我在尝试使用A100 GPU运行我的现有代码时遇到了以下错误：
---> backend='nccl'/home/miranda9/miniconda3/envs/metalearningpy1.7.1c10.2/lib/python3.8/site-packages/torch/cuda/__init__.py:104: UserWarning: A100-SXM4-40GB with CUDA capability sm_80 is not compatible with the current PyTorch installation.The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 compute_37.If you want to use the A100-SXM4-40GB GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/这让我感到困惑，因为它指向了常规的pytorch安装页面，但并没有告诉我对于我的特定硬件（A100）应该使用哪种pytorch版本和cuda版本的组合。如何为A100正确安装pytorch？
我尝试了一些版本：
# conda install -y pytorch==1.8.0 torchvision cudatoolkit=10.2 -c pytorch# conda install -y pytorch torchvision cudatoolkit=10.2 -c pytorch#conda install -y pytorch==1.7.1 torchvision torchaudio cudatoolkit=10.2 -c pytorch -c conda-forge# conda install -y pytorch==1.6.0 torchvision cudatoolkit=10.2 -c pytorch#conda install -y pytorch==1.7.1 torchvision torchaudio cudatoolkit=11.1 -c pytorch -c conda-forge# conda install pytorch torchvision torchaudio cudatoolkit=11.0 -c pytorch# conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c conda-forge# conda install -y pytorch torchvision cudatoolkit=9.2 -c pytorch # For Nano, CC# conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c conda-forge请注意，这一点可能比较微妙，因为我之前在这台机器上使用这个pytorch版本时也遇到过这个错误：
如何解决著名的`unhandled cuda error, NCCL version 2.7.8`错误？
附加1：
我仍然遇到错误：
ncclSystemError: System call (socket, malloc, munmap, etc) failed.Traceback (most recent call last): File "/home/miranda9/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/experiment_mains/main_dist_maml_l2l.py", line 1423, in <module> main() File "/home/miranda9/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/experiment_mains/main_dist_maml_l2l.py", line 1365, in main train(args=args) File "/home/miranda9/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/experiment_mains/main_dist_maml_l2l.py", line 1385, in train args.opt = move_opt_to_cherry_opt_and_sync_params(args) if is_running_parallel(args.rank) else args.opt File "/home/miranda9/ultimate-utils/ultimate-utils-proj-src/uutils/torch_uu/distributed.py", line 456, in move_opt_to_cherry_opt_and_sync_params args.opt = cherry.optim.Distributed(args.model.parameters(), opt=args.opt, sync=syn) File "/home/miranda9/miniconda3/envs/meta_learning_a100/lib/python3.9/site-packages/cherry/optim.py", line 62, in __init__ self.sync_parameters() File "/home/miranda9/miniconda3/envs/meta_learning_a100/lib/python3.9/site-packages/cherry/optim.py", line 78, in sync_parameters dist.broadcast(p.data, src=root) File "/home/miranda9/miniconda3/envs/meta_learning_a100/lib/python3.9/site-packages/torch/distributed/distributed_c10d.py", line 1090, in broadcast work = default_pg.broadcast([tensor], opts)RuntimeError: NCCL error in: ../torch/lib/c10d/ProcessGroupNCCL.cpp:911, unhandled system error, NCCL version 2.7.8其中一个回答建议nvcca和pytorch.version.cuda应该匹配，但它们并不匹配：
(meta_learning_a100) [miranda9@hal-dgx ~]$ python -c "import torch;print(torch.version.cuda)"11.1(meta_learning_a100) [miranda9@hal-dgx ~]$ nvcc -Vnvcc: NVIDIA (R) Cuda compiler driverCopyright (c) 2005-2020 NVIDIA CorporationBuilt on Wed_Jul_22_19:09:09_PDT_2020Cuda compilation tools, release 11.0, V11.0.221Build cuda_11.0_bu.TC445_37.28845127_0我如何让它们匹配？这是错误的原因吗？有人可以展示他们的pip、conda和nvcca版本，以便我看到哪种配置是有效的吗？
更多错误信息：
hal-dgx:21797:21797 [0] NCCL INFO Bootstrap : Using [0]enp226s0:141.142.153.83<0> [1]virbr0:192.168.122.1<0>hal-dgx:21797:21797 [0] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementationhal-dgx:21797:21797 [0] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [4]mlx5_4:1/IB [5]mlx5_5:1/IB [6]mlx5_6:1/IB [7]mlx5_7:1/IB ; OOB enp226s0:141.142.153.83<0>hal-dgx:21797:21797 [0] NCCL INFO Using network IBNCCL version 2.7.8+cuda11.1hal-dgx:21805:21805 [2] NCCL INFO Bootstrap : Using [0]enp226s0:141.142.153.83<0> [1]virbr0:192.168.122.1<0>hal-dgx:21799:21799 [1] NCCL INFO Bootstrap : Using [0]enp226s0:141.142.153.83<0> [1]virbr0:192.168.122.1<0>hal-dgx:21805:21805 [2] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementationhal-dgx:21799:21799 [1] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementationhal-dgx:21811:21811 [3] NCCL INFO Bootstrap : Using [0]enp226s0:141.142.153.83<0> [1]virbr0:192.168.122.1<0>hal-dgx:21811:21811 [3] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementationhal-dgx:21811:21811 [3] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [4]mlx5_4:1/IB [5]mlx5_5:1/IB [6]mlx5_6:1/IB [7]mlx5_7:1/IB ; OOB enp226s0:141.142.153.83<0>hal-dgx:21811:21811 [3] NCCL INFO Using network IBhal-dgx:21799:21799 [1] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [4]mlx5_4:1/IB [5]mlx5_5:1/IB [6]mlx5_6:1/IB [7]mlx5_7:1/IB ; OOB enp226s0:141.142.153.83<0>hal-dgx:21805:21805 [2] NCCL INFO NET/IB : Using [0]mlx5_0:1/IB [1]mlx5_1:1/IB [2]mlx5_2:1/IB [3]mlx5_3:1/IB [4]mlx5_4:1/IB [5]mlx5_5:1/IB [6]mlx5_6:1/IB [7]mlx5_7:1/IB ; OOB enp226s0:141.142.153.83<0>hal-dgx:21799:21799 [1] NCCL INFO Using network IBhal-dgx:21805:21805 [2] NCCL INFO Using network IBhal-dgx:21797:27906 [0] misc/ibvwrap.cc:280 NCCL WARN Call to ibv_create_qp failedhal-dgx:21797:27906 [0] NCCL INFO transport/net_ib.cc:360 -> 2hal-dgx:21797:27906 [0] NCCL INFO transport/net_ib.cc:437 -> 2hal-dgx:21797:27906 [0] NCCL INFO include/net.h:21 -> 2hal-dgx:21797:27906 [0] NCCL INFO include/net.h:51 -> 2hal-dgx:21797:27906 [0] NCCL INFO init.cc:300 -> 2hal-dgx:21797:27906 [0] NCCL INFO init.cc:566 -> 2hal-dgx:21797:27906 [0] NCCL INFO init.cc:840 -> 2hal-dgx:21797:27906 [0] NCCL INFO group.cc:73 -> 2 [Async thread]hal-dgx:21811:27929 [3] misc/ibvwrap.cc:280 NCCL WARN Call to ibv_create_qp failedhal-dgx:21811:27929 [3] NCCL INFO transport/net_ib.cc:360 -> 2hal-dgx:21811:27929 [3] NCCL INFO transport/net_ib.cc:437 -> 2hal-dgx:21811:27929 [3] NCCL INFO include/net.h:21 -> 2hal-dgx:21811:27929 [3] NCCL INFO include/net.h:51 -> 2hal-dgx:21811:27929 [3] NCCL INFO init.cc:300 -> 2hal-dgx:21811:27929 [3] NCCL INFO init.cc:566 -> 2hal-dgx:21811:27929 [3] NCCL INFO init.cc:840 -> 2hal-dgx:21811:27929 [3] NCCL INFO group.cc:73 -> 2 [Async thread]在添加以下代码后：
import osos.environ["NCCL_DEBUG"] = "INFO"回答：
根据@SimonB的回答中提供的pytorch网站链接，我执行了以下操作：
pip3 install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html这解决了我的问题。
