{
  "repodata": {
    "build": "gpu_cuda128_py311ha5014ee_301",
    "build_number": 301,
    "depends": [
      "__glibc >=2.28,<3.0.a0",
      "_openmp_mutex >=4.5",
      "_openmp_mutex >=5.1",
      "blas 1.0 mkl",
      "cuda-cudart >=12.8.90,<13.0a0",
      "cuda-cupti >=12.8.90,<13.0a0",
      "cuda-nvrtc >=12.8.93,<13.0a0",
      "cuda-nvtx >=12.8.90,<13.0a0",
      "cuda-version >=12.8,<13",
      "cudnn >=9.15.1.9,<10.0a0",
      "filelock",
      "fmt >=12.1.0,<13.0a0",
      "fsspec",
      "intel-openmp >=2025.0.0,<2026.0a0",
      "jinja2",
      "libabseil * cxx17*",
      "libabseil >=20260107.0,<20260108.0a0",
      "libcublas >=12.8.4.1,<13.0a0",
      "libcudnn >=9.15.1.9,<10.0a0",
      "libcufft >=11.3.3.83,<12.0a0",
      "libcufile >=1.13.1.3,<2.0a0",
      "libcurand >=10.3.9.90,<11.0a0",
      "libcusolver >=11.7.3.90,<12.0a0",
      "libcusparse >=12.5.8.93,<13.0a0",
      "libgcc >=14",
      "libprotobuf >=6.33.5,<6.33.6.0a0",
      "libstdcxx >=14",
      "libtorch 2.10.0 gpu_cuda128_h86e1c19_301",
      "libuv >=1.52.0,<2.0a0",
      "libzlib >=1.3.1,<2.0a0",
      "magma >=2.9.0,<3.0a0",
      "mkl >=2025.0.0,<2026.0a0",
      "mkl-service >=2.3.0,<3.0a0",
      "nccl >=2.21.5.1,<3.0a0",
      "networkx",
      "numpy >=1.23,<3",
      "numpy >=1.24.0,<3.0.0",
      "optree >=0.13.0",
      "python >=3.11,<3.12.0a0",
      "setuptools",
      "sleef >=3.5.1,<4.0a0",
      "sympy >=1.13.3",
      "triton 3.6.0",
      "typing_extensions >=4.15.0"
    ],
    "license": "BSD-3-Clause",
    "license_family": "BSD",
    "md5": "2345ec3fcde45b315fcdf6b0c0279ecc",
    "name": "pytorch",
    "sha256": "f5b06e59ebe9cc9e23ad6159e318654d2010251d5ecc743933d851b0ec1bac18",
    "size": 37470036,
    "subdir": "linux-64",
    "timestamp": 1776124476935,
    "version": "2.10.0"
  },
  "s3": "builds/ci/prefect/AHu9T3nuR8a0FmBzhL5INQ/1776147311/linux-64/pytorch-2.10.0-gpu_cuda128_py311ha5014ee_301.conda",
  "signatures": {
    "7e3910a4b96ef2fe7242b10587a47039c8924fadf98a69503d63445e88b984b3": "c80a2c240128f38336c7906b6b086e95d73e56b7903be1cd2f0a6e20cc0998085f0d16a0b1212218ad8c8aa4bbdc7acc116152bf5e3457d7bc842248c66aeb06"
  }
}