Source: pytorch Section: science Homepage: https://pytorch.org/ Priority: optional Standards-Version: 4.6.0.1 Vcs-Git: https://salsa.debian.org/deeplearning-team/pytorch.git Vcs-Browser: https://salsa.debian.org/deeplearning-team/pytorch Maintainer: Debian Deep Learning Team Uploaders: Mo Zhou Rules-Requires-Root: no Build-Depends: cmake, debhelper-compat (= 12), dh-exec, dh-python, googletest, # glslc, libasio-dev, libavcodec-dev, libblas-dev, libbenchmark-dev, libcpuinfo-dev (>= 0.0~git20220819.8ec7bd9~), libdnnl-dev (>= 2.7.4~) [amd64 arm64 ppc64el], libeigen3-dev, libfmt-dev, libfp16-dev (>= 0.0~git20200514.4dfe081~), libflatbuffers-dev (>= 2.0.8~), libflatbuffers-dev (<< 2.0.9~), flatbuffers-compiler-dev, libfxdiv-dev (>= 0.0~git20200417.b408327~), libgloo-dev (>= 0.0~git20230117.1090929~) [amd64 arm64 ppc64el mips64el s390x riscv64], libideep-dev (>= 0.0~git20230213.7bc3e12~) [amd64 arm64 ppc64el], liblapack-dev, libleveldb-dev, liblmdb-dev, llvm-dev, libnop-dev, libnuma-dev, libonnx-dev (>= 1.13.1~), libopencv-dev, libprotobuf-dev, libprotoc-dev, libpsimd-dev (>= 0.0~git20200517.072586a~), libpthreadpool-dev (>= 0.0~git20210507.1787867~), libsleef-dev, libsnappy-dev, libtensorpipe-dev (>= 0.0~git20220513.bb1473a~), # libvulkan-dev, # libvulkan-memory-allocator-dev, libxnnpack-dev (>= 0.0~git20221221.51a9875~) [amd64 arm64 riscv64], libzmq3-dev, libzstd-dev, ninja-build, ocl-icd-opencl-dev, protobuf-compiler, pybind11-dev, python3, python3-dev, python3-cffi, python3-distutils, python3-numpy, python3-onnx, python3-pybind11, python3-setuptools, python3-yaml Package: python3-torch Section: python Architecture: amd64 arm64 mips64el ppc64el s390x kfreebsd-amd64 riscv64 Depends: libtorch2.0 (= ${binary:Version}), ${misc:Depends}, ${python3:Depends}, ${shlibs:Depends}, libtorch-test (= ${binary:Version}), # PyTorch's JIT (C++ Extension) functionality needs development files/tools. Recommends: libtorch-dev (= ${binary:Version}), build-essential, ninja-build, pybind11-dev, Suggests: python3-hypothesis, python3-pytest Provides: ${python3:Provides}, python3-torch-api-2.0 Conflicts: python3-torch-cuda Replaces: python3-torch-cuda Description: Tensors and Dynamic neural networks in Python (Python Interface) PyTorch is a Python package that provides two high-level features: . (1) Tensor computation (like NumPy) with strong GPU acceleration (2) Deep neural networks built on a tape-based autograd system . You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed. . This is the CPU-only version of PyTorch (Python interface). Package: libtorch-dev Section: libdevel Architecture: amd64 arm64 mips64el ppc64el s390x kfreebsd-amd64 riscv64 Depends: libtorch2.0 (= ${binary:Version}), python3-dev, libprotobuf-dev, ${misc:Depends} Conflicts: libtorch-cuda-dev Replaces: libtorch-cuda-dev Description: Tensors and Dynamic neural networks in Python (Development Files) PyTorch is a Python package that provides two high-level features: . (1) Tensor computation (like NumPy) with strong GPU acceleration (2) Deep neural networks built on a tape-based autograd system . You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed. . This is the CPU-only version of PyTorch (Development files). Package: libtorch2.0 Section: libs Architecture: amd64 arm64 mips64el ppc64el s390x kfreebsd-amd64 riscv64 Multi-Arch: same Depends: ${misc:Depends}, ${shlibs:Depends}, Recommends: libopenblas0 | libblis3 | libatlas3-base | libmkl-rt | libblas3, Conflicts: libtorch1.13, libtorch-cuda-1.13, libtorch-cuda-2.0 Replaces: libtorch1.13, libtorch-cuda-1.13, libtorch-cuda-2.0 Description: Tensors and Dynamic neural networks in Python (Shared Objects) PyTorch is a Python package that provides two high-level features: . (1) Tensor computation (like NumPy) with strong GPU acceleration (2) Deep neural networks built on a tape-based autograd system . You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed. . This is the CPU-only version of PyTorch (Shared Objects). Package: libtorch-test Section: libs Architecture: amd64 arm64 mips64el ppc64el s390x kfreebsd-amd64 riscv64 Depends: libtorch2.0 (= ${binary:Version}), ${misc:Depends}, ${shlibs:Depends}, Conflicts: libtorch-cuda-test Replaces: libtorch-cuda-test Description: Tensors and Dynamic neural networks in Python (Test Binaries) PyTorch is a Python package that provides two high-level features: . (1) Tensor computation (like NumPy) with strong GPU acceleration (2) Deep neural networks built on a tape-based autograd system . You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed. . This is the CPU-only version of PyTorch (Test Binaries).