libtorch1.6.0(CPU):选择使用release版本即可(据说debug有问题)https://download.pytorch.org/libtorch/cpu/libtorch-win-shared-with-deps-1.6.0%2Bcpu.zip 2.2 使用cmakelist的搭建工程 cmake_minimum_required(VERSION3.12FATAL_ERROR)project(torch_gpu_test)# add CMAKE_PREFIX_PATHlist(APPENDCMAKE_PREFIX_PAT...
$ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 然后编译我们就发现可以编译通过啦~ 至此我们Docker挂载GPU以及编译开发环境就搭建好啦~大家可以放心测试上线啦~
wget https://download.pytorch.org/libtorch/nightly/cu9/libtorch-shared-with-deps-latest.zip 或者下载cpu版本 wget https://download.pytorch.org/libtorch/nightly/cpu/libtorch-shared-with-deps-latest.zip 解压这个压缩包 unzip libtorch-shared-with-deps-latest.zip 创建目录dcgan 现在dcagn目录下的文件 CMa...