Package: libtorch1.8
Source: pytorch
Version: 1.8.1-4
Architecture: amd64
Maintainer: Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
Original-Maintainer: Debian Deep Learning Team <debian-ai@lists.debian.org>
Installed-Size: 101123
Depends: libavcodec58 (>= 7:4.4), libavformat58 (>= 7:4.4), libavutil56 (>= 7:4.4), libblas3 | libblas.so.3, libc6 (>= 2.34), libcpuinfo0 (>= 0.0~git20181113.3bf2c72), libdnnl2 (>= 2.0), libfmt8 (>= 8.1.1+ds1), libgcc-s1 (>= 3.4), libgflags2.2 (>= 2.2.2), libgloo0 (>= 0.0~git20200918.3dc0328), libgomp1 (>= 4.9), libgoogle-glog0v5 (>= 0.5.0+really0.4.0), liblapack3 | liblapack.so.3, libleveldb1d (>= 1.23), liblmdb0 (>= 0.9.7), libnuma1 (>= 2.0.11), libonnx1 (>= 1.7.0+dfsg), libopencv-calib3d4.5d (>= 4.5.4+dfsg), libopencv-contrib4.5d (>= 4.5.4+dfsg), libopencv-core4.5d (>= 4.5.4+dfsg), libopencv-dnn4.5d (>= 4.5.4+dfsg), libopencv-features2d4.5d (>= 4.5.4+dfsg), libopencv-flann4.5d (>= 4.5.4+dfsg), libopencv-highgui4.5d (>= 4.5.4+dfsg), libopencv-imgcodecs4.5d (>= 4.5.4+dfsg), libopencv-imgproc4.5d (>= 4.5.4+dfsg), libopencv-video4.5d (>= 4.5.4+dfsg), libopencv-videoio4.5d (>= 4.5.4+dfsg), libprotobuf23 (>= 3.12.4), libpthreadpool0 (>= 0.0~git20200423.6acde9c), libsleef3 (>= 3.3), libsnappy1v5 (>= 1.1.8), libstdc++6 (>= 11), libswresample3 (>= 7:4.4), libswscale5 (>= 7:4.4), libtensorpipe0 (>= 0.0~git20210304.369e855), libunwind8, libxnnpack0 (>= 0.0~git20201221.e1ffe15), libzmq5 (>= 3.2.3+dfsg), libzstd1 (>= 1.4.0), ocl-icd-libopencl1 | libopencl1
Recommends: libopenblas0 | libblis3 | libatlas3-base | libmkl-rt | libblas3
Section: libs
Priority: optional
Multi-Arch: same
Homepage: https://pytorch.org/
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 and Caffe2 (Shared Objects).
