//! `uv-torch` is a library for determining the appropriate PyTorch index based on the operating //! system and CUDA driver version. //! //! This library is derived from `light-the-torch` by Philipp Meier, which is available under the //! following BSD-3 Clause license: //! //! ```text //! BSD 3-Clause License //! //! Copyright (c) 2020, Philip Meier //! All rights reserved. //! //! Redistribution and use in source and binary forms, with or without //! modification, are permitted provided that the following conditions are met: //! //! 1. Redistributions of source code must retain the above copyright notice, this //! list of conditions and the following disclaimer. //! //! 2. Redistributions in binary form must reproduce the above copyright notice, //! this list of conditions and the following disclaimer in the documentation //! and/or other materials provided with the distribution. //! //! 3. Neither the name of the copyright holder nor the names of its //! contributors may be used to endorse or promote products derived from //! this software without specific prior written permission. //! //! THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" //! AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE //! IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE //! DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE //! FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL //! DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR //! SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER //! CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, //! OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE //! OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. //! ``` use std::str::FromStr; use std::sync::LazyLock; use either::Either; use url::Url; use uv_distribution_types::IndexUrl; use uv_normalize::PackageName; use uv_pep440::Version; use uv_platform_tags::Os; use crate::{Accelerator, AcceleratorError}; /// The strategy to use when determining the appropriate PyTorch index. #[derive(Debug, Copy, Clone, Eq, PartialEq, serde::Deserialize, serde::Serialize)] #[cfg_attr(feature = "clap", derive(clap::ValueEnum))] #[cfg_attr(feature = "schemars", derive(schemars::JsonSchema))] #[serde(rename_all = "kebab-case")] pub enum TorchMode { /// Select the appropriate PyTorch index based on the operating system and CUDA driver version. Auto, /// Use the CPU-only PyTorch index. Cpu, /// Use the PyTorch index for CUDA 12.8. Cu128, /// Use the PyTorch index for CUDA 12.6. Cu126, /// Use the PyTorch index for CUDA 12.5. Cu125, /// Use the PyTorch index for CUDA 12.4. Cu124, /// Use the PyTorch index for CUDA 12.3. Cu123, /// Use the PyTorch index for CUDA 12.2. Cu122, /// Use the PyTorch index for CUDA 12.1. Cu121, /// Use the PyTorch index for CUDA 12.0. Cu120, /// Use the PyTorch index for CUDA 11.8. Cu118, /// Use the PyTorch index for CUDA 11.7. Cu117, /// Use the PyTorch index for CUDA 11.6. Cu116, /// Use the PyTorch index for CUDA 11.5. Cu115, /// Use the PyTorch index for CUDA 11.4. Cu114, /// Use the PyTorch index for CUDA 11.3. Cu113, /// Use the PyTorch index for CUDA 11.2. Cu112, /// Use the PyTorch index for CUDA 11.1. Cu111, /// Use the PyTorch index for CUDA 11.0. Cu110, /// Use the PyTorch index for CUDA 10.2. Cu102, /// Use the PyTorch index for CUDA 10.1. Cu101, /// Use the PyTorch index for CUDA 10.0. Cu100, /// Use the PyTorch index for CUDA 9.2. Cu92, /// Use the PyTorch index for CUDA 9.1. Cu91, /// Use the PyTorch index for CUDA 9.0. Cu90, /// Use the PyTorch index for CUDA 8.0. Cu80, /// Use the PyTorch index for ROCm 6.3. #[serde(rename = "rocm6.3")] #[clap(name = "rocm6.3")] Rocm63, /// Use the PyTorch index for ROCm 6.2.4. #[serde(rename = "rocm6.2.4")] #[clap(name = "rocm6.2.4")] Rocm624, /// Use the PyTorch index for ROCm 6.2. #[serde(rename = "rocm6.2")] #[clap(name = "rocm6.2")] Rocm62, /// Use the PyTorch index for ROCm 6.1. #[serde(rename = "rocm6.1")] #[clap(name = "rocm6.1")] Rocm61, /// Use the PyTorch index for ROCm 6.0. #[serde(rename = "rocm6.0")] #[clap(name = "rocm6.0")] Rocm60, /// Use the PyTorch index for ROCm 5.7. #[serde(rename = "rocm5.7")] #[clap(name = "rocm5.7")] Rocm57, /// Use the PyTorch index for ROCm 5.6. #[serde(rename = "rocm5.6")] #[clap(name = "rocm5.6")] Rocm56, /// Use the PyTorch index for ROCm 5.5. #[serde(rename = "rocm5.5")] #[clap(name = "rocm5.5")] Rocm55, /// Use the PyTorch index for ROCm 5.4.2. #[serde(rename = "rocm5.4.2")] #[clap(name = "rocm5.4.2")] Rocm542, /// Use the PyTorch index for ROCm 5.4. #[serde(rename = "rocm5.4")] #[clap(name = "rocm5.4")] Rocm54, /// Use the PyTorch index for ROCm 5.3. #[serde(rename = "rocm5.3")] #[clap(name = "rocm5.3")] Rocm53, /// Use the PyTorch index for ROCm 5.2. #[serde(rename = "rocm5.2")] #[clap(name = "rocm5.2")] Rocm52, /// Use the PyTorch index for ROCm 5.1.1. #[serde(rename = "rocm5.1.1")] #[clap(name = "rocm5.1.1")] Rocm511, /// Use the PyTorch index for ROCm 4.2. #[serde(rename = "rocm4.2")] #[clap(name = "rocm4.2")] Rocm42, /// Use the PyTorch index for ROCm 4.1. #[serde(rename = "rocm4.1")] #[clap(name = "rocm4.1")] Rocm41, /// Use the PyTorch index for ROCm 4.0.1. #[serde(rename = "rocm4.0.1")] #[clap(name = "rocm4.0.1")] Rocm401, } /// The strategy to use when determining the appropriate PyTorch index. #[derive(Debug, Clone, Eq, PartialEq)] pub enum TorchStrategy { /// Select the appropriate PyTorch index based on the operating system and CUDA driver version. Auto { os: Os, driver_version: Version }, /// Use the specified PyTorch index. Backend(TorchBackend), } impl TorchStrategy { /// Determine the [`TorchStrategy`] from the given [`TorchMode`], [`Os`], and [`Accelerator`]. pub fn from_mode(mode: TorchMode, os: &Os) -> Result { match mode { TorchMode::Auto => { if let Some(Accelerator::Cuda { driver_version }) = Accelerator::detect()? { Ok(Self::Auto { os: os.clone(), driver_version: driver_version.clone(), }) } else { Ok(Self::Backend(TorchBackend::Cpu)) } } TorchMode::Cpu => Ok(Self::Backend(TorchBackend::Cpu)), TorchMode::Cu128 => Ok(Self::Backend(TorchBackend::Cu128)), TorchMode::Cu126 => Ok(Self::Backend(TorchBackend::Cu126)), TorchMode::Cu125 => Ok(Self::Backend(TorchBackend::Cu125)), TorchMode::Cu124 => Ok(Self::Backend(TorchBackend::Cu124)), TorchMode::Cu123 => Ok(Self::Backend(TorchBackend::Cu123)), TorchMode::Cu122 => Ok(Self::Backend(TorchBackend::Cu122)), TorchMode::Cu121 => Ok(Self::Backend(TorchBackend::Cu121)), TorchMode::Cu120 => Ok(Self::Backend(TorchBackend::Cu120)), TorchMode::Cu118 => Ok(Self::Backend(TorchBackend::Cu118)), TorchMode::Cu117 => Ok(Self::Backend(TorchBackend::Cu117)), TorchMode::Cu116 => Ok(Self::Backend(TorchBackend::Cu116)), TorchMode::Cu115 => Ok(Self::Backend(TorchBackend::Cu115)), TorchMode::Cu114 => Ok(Self::Backend(TorchBackend::Cu114)), TorchMode::Cu113 => Ok(Self::Backend(TorchBackend::Cu113)), TorchMode::Cu112 => Ok(Self::Backend(TorchBackend::Cu112)), TorchMode::Cu111 => Ok(Self::Backend(TorchBackend::Cu111)), TorchMode::Cu110 => Ok(Self::Backend(TorchBackend::Cu110)), TorchMode::Cu102 => Ok(Self::Backend(TorchBackend::Cu102)), TorchMode::Cu101 => Ok(Self::Backend(TorchBackend::Cu101)), TorchMode::Cu100 => Ok(Self::Backend(TorchBackend::Cu100)), TorchMode::Cu92 => Ok(Self::Backend(TorchBackend::Cu92)), TorchMode::Cu91 => Ok(Self::Backend(TorchBackend::Cu91)), TorchMode::Cu90 => Ok(Self::Backend(TorchBackend::Cu90)), TorchMode::Cu80 => Ok(Self::Backend(TorchBackend::Cu80)), TorchMode::Rocm63 => Ok(Self::Backend(TorchBackend::Rocm63)), TorchMode::Rocm624 => Ok(Self::Backend(TorchBackend::Rocm624)), TorchMode::Rocm62 => Ok(Self::Backend(TorchBackend::Rocm62)), TorchMode::Rocm61 => Ok(Self::Backend(TorchBackend::Rocm61)), TorchMode::Rocm60 => Ok(Self::Backend(TorchBackend::Rocm60)), TorchMode::Rocm57 => Ok(Self::Backend(TorchBackend::Rocm57)), TorchMode::Rocm56 => Ok(Self::Backend(TorchBackend::Rocm56)), TorchMode::Rocm55 => Ok(Self::Backend(TorchBackend::Rocm55)), TorchMode::Rocm542 => Ok(Self::Backend(TorchBackend::Rocm542)), TorchMode::Rocm54 => Ok(Self::Backend(TorchBackend::Rocm54)), TorchMode::Rocm53 => Ok(Self::Backend(TorchBackend::Rocm53)), TorchMode::Rocm52 => Ok(Self::Backend(TorchBackend::Rocm52)), TorchMode::Rocm511 => Ok(Self::Backend(TorchBackend::Rocm511)), TorchMode::Rocm42 => Ok(Self::Backend(TorchBackend::Rocm42)), TorchMode::Rocm41 => Ok(Self::Backend(TorchBackend::Rocm41)), TorchMode::Rocm401 => Ok(Self::Backend(TorchBackend::Rocm401)), } } /// Returns `true` if the [`TorchStrategy`] applies to the given [`PackageName`]. pub fn applies_to(&self, package_name: &PackageName) -> bool { matches!( package_name.as_str(), "torch" | "torch-model-archiver" | "torch-tb-profiler" | "torcharrow" | "torchaudio" | "torchcsprng" | "torchdata" | "torchdistx" | "torchserve" | "torchtext" | "torchvision" | "pytorch-triton" | "pytorch-triton-rocm" | "pytorch-triton-xpu" ) } /// Return the appropriate index URLs for the given [`TorchStrategy`]. pub fn index_urls(&self) -> impl Iterator { match self { TorchStrategy::Auto { os, driver_version } => { // If this is a GPU-enabled package, and CUDA drivers are installed, use PyTorch's CUDA // indexes. // // See: https://github.com/pmeier/light-the-torch/blob/33397cbe45d07b51ad8ee76b004571a4c236e37f/light_the_torch/_patch.py#L36-L49 match os { Os::Manylinux { .. } | Os::Musllinux { .. } => Either::Left(Either::Left( LINUX_DRIVERS .iter() .filter_map(move |(backend, version)| { if driver_version >= version { Some(backend.index_url()) } else { None } }) .chain(std::iter::once(TorchBackend::Cpu.index_url())), )), Os::Windows => Either::Left(Either::Right( WINDOWS_CUDA_VERSIONS .iter() .filter_map(move |(backend, version)| { if driver_version >= version { Some(backend.index_url()) } else { None } }) .chain(std::iter::once(TorchBackend::Cpu.index_url())), )), Os::Macos { .. } | Os::FreeBsd { .. } | Os::NetBsd { .. } | Os::OpenBsd { .. } | Os::Dragonfly { .. } | Os::Illumos { .. } | Os::Haiku { .. } | Os::Android { .. } | Os::Pyodide { .. } => { Either::Right(std::iter::once(TorchBackend::Cpu.index_url())) } } } TorchStrategy::Backend(backend) => Either::Right(std::iter::once(backend.index_url())), } } } /// The available backends for PyTorch. #[derive(Debug, Copy, Clone, Eq, PartialEq)] pub enum TorchBackend { Cpu, Cu128, Cu126, Cu125, Cu124, Cu123, Cu122, Cu121, Cu120, Cu118, Cu117, Cu116, Cu115, Cu114, Cu113, Cu112, Cu111, Cu110, Cu102, Cu101, Cu100, Cu92, Cu91, Cu90, Cu80, Rocm63, Rocm624, Rocm62, Rocm61, Rocm60, Rocm57, Rocm56, Rocm55, Rocm542, Rocm54, Rocm53, Rocm52, Rocm511, Rocm42, Rocm41, Rocm401, } impl TorchBackend { /// Return the appropriate index URL for the given [`TorchBackend`]. fn index_url(self) -> &'static IndexUrl { match self { Self::Cpu => &CPU_INDEX_URL, Self::Cu128 => &CU128_INDEX_URL, Self::Cu126 => &CU126_INDEX_URL, Self::Cu125 => &CU125_INDEX_URL, Self::Cu124 => &CU124_INDEX_URL, Self::Cu123 => &CU123_INDEX_URL, Self::Cu122 => &CU122_INDEX_URL, Self::Cu121 => &CU121_INDEX_URL, Self::Cu120 => &CU120_INDEX_URL, Self::Cu118 => &CU118_INDEX_URL, Self::Cu117 => &CU117_INDEX_URL, Self::Cu116 => &CU116_INDEX_URL, Self::Cu115 => &CU115_INDEX_URL, Self::Cu114 => &CU114_INDEX_URL, Self::Cu113 => &CU113_INDEX_URL, Self::Cu112 => &CU112_INDEX_URL, Self::Cu111 => &CU111_INDEX_URL, Self::Cu110 => &CU110_INDEX_URL, Self::Cu102 => &CU102_INDEX_URL, Self::Cu101 => &CU101_INDEX_URL, Self::Cu100 => &CU100_INDEX_URL, Self::Cu92 => &CU92_INDEX_URL, Self::Cu91 => &CU91_INDEX_URL, Self::Cu90 => &CU90_INDEX_URL, Self::Cu80 => &CU80_INDEX_URL, Self::Rocm63 => &ROCM63_INDEX_URL, Self::Rocm624 => &ROCM624_INDEX_URL, Self::Rocm62 => &ROCM62_INDEX_URL, Self::Rocm61 => &ROCM61_INDEX_URL, Self::Rocm60 => &ROCM60_INDEX_URL, Self::Rocm57 => &ROCM57_INDEX_URL, Self::Rocm56 => &ROCM56_INDEX_URL, Self::Rocm55 => &ROCM55_INDEX_URL, Self::Rocm542 => &ROCM542_INDEX_URL, Self::Rocm54 => &ROCM54_INDEX_URL, Self::Rocm53 => &ROCM53_INDEX_URL, Self::Rocm52 => &ROCM52_INDEX_URL, Self::Rocm511 => &ROCM511_INDEX_URL, Self::Rocm42 => &ROCM42_INDEX_URL, Self::Rocm41 => &ROCM41_INDEX_URL, Self::Rocm401 => &ROCM401_INDEX_URL, } } /// Extract a [`TorchBackend`] from an index URL. pub fn from_index(index: &Url) -> Option { let backend_identifier = if index.host_str() == Some("download.pytorch.org") { // E.g., `https://download.pytorch.org/whl/cu124` let mut path_segments = index.path_segments()?; if path_segments.next() != Some("whl") { return None; } path_segments.next()? } else { return None; }; Self::from_str(backend_identifier).ok() } /// Returns the CUDA [`Version`] for the given [`TorchBackend`]. pub fn cuda_version(&self) -> Option { match self { TorchBackend::Cpu => None, TorchBackend::Cu128 => Some(Version::new([12, 8])), TorchBackend::Cu126 => Some(Version::new([12, 6])), TorchBackend::Cu125 => Some(Version::new([12, 5])), TorchBackend::Cu124 => Some(Version::new([12, 4])), TorchBackend::Cu123 => Some(Version::new([12, 3])), TorchBackend::Cu122 => Some(Version::new([12, 2])), TorchBackend::Cu121 => Some(Version::new([12, 1])), TorchBackend::Cu120 => Some(Version::new([12, 0])), TorchBackend::Cu118 => Some(Version::new([11, 8])), TorchBackend::Cu117 => Some(Version::new([11, 7])), TorchBackend::Cu116 => Some(Version::new([11, 6])), TorchBackend::Cu115 => Some(Version::new([11, 5])), TorchBackend::Cu114 => Some(Version::new([11, 4])), TorchBackend::Cu113 => Some(Version::new([11, 3])), TorchBackend::Cu112 => Some(Version::new([11, 2])), TorchBackend::Cu111 => Some(Version::new([11, 1])), TorchBackend::Cu110 => Some(Version::new([11, 0])), TorchBackend::Cu102 => Some(Version::new([10, 2])), TorchBackend::Cu101 => Some(Version::new([10, 1])), TorchBackend::Cu100 => Some(Version::new([10, 0])), TorchBackend::Cu92 => Some(Version::new([9, 2])), TorchBackend::Cu91 => Some(Version::new([9, 1])), TorchBackend::Cu90 => Some(Version::new([9, 0])), TorchBackend::Cu80 => Some(Version::new([8, 0])), TorchBackend::Rocm63 => None, TorchBackend::Rocm624 => None, TorchBackend::Rocm62 => None, TorchBackend::Rocm61 => None, TorchBackend::Rocm60 => None, TorchBackend::Rocm57 => None, TorchBackend::Rocm56 => None, TorchBackend::Rocm55 => None, TorchBackend::Rocm542 => None, TorchBackend::Rocm54 => None, TorchBackend::Rocm53 => None, TorchBackend::Rocm52 => None, TorchBackend::Rocm511 => None, TorchBackend::Rocm42 => None, TorchBackend::Rocm41 => None, TorchBackend::Rocm401 => None, } } /// Returns the ROCM [`Version`] for the given [`TorchBackend`]. pub fn rocm_version(&self) -> Option { match self { TorchBackend::Cpu => None, TorchBackend::Cu128 => None, TorchBackend::Cu126 => None, TorchBackend::Cu125 => None, TorchBackend::Cu124 => None, TorchBackend::Cu123 => None, TorchBackend::Cu122 => None, TorchBackend::Cu121 => None, TorchBackend::Cu120 => None, TorchBackend::Cu118 => None, TorchBackend::Cu117 => None, TorchBackend::Cu116 => None, TorchBackend::Cu115 => None, TorchBackend::Cu114 => None, TorchBackend::Cu113 => None, TorchBackend::Cu112 => None, TorchBackend::Cu111 => None, TorchBackend::Cu110 => None, TorchBackend::Cu102 => None, TorchBackend::Cu101 => None, TorchBackend::Cu100 => None, TorchBackend::Cu92 => None, TorchBackend::Cu91 => None, TorchBackend::Cu90 => None, TorchBackend::Cu80 => None, TorchBackend::Rocm63 => Some(Version::new([6, 3])), TorchBackend::Rocm624 => Some(Version::new([6, 2, 4])), TorchBackend::Rocm62 => Some(Version::new([6, 2])), TorchBackend::Rocm61 => Some(Version::new([6, 1])), TorchBackend::Rocm60 => Some(Version::new([6, 0])), TorchBackend::Rocm57 => Some(Version::new([5, 7])), TorchBackend::Rocm56 => Some(Version::new([5, 6])), TorchBackend::Rocm55 => Some(Version::new([5, 5])), TorchBackend::Rocm542 => Some(Version::new([5, 4, 2])), TorchBackend::Rocm54 => Some(Version::new([5, 4])), TorchBackend::Rocm53 => Some(Version::new([5, 3])), TorchBackend::Rocm52 => Some(Version::new([5, 2])), TorchBackend::Rocm511 => Some(Version::new([5, 1, 1])), TorchBackend::Rocm42 => Some(Version::new([4, 2])), TorchBackend::Rocm41 => Some(Version::new([4, 1])), TorchBackend::Rocm401 => Some(Version::new([4, 0, 1])), } } } impl FromStr for TorchBackend { type Err = String; fn from_str(s: &str) -> Result { match s { "cpu" => Ok(TorchBackend::Cpu), "cu128" => Ok(TorchBackend::Cu128), "cu126" => Ok(TorchBackend::Cu126), "cu125" => Ok(TorchBackend::Cu125), "cu124" => Ok(TorchBackend::Cu124), "cu123" => Ok(TorchBackend::Cu123), "cu122" => Ok(TorchBackend::Cu122), "cu121" => Ok(TorchBackend::Cu121), "cu120" => Ok(TorchBackend::Cu120), "cu118" => Ok(TorchBackend::Cu118), "cu117" => Ok(TorchBackend::Cu117), "cu116" => Ok(TorchBackend::Cu116), "cu115" => Ok(TorchBackend::Cu115), "cu114" => Ok(TorchBackend::Cu114), "cu113" => Ok(TorchBackend::Cu113), "cu112" => Ok(TorchBackend::Cu112), "cu111" => Ok(TorchBackend::Cu111), "cu110" => Ok(TorchBackend::Cu110), "cu102" => Ok(TorchBackend::Cu102), "cu101" => Ok(TorchBackend::Cu101), "cu100" => Ok(TorchBackend::Cu100), "cu92" => Ok(TorchBackend::Cu92), "cu91" => Ok(TorchBackend::Cu91), "cu90" => Ok(TorchBackend::Cu90), "cu80" => Ok(TorchBackend::Cu80), "rocm6.3" => Ok(TorchBackend::Rocm63), "rocm6.2.4" => Ok(TorchBackend::Rocm624), "rocm6.2" => Ok(TorchBackend::Rocm62), "rocm6.1" => Ok(TorchBackend::Rocm61), "rocm6.0" => Ok(TorchBackend::Rocm60), "rocm5.7" => Ok(TorchBackend::Rocm57), "rocm5.6" => Ok(TorchBackend::Rocm56), "rocm5.5" => Ok(TorchBackend::Rocm55), "rocm5.4.2" => Ok(TorchBackend::Rocm542), "rocm5.4" => Ok(TorchBackend::Rocm54), "rocm5.3" => Ok(TorchBackend::Rocm53), "rocm5.2" => Ok(TorchBackend::Rocm52), "rocm5.1.1" => Ok(TorchBackend::Rocm511), "rocm4.2" => Ok(TorchBackend::Rocm42), "rocm4.1" => Ok(TorchBackend::Rocm41), "rocm4.0.1" => Ok(TorchBackend::Rocm401), _ => Err(format!("Unknown PyTorch backend: {s}")), } } } /// Linux CUDA driver versions and the corresponding CUDA versions. /// /// See: static LINUX_DRIVERS: LazyLock<[(TorchBackend, Version); 24]> = LazyLock::new(|| { [ // Table 2 from // https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html (TorchBackend::Cu128, Version::new([525, 60, 13])), (TorchBackend::Cu126, Version::new([525, 60, 13])), (TorchBackend::Cu125, Version::new([525, 60, 13])), (TorchBackend::Cu124, Version::new([525, 60, 13])), (TorchBackend::Cu123, Version::new([525, 60, 13])), (TorchBackend::Cu122, Version::new([525, 60, 13])), (TorchBackend::Cu121, Version::new([525, 60, 13])), (TorchBackend::Cu120, Version::new([525, 60, 13])), // Table 2 from // https://docs.nvidia.com/cuda/archive/11.8.0/cuda-toolkit-release-notes/index.html (TorchBackend::Cu118, Version::new([450, 80, 2])), (TorchBackend::Cu117, Version::new([450, 80, 2])), (TorchBackend::Cu116, Version::new([450, 80, 2])), (TorchBackend::Cu115, Version::new([450, 80, 2])), (TorchBackend::Cu114, Version::new([450, 80, 2])), (TorchBackend::Cu113, Version::new([450, 80, 2])), (TorchBackend::Cu112, Version::new([450, 80, 2])), (TorchBackend::Cu111, Version::new([450, 80, 2])), (TorchBackend::Cu110, Version::new([450, 36, 6])), // Table 1 from // https://docs.nvidia.com/cuda/archive/10.2/cuda-toolkit-release-notes/index.html (TorchBackend::Cu102, Version::new([440, 33])), (TorchBackend::Cu101, Version::new([418, 39])), (TorchBackend::Cu100, Version::new([410, 48])), (TorchBackend::Cu92, Version::new([396, 26])), (TorchBackend::Cu91, Version::new([390, 46])), (TorchBackend::Cu90, Version::new([384, 81])), (TorchBackend::Cu80, Version::new([375, 26])), ] }); /// Windows CUDA driver versions and the corresponding CUDA versions. /// /// See: static WINDOWS_CUDA_VERSIONS: LazyLock<[(TorchBackend, Version); 24]> = LazyLock::new(|| { [ // Table 2 from // https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html (TorchBackend::Cu128, Version::new([528, 33])), (TorchBackend::Cu126, Version::new([528, 33])), (TorchBackend::Cu125, Version::new([528, 33])), (TorchBackend::Cu124, Version::new([528, 33])), (TorchBackend::Cu123, Version::new([528, 33])), (TorchBackend::Cu122, Version::new([528, 33])), (TorchBackend::Cu121, Version::new([528, 33])), (TorchBackend::Cu120, Version::new([528, 33])), // Table 2 from // https://docs.nvidia.com/cuda/archive/11.8.0/cuda-toolkit-release-notes/index.html (TorchBackend::Cu118, Version::new([452, 39])), (TorchBackend::Cu117, Version::new([452, 39])), (TorchBackend::Cu116, Version::new([452, 39])), (TorchBackend::Cu115, Version::new([452, 39])), (TorchBackend::Cu114, Version::new([452, 39])), (TorchBackend::Cu113, Version::new([452, 39])), (TorchBackend::Cu112, Version::new([452, 39])), (TorchBackend::Cu111, Version::new([452, 39])), (TorchBackend::Cu110, Version::new([451, 22])), // Table 1 from // https://docs.nvidia.com/cuda/archive/10.2/cuda-toolkit-release-notes/index.html (TorchBackend::Cu102, Version::new([441, 22])), (TorchBackend::Cu101, Version::new([418, 96])), (TorchBackend::Cu100, Version::new([411, 31])), (TorchBackend::Cu92, Version::new([398, 26])), (TorchBackend::Cu91, Version::new([391, 29])), (TorchBackend::Cu90, Version::new([385, 54])), (TorchBackend::Cu80, Version::new([376, 51])), ] }); static CPU_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cpu").unwrap()); static CU128_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu128").unwrap()); static CU126_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu126").unwrap()); static CU125_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu125").unwrap()); static CU124_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu124").unwrap()); static CU123_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu123").unwrap()); static CU122_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu122").unwrap()); static CU121_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu121").unwrap()); static CU120_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu120").unwrap()); static CU118_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu118").unwrap()); static CU117_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu117").unwrap()); static CU116_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu116").unwrap()); static CU115_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu115").unwrap()); static CU114_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu114").unwrap()); static CU113_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu113").unwrap()); static CU112_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu112").unwrap()); static CU111_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu111").unwrap()); static CU110_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu110").unwrap()); static CU102_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu102").unwrap()); static CU101_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu101").unwrap()); static CU100_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu100").unwrap()); static CU92_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu92").unwrap()); static CU91_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu91").unwrap()); static CU90_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu90").unwrap()); static CU80_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/cu80").unwrap()); static ROCM63_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm6.3").unwrap()); static ROCM624_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm6.2.4").unwrap()); static ROCM62_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm6.2").unwrap()); static ROCM61_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm6.1").unwrap()); static ROCM60_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm6.0").unwrap()); static ROCM57_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.7").unwrap()); static ROCM56_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.6").unwrap()); static ROCM55_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.5").unwrap()); static ROCM542_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.4.2").unwrap()); static ROCM54_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.4").unwrap()); static ROCM53_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.3").unwrap()); static ROCM52_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.2").unwrap()); static ROCM511_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm5.1.1").unwrap()); static ROCM42_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm4.2").unwrap()); static ROCM41_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm4.1").unwrap()); static ROCM401_INDEX_URL: LazyLock = LazyLock::new(|| IndexUrl::from_str("https://download.pytorch.org/whl/rocm4.0.1").unwrap());