我发现在Anaconda中安装Pytorch 0.4 GPU版本后,您不需要在本地安装CUDA即可调用gpu加速。当运行代码时,GPU内核的使用率可以达到90%以上。
编辑:我在Windows10下用过,不知道在Linux下能不能用。
发布于 2018-11-16 17:59:28
@talonmies
谢谢你的网址。在Windows中,pytorch似乎不需要cuda,因为它的依赖项是cffi、mkl、numpy和python。
我在Anaconda提示符中输入了这个命令conda search -c pytorch pytorch=0.4.0 --info,它显示
Loading channels: done
pytorch 0.4.0 py35_cuda80_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py35_cuda80_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py35_cuda80_cudnn7he774522_1
build number: 1
size : 528.5 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py35_cuda80_cudnn7he774522_1.tar.bz2
md5 : 7db3971bb054079d7c7ff84b6286c58e
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.5,<3.6.0a0
pytorch 0.4.0 py35_cuda90_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py35_cuda90_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py35_cuda90_cudnn7he774522_1
build number: 1
size : 578.5 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py35_cuda90_cudnn7he774522_1.tar.bz2
md5 : 8200c9841f9cad6f2e605015812aa3f2
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.5,<3.6.0a0
pytorch 0.4.0 py35_cuda91_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py35_cuda91_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py35_cuda91_cudnn7he774522_1
build number: 1
size : 546.1 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py35_cuda91_cudnn7he774522_1.tar.bz2
md5 : 79d99a825f66b55b1aa6f04d22d68aac
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.5,<3.6.0a0
pytorch 0.4.0 py36_cuda80_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py36_cuda80_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py36_cuda80_cudnn7he774522_1
build number: 1
size : 529.2 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py36_cuda80_cudnn7he774522_1.tar.bz2
md5 : 27d20c9869fb57ffe0d6d014cf348855
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.6,<3.7.0a0
pytorch 0.4.0 py36_cuda90_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py36_cuda90_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py36_cuda90_cudnn7he774522_1
build number: 1
size : 577.6 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py36_cuda90_cudnn7he774522_1.tar.bz2
md5 : 138dcca8eeff1d58a8fd9b1febf702f6
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.6,<3.7.0a0
pytorch 0.4.0 py36_cuda91_cudnn7he774522_1
------------------------------------------
file name : pytorch-0.4.0-py36_cuda91_cudnn7he774522_1.tar.bz2
name : pytorch
version : 0.4.0
build string: py36_cuda91_cudnn7he774522_1
build number: 1
size : 546.4 MB
arch : x86_64
constrains : ()
platform : Platform.win
license : BSD 3-Clause
subdir : win-64
url : https://conda.anaconda.org/pytorch/win-64/pytorch-0.4.0-py36_cuda91_cudnn7he774522_1.tar.bz2
md5 : 326265665000de6f7501160b10b089c8
dependencies:
- cffi
- mkl >=2018
- numpy >=1.11
- python >=3.6,<3.7.0a0https://stackoverflow.com/questions/53292107
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