AMD的CPU是否适合搭建深度学习主机？ 第1页

       conda create -n ~~~~~~~ python=3.8 conda activate ~~~~~~~     

       # 安装gfortran sudo apt-get install gfortran  ## 来自：https://stackoverflow.com/questions/11443302/compiling-numpy-with-openblas-integration # 下载openblas git clone https://github.com/xianyi/OpenBLAS # 进入目录，然后编译 cd OpenBLAS && make FC=gfortran # 安装，以及解决环境变量 sudo make PREFIX=/opt/OpenBLAS install export LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH sudo ldconfig     

       # 克隆numpy git clone https://github.com/numpy/numpy.git cd numpy     

       cp site.cfg.example site.cfg nano site.cfg     

       python setup.py config     

         FOUND:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib']    FOUND:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib']     

         FOUND:  如果失败如出现 MKL     libraries = ['mkl_rt', 'pthread']     library_dirs = ['/home/fuqingxu/anaconda3/lib']     define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]     include_dirs = ['/usr/local/include', '/usr/include', '/home/fuqingxu/anaconda3/include']     

       pip install . --verbose     

       cd .. python     

       >>> import numpy >>> numpy.__config__.show() blas_mkl_info:   NOT AVAILABLE blis_info:   NOT AVAILABLE openblas_info:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib'] blas_opt_info:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib'] lapack_mkl_info:   NOT AVAILABLE openblas_lapack_info:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib'] lapack_opt_info:     libraries = ['openblas', 'openblas']     library_dirs = ['/opt/OpenBLAS/lib']     language = c     define_macros = [('HAVE_CBLAS', None)]     runtime_library_dirs = ['/opt/OpenBLAS/lib']     

       # Get the PyTorch Source git clone --recursive pytorch/pytorch cd pytorch # if you are updating an existing checkout git submodule sync git submodule update --init --recursive     

       git config --global http.proxy socks5://127.0.0.1:port???? git config --global https.proxy socks5://127.0.0.1:port????     

       conda install ninja pyyaml setuptools cmake cffi typing_extensions future six requests dataclasses conda install -c pytorch magma-cuda110     

       export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"} export USE_OPENMP=1  # 不是很懂这个 export BLAS=OpenBLAS export USE_CUDA=1 export USE_CUDNN=1 export MAX_JOBS=128 export USE_MKLDNN=0 # export USE_NUMPY=1 这个我不是很确定，哪位大佬看到可以评论一下这个有什么作用 export USE_MPI=1        # 不是很懂这个 export BUILD_BINARY=1 export LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH export OpenBLAS_HOME=/opt/OpenBLAS export CUDA_HOME=/usr/local/cuda-11.0        # 取决于cuda的安装位置和版本 export CUDNN_LIB_DIR=/usr/local/cuda-11.0/lib64  # 取决于cuda的安装位置和版本 export CUDNN_INCLUDE_DIR=/usr/local/cuda-11.0/include  # 取决于cuda的安装位置和版本     

       # exectute building python setup.py install     

       git clean -xfd && git submodule foreach git clean -xfd     

       cd ..  python >>> import torch >>> torch.cuda.is_available() True >>> torch.__config__.show() 'PyTorch built with:
  - GCC 9.3
  - C++ Version: 201402
   - OpenMP 201511 (a.k.a. OpenMP 4.5)
   - NNPACK is enabled
   - CPU capability usage: AVX2
   - CUDA Runtime 11.0
   - NVCC architecture flags: -gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_75,code=sm_75; -gencode;arch=compute_80,code=compute_80
   - CuDNN 8.1.1  (built against CUDA 11.2)
   - Magma 2.5.2
   - Build settings: BLAS_INFO=open, BUILD_TYPE=Release,  CUDA_VERSION=11.0, CUDNN_VERSION=8.1.1, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated  -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM  -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type  -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas  -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable  -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow  -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic  -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new  -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format  -Werror=cast-function-type -Wno-stringop-overflow,  FORCE_FALLBACK_CUDA_MPI=1, LAPACK_INFO=open, PERF_WITH_AVX=1,  PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0,  USE_CUDA=1, USE_CUDNN=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF,  USE_GLOG=OFF, USE_MKLDNN=OFF, USE_MPI=1, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=1, 
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