{
  "name": "libtorch",
  "version": "2.12.0",
  "description": "Tensors and Dynamic neural networks in Python with strong GPU acceleration",
  "homepage": "https://pytorch.org/",
  "license": null,
  "supports": "(windows & !static) | osx | linux",
  "dependencies": [
    "cpp-httplib",
    "cpuinfo",
    "eigen3",
    {
      "name": "fbgemm",
      "platform": "x64 & !uwp"
    },
    "flatbuffers",
    {
      "name": "flatbuffers",
      "host": true
    },
    "fmt",
    "fp16",
    "kineto",
    {
      "name": "kleidiai",
      "platform": "arm64"
    },
    {
      "name": "mimalloc",
      "platform": "windows | (arm64 & !osx)"
    },
    "nlohmann-json",
    {
      "name": "nnpack",
      "platform": "linux | osx"
    },
    "onnx",
    "opencl",
    "pocketfft",
    "protobuf",
    {
      "name": "protobuf",
      "host": true
    },
    "pthreadpool",
    "pybind11",
    "sleef",
    {
      "name": "vcpkg-cmake",
      "host": true
    },
    {
      "name": "vcpkg-cmake-config",
      "host": true
    },
    {
      "name": "vcpkg-get-python-packages",
      "host": true
    },
    "xnnpack"
  ],
  "default-features": [
    "blas"
  ],
  "features": {
    "blas": {
      "description": "BLAS/LAPACK backend (openblas on linux/windows, Accelerate on macOS). On by default; disable with [core,...] when using [mkl] instead.",
      "dependencies": [
        "blas",
        "lapack"
      ]
    },
    "cuda": {
      "description": "Build with CUDA GPU backend",
      "supports": "(windows & x64 & !staticcrt) | (linux & x64)",
      "dependencies": [
        "cuda",
        "cudnn",
        "cudnn-frontend",
        {
          "name": "gloo",
          "features": [
            "cuda"
          ],
          "platform": "linux"
        },
        "magma",
        {
          "name": "nccl",
          "platform": "linux"
        },
        "nvidia-cutlass",
        {
          "name": "tensorpipe",
          "features": [
            "cuda"
          ],
          "platform": "linux"
        }
      ]
    },
    "dist": {
      "description": "Use distributed training/inference (Gloo, MPI, libuv, TensorPipe)",
      "supports": "(linux & x64) | windows",
      "dependencies": [
        {
          "name": "gloo",
          "platform": "linux"
        },
        {
          "name": "libuv",
          "platform": "windows | osx"
        },
        {
          "name": "mpi",
          "platform": "linux"
        },
        {
          "name": "tensorpipe",
          "platform": "linux"
        }
      ]
    },
    "gflags": {
      "description": "Build with gflags",
      "dependencies": [
        "gflags"
      ]
    },
    "glog": {
      "description": "Build with glog",
      "dependencies": [
        "glog"
      ]
    },
    "llvm": {
      "description": "Build with LLVM",
      "dependencies": [
        "llvm"
      ]
    },
    "mkl": {
      "description": "Intel performance backend: use oneMKL for BLAS/LAPACK and enable oneDNN (MKLDNN) CPU acceleration via ideep. Mutually exclusive with [blas] (the openblas default-feature) — install as libtorch[core,mkl,...] to skip the openblas backend, otherwise both backends get built and only MKL is linked.",
      "supports": "(windows | linux) & x64 & !uwp",
      "dependencies": [
        "ideep",
        "intel-mkl",
        "onednn"
      ]
    },
    "vulkan": {
      "description": "Build with Vulkan GPU backend",
      "dependencies": [
        {
          "name": "shaderc",
          "host": true
        },
        "vulkan",
        "vulkan-loader",
        "vulkan-memory-allocator"
      ]
    }
  }
}