Merge pull request #164338 from samuela/samuela/cudnn
cudnn: 8.3.0 -> 8.3.2
This commit is contained in:
Samuel Ainsworth
GitHub
commit
7c6eaf9be2
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@ -1,23 +1,29 @@
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# The following version combinations are supported:
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# * cuDNN 7.4.2, cudatoolkit 10.0
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# * cuDNN 7.6.5, cudatoolkit 10.2
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# * cuDNN 8.1.1, cudatoolkit 11.0-11.2
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# * cuDNN 8.3.0, cudatoolkit 11.0-11.5
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# * cuDNN 7.6.5, cudatoolkit 10.0-10.1
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# * cuDNN 8.1.1, cudatoolkit 10.2-11.2
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# * cuDNN 8.3.2, cudatoolkit 10.2-11.5
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{ callPackage
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, cudatoolkit_10
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, cudatoolkit_10_0
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, cudatoolkit_10_1
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, cudatoolkit_10_2
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, cudatoolkit_11
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, cudatoolkit_11_0
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, cudatoolkit_11_1
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, cudatoolkit_11_2
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, cudatoolkit_11_3
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, cudatoolkit_11_4
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, cudatoolkit_11_5
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, fetchurl
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, lib
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}:
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let
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generic = args: callPackage (import ./generic.nix (removeAttrs args [ "cudatoolkit" ])) {
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inherit (args) cudatoolkit;
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};
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urlPrefix = "https://developer.download.nvidia.com/compute/redist/cudnn";
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in
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rec {
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# cuDNN 7.x
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@ -25,53 +31,88 @@ rec {
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cudnn_7_4_cudatoolkit_10_0 = generic rec {
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version = "7.4.2";
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cudatoolkit = cudatoolkit_10_0;
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srcName = "cudnn-${cudatoolkit.majorVersion}-linux-x64-v7.4.2.24.tgz";
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sha256 = "18ys0apiz9afid2s6lvy9qbyi8g66aimb2a7ikl1f3dm09mciprf";
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# See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn_742/cudnn-support-matrix/index.html#cudnn-cuda-hardware-versions__table-cudnn-cuda-hardware-versions.
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minCudaVersion = "9.2.88";
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maxCudaVersion = "10.0.99999";
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mkSrc = _: fetchurl {
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url = "${urlPrefix}/v${version}/cudnn-10.0-linux-x64-v7.4.2.24.tgz";
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hash = "sha256-Lt/IagK1DRfojEeJVaMy5qHoF05+U6NFi06lH68C2qM=";
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};
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};
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# The only overlap between supported and packaged CUDA versions is 10.0.
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# The `cudnn` alias still points to this in all-packages.nix. It should be
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# upgraded at some point.
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cudnn_7_6_cudatoolkit_10_2 = generic rec {
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cudnn_7_6_cudatoolkit_10_0 = generic rec {
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version = "7.6.5";
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cudatoolkit = cudatoolkit_10_2;
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srcName = "cudnn-${cudatoolkit.majorVersion}-linux-x64-v7.6.5.32.tgz";
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sha256 = "084c13vzjdkb5s1996yilybg6dgav1lscjr1xdcgvlmfrbr6f0k0";
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cudatoolkit = cudatoolkit_10_0;
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# See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn_765/cudnn-support-matrix/index.html#cudnn-versions-763-765.
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minCudaVersion = "9.2.148";
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maxCudaVersion = "10.1.243";
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mkSrc = cudatoolkit: fetchurl {
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url = "${urlPrefix}/v${version}/cudnn-${cudatoolkit.majorVersion}-linux-x64-v7.6.5.32.tgz";
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hash = {
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"10.0" = "sha256-KDVeOV8LK5OsLIO2E2CzW6bNA3fkTni+GXtrYbS0kro=";
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"10.1" = "sha256-fq7IA5osMKsLx1jTA1iHZ2k972v0myJIWiwAvy4TbLM=";
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}."${cudatoolkit.majorVersion}";
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};
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};
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cudnn_7_6_cudatoolkit_10 = cudnn_7_6_cudatoolkit_10_2;
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cudnn_7_6_cudatoolkit_10_1 = cudnn_7_6_cudatoolkit_10_0.override { cudatoolkit = cudatoolkit_10_1; };
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# cuDNN 8.x
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# cuDNN 8.1 is still used by tensorflow at the time of writing (2022-02-17).
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# See https://github.com/NixOS/nixpkgs/pull/158218 for more info.
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cudnn_8_1_cudatoolkit_11_0 = generic rec {
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cudnn_8_1_cudatoolkit_10_2 = generic rec {
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version = "8.1.1";
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cudatoolkit = cudatoolkit_11_0;
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# 8.1.0 is compatible with CUDA 11.0-11.2:
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# https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-811/support-matrix/index.html
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srcName = "cudnn-11.2-linux-x64-v8.1.1.33.tgz";
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hash = "sha256-mKh4TpKGLyABjSDCgbMNSgzZUfk2lPZDPM9K6cUCumo=";
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cudatoolkit = cudatoolkit_10_2;
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# See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-811/support-matrix/index.html#cudnn-versions-810-811.
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minCudaVersion = "10.2.00000";
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maxCudaVersion = "11.2.99999";
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mkSrc = cudatoolkit:
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let v = if lib.versions.majorMinor cudatoolkit.version == "10.2" then "10.2" else "11.2"; in
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fetchurl {
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url = "${urlPrefix}/v${version}/cudnn-${v}-linux-x64-v8.1.1.33.tgz";
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hash = {
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"10.2" = "sha256-Kkp7mabpv6aQ6xm7QeSVU/KnpJGls6v8rpAOFmxbbr0=";
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"11.2" = "sha256-mKh4TpKGLyABjSDCgbMNSgzZUfk2lPZDPM9K6cUCumo=";
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}."${v}";
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};
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};
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cudnn_8_1_cudatoolkit_11_1 = cudnn_8_1_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_1; };
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cudnn_8_1_cudatoolkit_11_2 = cudnn_8_1_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_2; };
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cudnn_8_1_cudatoolkit_11 = cudnn_8_1_cudatoolkit_11_2;
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cudnn_8_1_cudatoolkit_11_0 = cudnn_8_1_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_0; };
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cudnn_8_1_cudatoolkit_11_1 = cudnn_8_1_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_1; };
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cudnn_8_1_cudatoolkit_11_2 = cudnn_8_1_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_2; };
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cudnn_8_1_cudatoolkit_10 = cudnn_8_1_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_10; };
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cudnn_8_1_cudatoolkit_11 = cudnn_8_1_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11; };
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# cuDNN 8.3 is necessary for the latest jaxlib, esp. jaxlib-bin. See
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# https://github.com/google/jax/discussions/9455 for more info.
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cudnn_8_3_cudatoolkit_11_0 = generic rec {
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# 8.3.0 is the last version to respect the folder structure that generic.nix
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# expects. Later versions have files in a subdirectory `local_installers`.
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# See eg https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.1/.
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version = "8.3.0";
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cudatoolkit = cudatoolkit_11_0;
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# 8.3.0 is compatible with CUDA 11.0-11.5:
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# https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-830/support-matrix/index.html
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srcName = "cudnn-11.5-linux-x64-v8.3.0.98.tgz";
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hash = "sha256-RMb1rVyxL7dPoMmh58qvTwTXVa3xGi5bbJ5BfaN2srI=";
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};
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cudnn_8_3_cudatoolkit_11_1 = cudnn_8_3_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_1; };
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cudnn_8_3_cudatoolkit_11_2 = cudnn_8_3_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_2; };
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cudnn_8_3_cudatoolkit_11_3 = cudnn_8_3_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_3; };
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cudnn_8_3_cudatoolkit_11_4 = cudnn_8_3_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_4; };
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cudnn_8_3_cudatoolkit_11_5 = cudnn_8_3_cudatoolkit_11_0.override { cudatoolkit = cudatoolkit_11_5; };
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cudnn_8_3_cudatoolkit_11 = cudnn_8_3_cudatoolkit_11_5;
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cudnn_8_3_cudatoolkit_10_2 =
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generic
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rec {
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version = "8.3.2";
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cudatoolkit = cudatoolkit_10_2;
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# See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-832/support-matrix/index.html#cudnn-cuda-hardware-versions.
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minCudaVersion = "10.2.00000";
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maxCudaVersion = "11.5.99999";
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mkSrc = cudatoolkit:
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let v = if lib.versions.majorMinor cudatoolkit.version == "10.2" then "10.2" else "11.5"; in
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fetchurl {
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# Starting at version 8.3.1 there's a new directory layout including
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# a subdirectory `local_installers`.
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url = "https://developer.download.nvidia.com/compute/redist/cudnn/v${version}/local_installers/${v}/cudnn-linux-x86_64-8.3.2.44_cuda${v}-archive.tar.xz";
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hash = {
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"10.2" = "sha256-1vVu+cqM+PketzIQumw9ykm6REbBZhv6/lXB7EC2aaw=";
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"11.5" = "sha256-VQCVPAjF5dHd3P2iNPnvvdzb5DpTsm3AqCxyP6FwxFc=";
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}."${v}";
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};
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}
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;
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cudnn_8_3_cudatoolkit_11_0 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_0; };
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cudnn_8_3_cudatoolkit_11_1 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_1; };
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cudnn_8_3_cudatoolkit_11_2 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_2; };
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cudnn_8_3_cudatoolkit_11_3 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_3; };
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cudnn_8_3_cudatoolkit_11_4 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_4; };
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cudnn_8_3_cudatoolkit_11_5 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11_5; };
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cudnn_8_3_cudatoolkit_10 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_10; };
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cudnn_8_3_cudatoolkit_11 = cudnn_8_3_cudatoolkit_10_2.override { cudatoolkit = cudatoolkit_11; };
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}
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@ -1,11 +1,9 @@
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{ version
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, srcName
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, hash ? null
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, sha256 ? null
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{ minCudaVersion
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, maxCudaVersion
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, mkSrc
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, version
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}:
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assert (hash != null) || (sha256 != null);
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{ stdenv
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, lib
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, cudatoolkit
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@ -25,19 +23,18 @@ stdenv.mkDerivation {
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name = "cudatoolkit-${cudatoolkit.majorVersion}-cudnn-${version}";
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inherit version;
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src = let
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hash_ = if hash != null then { inherit hash; } else { inherit sha256; };
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in fetchurl ({
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# URL from NVIDIA docker containers: https://gitlab.com/nvidia/cuda/blob/centos7/7.0/runtime/cudnn4/Dockerfile
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url = "https://developer.download.nvidia.com/compute/redist/cudnn/v${version}/${srcName}";
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} // hash_);
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# It's often the case that the src depends on the version of cudatoolkit it's
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# being linked against, so we pass in `cudatoolkit` as an argument to `mkSrc`.
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src = mkSrc cudatoolkit;
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nativeBuildInputs = [ addOpenGLRunpath ];
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# Some cuDNN libraries depend on things in cudatoolkit, eg.
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# libcudnn_ops_infer.so.8 tries to load libcublas.so.11. So we need to patch
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# cudatoolkit into RPATH. See also https://github.com/NixOS/nixpkgs/blob/88a2ad974692a5c3638fcdc2c772e5770f3f7b21/pkgs/development/python-modules/jaxlib/bin.nix#L78-L98.
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#
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# Note also that version <=8.3.0 contained a subdirectory "lib64/" but in
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# version 8.3.2 it seems to have been renamed to simply "lib/".
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installPhase = ''
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runHook preInstall
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@ -46,14 +43,16 @@ stdenv.mkDerivation {
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patchelf --set-rpath "''${p:+$p:}${lib.makeLibraryPath [ stdenv.cc.cc cudatoolkit.lib ]}:${cudatoolkit}/lib:\$ORIGIN/" $1
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}
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for lib in lib64/lib*.so; do
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fixRunPath $lib
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for sofile in {lib,lib64}/lib*.so; do
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fixRunPath $sofile
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done
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mkdir -p $out
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cp -a include $out/include
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cp -a lib64 $out/lib64
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[ -d "lib/" ] && cp -a lib $out/lib
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[ -d "lib64/" ] && cp -a lib64 $out/lib64
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'' + lib.optionalString removeStatic ''
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rm -f $out/lib/*.a
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rm -f $out/lib64/*.a
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'' + ''
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runHook postInstall
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@ -77,10 +76,21 @@ stdenv.mkDerivation {
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};
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meta = with lib; {
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# Check that the cudatoolkit version satisfies our min/max constraints (both
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# inclusive). We mark the package as broken if it fails to satisfies the
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# official version constraints (as recorded in default.nix). In some cases
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# you _may_ be able to smudge version constraints, just know that you're
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# embarking into unknown and unsupported territory when doing so.
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broken = let cudaVer = lib.getVersion cudatoolkit; in
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!(
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lib.versionAtLeast cudaVer minCudaVersion
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&& lib.versionAtLeast maxCudaVersion cudaVer
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);
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description = "NVIDIA CUDA Deep Neural Network library (cuDNN)";
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homepage = "https://developer.nvidia.com/cudnn";
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license = licenses.unfree;
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platforms = [ "x86_64-linux" ];
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maintainers = with maintainers; [ mdaiter ];
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maintainers = with maintainers; [ mdaiter samuela ];
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};
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}
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@ -4600,21 +4600,26 @@ with pkgs;
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cudnnPackages = callPackages ../development/libraries/science/math/cudnn { };
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inherit (cudnnPackages)
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cudnn_7_4_cudatoolkit_10_0
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cudnn_7_6_cudatoolkit_10_2
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cudnn_7_6_cudatoolkit_10
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cudnn_7_6_cudatoolkit_10_0
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cudnn_7_6_cudatoolkit_10_1
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cudnn_8_1_cudatoolkit_10_2
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cudnn_8_1_cudatoolkit_11_0
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cudnn_8_1_cudatoolkit_11_1
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cudnn_8_1_cudatoolkit_11_2
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cudnn_8_1_cudatoolkit_10
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cudnn_8_1_cudatoolkit_11
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cudnn_8_3_cudatoolkit_10_2
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cudnn_8_3_cudatoolkit_11_0
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cudnn_8_3_cudatoolkit_11_1
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cudnn_8_3_cudatoolkit_11_2
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cudnn_8_3_cudatoolkit_11_3
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cudnn_8_3_cudatoolkit_11_4
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cudnn_8_3_cudatoolkit_11_5
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cudnn_8_3_cudatoolkit_10
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cudnn_8_3_cudatoolkit_11;
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cudnn = cudnn_7_6_cudatoolkit_10;
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# TODO(samuela): This is old and should be upgraded to 8.3 at some point.
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cudnn = cudnn_7_6_cudatoolkit_10_1;
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cutensorPackages = callPackages ../development/libraries/science/math/cutensor { };
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inherit (cutensorPackages)
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