PointRCNN
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运行环境
我新装了一个ubantu16.04的服务器,但是在执行 python setup.py install时就会出错。能否告知一下测试的环境,包括gcc版本,cuda版本,python版本等。
In file included from /usr/local/python3.9/lib/python3.9/site-packages/torch/include/ATen/Parallel.h:149:0, from /usr/local/python3.9/lib/python3.9/site-packages/torch/include/TH/THTensorApply.h:4, from /usr/local/python3.9/lib/python3.9/site-packages/torch/include/TH/THTensor.h:5, from /usr/local/python3.9/lib/python3.9/site-packages/torch/include/THC/THCTensor.h:4, from /usr/local/python3.9/lib/python3.9/site-packages/torch/include/THC/THC.h:13, from src/ball_query.cpp:3: /usr/local/python3.9/lib/python3.9/site-packages/torch/include/ATen/ParallelOpenMP.h:84:0: warning: ignoring #pragma omp parallel [-Wunknown-pragmas] #pragma omp parallel for if ((end - begin) >= grain_size) ^ src/ball_query.cpp: In function ‘int ball_query_wrapper_fast(int, int, int, float, int, at::Tensor, at::Tensor, at::Tensor)’: src/ball_query.cpp:10:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations] #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x, " must be a CUDAtensor ") ^ src/ball_query.cpp:12:24: note: in expansion of macro ‘CHECK_CUDA’ #define CHECK_INPUT(x) CHECK_CUDA(x);CHECK_CONTIGUOUS(x) ^ src/ball_query.cpp:16:5: note: in expansion of macro ‘CHECK_INPUT’ CHECK_INPUT(new_xyz_tensor); ^
采用python==3.6.2,cuda=10.0可复现成功,可供参考。