\n1.3 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.3-cpu/tensorflow-1.3.0-cp36-cp36m-linux_x86_64.whl\n1.3 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.3-gpu/tensorflow-1.3.0-cp27-cp27mu-linux_x86_64.whl\n1.3 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.3-gpu/tensorflow-1.3.0-cp35-cp35m-linux_x86_64.whl\n1.3 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.3-gpu/tensorflow-1.3.0-cp36-cp36m-linux_x86_64.whl\n1.3.1 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp27-cp27mu-linux_x86_64.whl\n1.3.1 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp35-cp35m-linux_x86_64.whl\n1.3.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.3.1-cpu/tensorflow-1.3.1-cp36-cp36m-linux_x86_64.whl\n1.3.1 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.3.1-gpu/tensorflow-1.3.1-cp27-cp27mu-linux_x86_64.whl\n1.3.1 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.3.1-gpu/tensorflow-1.3.1-cp35-cp35m-linux_x86_64.whl\n1.3.1 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.3.1-gpu/tensorflow-1.3.1-cp36-cp36m-linux_x86_64.whl\n1.4 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.4-cpu/tensorflow-1.4.0-cp27-cp27mu-linux_x86_64.whl\n1.4 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.4-cpu/tensorflow-1.4.0-cp35-cp35m-linux_x86_64.whl\n1.4 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.4-cpu/tensorflow-1.4.0-cp36-cp36m-linux_x86_64.whl\n1.4 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.4-gpu/tensorflow-1.4.0-cp27-cp27mu-linux_x86_64.whl\n1.4 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.4-gpu/tensorflow-1.4.0-cp35-cp35m-linux_x86_64.whl\n1.4 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.4-gpu/tensorflow-1.4.0-cp36-cp36m-linux_x86_64.whl\n1.4.1 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.4.1-cpu/tensorflow-1.4.1-cp27-cp27mu-linux_x86_64.whl\n1.4.1 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.4.1-cpu/tensorflow-1.4.1-cp35-cp35m-linux_x86_64.whl\n1.4.1 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.4.1-cpu/tensorflow-1.4.1-cp36-cp36m-linux_x86_64.whl\n1.4.1 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.4.1-gpu/tensorflow-1.4.1-cp27-cp27mu-linux_x86_64.whl\n1.4.1 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.4.1-gpu/tensorflow-1.4.1-cp35-cp35m-linux_x86_64.whl\n1.4.1 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.4.1-gpu/tensorflow-1.4.1-cp36-cp36m-linux_x86_64.whl\n1.5 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.5-cpu/tensorflow-1.5.0-cp27-cp27mu-linux_x86_64.whl\n1.5 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.5-cpu/tensorflow-1.5.0-cp35-cp35m-linux_x86_64.whl\n1.5 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.5-cpu/tensorflow-1.5.0-cp36-cp36m-linux_x86_64.whl\n1.5 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.5-gpu/tensorflow-1.5.0-cp27-cp27mu-linux_x86_64.whl\n1.5 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.5-gpu/tensorflow-1.5.0-cp35-cp35m-linux_x86_64.whl\n1.5 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.5-gpu/tensorflow-1.5.0-cp36-cp36m-linux_x86_64.whl\n1.6 | 2.7 | CPU | https://github.com/mind/wheels/releases/download/tf1.6-cpu/tensorflow-1.6.0-cp27-cp27mu-linux_x86_64.whl\n1.6 | 3.5 | CPU | https://github.com/mind/wheels/releases/download/tf1.6-cpu/tensorflow-1.6.0-cp35-cp35m-linux_x86_64.whl\n1.6 | 3.6 | CPU | https://github.com/mind/wheels/releases/download/tf1.6-cpu/tensorflow-1.6.0-cp36-cp36m-linux_x86_64.whl\n1.6 | 2.7 | GPU | https://github.com/mind/wheels/releases/download/tf1.6-gpu-cuda91/tensorflow-1.6.0-cp27-cp27mu-linux_x86_64.whl\n1.6 | 3.5 | GPU | https://github.com/mind/wheels/releases/download/tf1.6-gpu-cuda91/tensorflow-1.6.0-cp35-cp35m-linux_x86_64.whl\n1.6 | 3.6 | GPU | https://github.com/mind/wheels/releases/download/tf1.6-gpu-cuda91/tensorflow-1.6.0-cp36-cp36m-linux_x86_64.whl\n\n## Help!\n\nThis section contains tips for debugging your setup. Seriously though, try [TinyMind](https://www.tinymind.com) out and you will never need to waste time debugging again. We also have [Docker images](https://hub.docker.com/r/tinymind/tensorflow/) that you can use on your own machines. If this section doesn't solve your problem, be sure to file an issue.\n\n### CUDA\n\nDifferent TensorFlow versions support/require different CUDA versions:\n\nTF | CUDA | cuDNN | Compute Capability\n-----------|------|-------|-------------------\n1.1, 1.2 | 8.0 | 5.1 | 3.7 (K80)\n1.2.1-1.3.1 | 8.0 | 6.0 | 3.7\n1.4 | 8.0/9.0 | 6.0/7.0 | 3.7, 6.0 (P100), 7.0 (V100)\n1.4.1 | 8.0/9.0/9.1 | 6.0/7.0 | 3.7, 6.0, 7.0\n1.5 | 9.0/9.1 | 7.0 | 3.7, 6.0, 7.0\n1.6 | 9.1 | 7.0 | 3.7, 6.0, 7.0\n1.7 | 9.0/9.1 | 7.0/7.1 | 3.7, 6.0, 7.0\n\nTensorFlow \u003c 1.4 doesn't work with CUDA 9, the current version. Instead of `sudo apt-get install cuda`, you need to do `sudo apt-get install cuda-8-0`. CUDA 8 variants of TensorFlow 1.4 go with cuDNN 6.0, and CUDA 9.x variants go with cuDNN 7.x.\n\n```sh\n# Install CUDA 8\ncurl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb\nsudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb\nsudo apt-get update\nsudo apt-get install cuda-8-0\n\n# Install CUDA 9\ncurl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb\nsudo dpkg -i cuda-repo-ubuntu1604_9.0.176-1_amd64.deb\nsudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub\nsudo apt-get update\nsudo apt-get install cuda\n```\n\nMake sure that CUDA-related environment variables are set properly:\n\n```sh\necho 'export CUDA_HOME=/usr/local/cuda' \u003e\u003e ~/.bashrc\necho 'export PATH=$PATH:$CUDA_HOME/bin' \u003e\u003e ~/.bashrc\necho 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64' \u003e\u003e ~/.bashrc\n. ~/.bashrc\n```\n\n[Download the correct cuDNN](https://developer.nvidia.com/cudnn) and install it as follows:\n\n```sh\n# The cuDNN tar file.\ntar xzvf cudnn-9.0-linux-x64-v7.0.tgz\nsudo cp cuda/lib64/* /usr/local/cuda/lib64/\nsudo cp cuda/include/cudnn.h /usr/local/cuda/include/\n```\n\nMissing `libcupti` library? Install it and add it to your `PATH`.\n\n```sh\nsudo apt-get install libcupti-dev\necho 'export LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH' \u003e\u003e ~/.bashrc\n```\n\n### TensorRT\n\nCertain wheels support TensorRT. To install TensorRT, first download it from [Nvidia's website](https://developer.nvidia.com/tensorrt), and then run:\n\n```sh\nsudo dpkg -i nv-tensorrt-repo-ubuntu1604-ga-cuda9.0-trt3.0.4-20180208_1-1_amd64.deb\nsudo apt-get update\nsudo apt-get install tensorrt\n```\n\n### MKL\n\nMKL is [Intel's deep learning kernel library](https://github.com/01org/mkl-dnn), which makes training neural nets on CPU much faster. If you don't have it, install it like the following:\n\n```sh\n# If you don't have cmake\nsudo apt install cmake\n\ngit clone https://github.com/01org/mkl-dnn.git\ncd mkl-dnn/scripts \u0026\u0026 ./prepare_mkl.sh \u0026\u0026 cd ..\nmkdir -p build \u0026\u0026 cd build \u0026\u0026 cmake .. \u0026\u0026 make\nsudo make install\n\necho 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib' \u003e\u003e ~/.bashrc\n```\n\n### Glibc 2.23\n\nPlease note that Ubuntu 16.04 LTS is the intended environment. If you have an old OS, you may run into issues with old glibc versions. You may want to check out [discussions here](https://github.com/mind/wheels/issues/7) to see if they would help.\n\n### MPI\n\nUsing a wheel with MPI support? Be sure to run `sudo apt-get install mpich`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmind%2Fwheels","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmind%2Fwheels","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmind%2Fwheels/lists"}