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facebookarchive / caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.
https://caffe2.ai
Apache License 2.0
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Windows 10 Build failure on arg_ops.cu #2489

Open TrentWeiss opened 6 years ago

TrentWeiss commented 6 years ago

If this is a build issue, please fill out the template below.

System information

CMake summary output

******** Summary ********
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The error I get is: C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here C:/Users/Madhur/Documents/git_repos/caffe2\caffe2/operators/arg_ops.h(17): error : invalid base class [C:\Users\Madhur\ Documents\git_repos\caffe2\build\caffe2\caffe2_gpu.vcxproj] detected during instantiation of class "caffe2::ArgOpBase<T, Context> [with T=T, Context=caffe2::CUDAContex t]" C:/Users/Madhur/Documents/git_repos/caffe2/caffe2/operators/arg_ops.cu(52): here arg_ops.cu CUSTOMBUILD : nvcc error : 'cicc' died with status 0xC0000005 (ACCESS_VIOLATION) [C:\Users\Madhur\Documents\git_repos\c affe2\build\caffe2\caffe2_gpu.vcxproj] CMake Error at caffe2_gpu_generated_arg_ops.cu.obj.Release.cmake:275 (message): Error generating file C:/Users/Madhur/Documents/git_repos/caffe2/build/caffe2/CMakeFiles/caffe2_gpu.dir/operators/Release/caffe2_gpu_gene rated_arg_ops.cu.obj

Any ideas what would cause this?

TrentWeiss commented 6 years ago

Also note that the CPU version of Caffe2 builds just fine, but I need GPU acceleration for my application.

pjh5 commented 6 years ago

Is "nvcc error : 'cicc' died with status 0xC0000005 (ACCESS_VIOLATION)" the root cause of this? Does it look like cmake is finding nvcc correctly?

harrysummer commented 6 years ago

I am experiencing exactly the same issue on Win10 + VS2015 + CUDA9.0. It seems that partially-specialized class inheritance on Windows is very buggy. The following patch works for me. It defines separate class templates ArgMinOpCuda and ArgMaxOpCuda to void the class template inheritance. However, after applying this patch, the compilation would still fail because Eigen with CUDA is still not supported on Windows.

diff --git a/caffe2/operators/arg_ops.cu b/caffe2/operators/arg_ops.cu
index 99c31dfa8..8c6aa35a6 100644
--- a/caffe2/operators/arg_ops.cu
+++ b/caffe2/operators/arg_ops.cu
@@ -48,20 +48,20 @@ __global__ void ComputeArgCUDAKernel(

 } // namespace

-template <typename T>
-class ArgMaxOp<T, CUDAContext> final : public ArgOpBase<T, CUDAContext> {
+template <typename T, class Context>
+class ArgMaxOpCuda final : public ArgOpBase<T, Context> {
  public:
-  USE_OPERATOR_FUNCTIONS(CUDAContext);
+  USE_OPERATOR_FUNCTIONS(Context);

 #if EIGEN_VERSION_AT_LEAST(3, 3, 0)
-  ArgMaxOp(const OperatorDef& operator_def, Workspace* ws)
-      : ArgOpBase<T, CUDAContext>(operator_def, ws),
+ArgMaxOpCuda(const OperatorDef& operator_def, Workspace* ws)
+      : ArgOpBase<T, Context>(operator_def, ws),
         cuda_stream_(context_.cuda_stream()),
         stream_device_(&cuda_stream_, context_.cuda_gpu_id()),
         gpu_device_(&stream_device_) {}
 #else // EIGEN_VERSION_AT_LEAST(3, 3, 0)
-  ArgMaxOp(const OperatorDef& operator_def, Workspace* ws)
-      : ArgOpBase<T, CUDAContext>(operator_def, ws) {}
+ArgMaxOpCuda(const OperatorDef& operator_def, Workspace* ws)
+      : ArgOpBase<T, Context>(operator_def, ws) {}
 #endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)

  protected:
@@ -80,8 +80,8 @@ class ArgMaxOp<T, CUDAContext> final : public ArgOpBase<T, CUDAContext> {
 #endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)
 };

-template <typename T>
-bool ArgMaxOp<T, CUDAContext>::Compute(
+template <typename T, class Context>
+bool ArgMaxOpCuda<T, Context>::Compute(
     const T* X,
     const TIndex prev_size,
     const TIndex next_size,
@@ -107,20 +107,20 @@ bool ArgMaxOp<T, CUDAContext>::Compute(
   return true;
 }

-template <typename T>
-class ArgMinOp<T, CUDAContext> final : public ArgOpBase<T, CUDAContext> {
+template <typename T, class Context>
+class ArgMinOpCuda final : public ArgOpBase<T, Context> {
  public:
-  USE_OPERATOR_FUNCTIONS(CUDAContext);
+  USE_OPERATOR_FUNCTIONS(Context);

 #if EIGEN_VERSION_AT_LEAST(3, 3, 0)
-  ArgMinOp(const OperatorDef& operator_def, Workspace* ws)
-      : ArgOpBase<T, CUDAContext>(operator_def, ws),
+ArgMinOpCuda(const OperatorDef& operator_def, Workspace* ws)
+      : ArgOpBase<T, Context>(operator_def, ws),
         cuda_stream_(context_.cuda_stream()),
         stream_device_(&cuda_stream_, context_.cuda_gpu_id()),
         gpu_device_(&stream_device_) {}
 #else // EIGEN_VERSION_AT_LEAST(3, 3, 0)
-  ArgMinOp(const OperatorDef& operator_def, Workspace* ws)
-      : ArgOpBase<T, CUDAContext>(operator_def, ws) {}
+ArgMinOpCuda(const OperatorDef& operator_def, Workspace* ws)
+      : ArgOpBase<T, Context>(operator_def, ws) {}
 #endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)

  protected:
@@ -139,8 +139,8 @@ class ArgMinOp<T, CUDAContext> final : public ArgOpBase<T, CUDAContext> {
 #endif // EIGEN_VERSION_AT_LEAST(3, 3, 0)
 };

-template <typename T>
-bool ArgMinOp<T, CUDAContext>::Compute(
+template <typename T, class Context>
+bool ArgMinOpCuda<T, Context>::Compute(
     const T* X,
     const TIndex prev_size,
     const TIndex next_size,
@@ -166,7 +166,7 @@ bool ArgMinOp<T, CUDAContext>::Compute(
   return true;
 }

-REGISTER_CUDA_OPERATOR(ArgMax, ArgMaxOp<float, CUDAContext>);
-REGISTER_CUDA_OPERATOR(ArgMin, ArgMinOp<float, CUDAContext>);
+REGISTER_CUDA_OPERATOR(ArgMax, ArgMaxOpCuda<float, CUDAContext>);
+REGISTER_CUDA_OPERATOR(ArgMin, ArgMinOpCuda<float, CUDAContext>);

 } // namespace caffe2
harrysummer commented 6 years ago

To fully solve the issue, I think we need reimplement arg_ops.cu, without defining class template specializations, without using Eigen.

TrentWeiss commented 6 years ago

https://github.com/caffe2/caffe2/issues/2489#issuecomment-378398030 I don't think so. I was getting this issue before because CMake did not set CUDA_HOST_COMPILER properly, although it did find NVCC. I was able to fix this issue by manually specifying the correct path of cl.exe in the CMake variable CUDA_HOST_COMPILER.

harrysummer commented 6 years ago

I am still having this issue with the latest master branch in pytorch (VS2015, CUDA9.0). And the change I mentioned above now completely fixes compile error (because eigen tensor implementation was removed). I still think the problem roots in the VS compiler with template class partial specialization.

bddppq commented 6 years ago

@harrysummer Thanks. I have put up your suggestion here https://github.com/pytorch/pytorch/pull/6746 to fix our windows build