This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/
Other
1.34k
stars
462
forks
source link
cuDNN compile error on Tesla K80 GPU - error: too few arguments to function #146
@sadeepj @bittnt
Thanks for sharing this awesome piece of work.
I have run the caffe version on a Tesla K80 GPU. And the timing is ~4second. Now I am trying to use cuDNN to see what speedup it does to the code.
I have tried - cudnn-8.0-linux-x64-v5.1, v6.0, v7.
And all of them are taking me to the same error -
:~/cudnn_version/crfasrnn/caffe$ make PROTOC src/caffe/proto/caffe.proto CXX .build_release/src/caffe/proto/caffe.pb.cc CXX src/caffe/util/im2col.cpp In file included from ./include/caffe/util/device_alternate.hpp:40:0, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: ./include/caffe/util/cudnn.hpp: In function ‘const char* cudnnGetErrorString(cudnnStatus_t)’: ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING’ not handled in switch [-Wswitch] switch (status) { ^ ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_IN_PROGRESS’ not handled in switch [-Wswitch] ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_FP_OVERFLOW’ not handled in switch [-Wswitch] ./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::setConvolutionDesc(cudnnConvolutionStruct**, cudnnTensorDescriptor_t, cudnnFilterDescriptor_t, int, int, int, int)’: ./include/caffe/util/cudnn.hpp:105:70:error: too few arguments to function ‘cudnnStatus_t cudnnSetConvolution2dDescriptor(cudnnConvolutionDescriptor_t, int, int, int, int, int, int, cudnnConvolutionMode_t, cudnnDataType_t)’pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION)); ^ ./include/caffe/util/cudnn.hpp:12:28: note: in definition of macro ‘CUDNN_CHECK’ cudnnStatus_t status = condition; \ ^ In file included from ./include/caffe/util/cudnn.hpp:5:0, from ./include/caffe/util/device_alternate.hpp:40, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: /usr/local/cuda-8.0/include/cudnn.h:537:27: note: declared here cudnnStatus_t CUDNNWINAPI cudnnSetConvolution2dDescriptor( cudnnConvolutionDescriptor_t convDesc, ^ In file included from ./include/caffe/util/device_alternate.hpp:40:0, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: ./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::createPoolingDesc(cudnnPoolingStruct**, caffe::PoolingParameter_PoolMethod, cudnnPoolingMode_t*, int, int, int, int, int, int)’: ./include/caffe/util/cudnn.hpp:124:41: error: too few arguments to function ‘cudnnStatus_t cudnnSetPooling2dDescriptor(cudnnPoolingDescriptor_t, cudnnPoolingMode_t, cudnnNanPropagation_t, int, int, int, int, int, int)’ pad_h, pad_w, stride_h, stride_w)); ^ ./include/caffe/util/cudnn.hpp:12:28: note: in definition of macro ‘CUDNN_CHECK’ cudnnStatus_t status = condition; \ ^ In file included from ./include/caffe/util/cudnn.hpp:5:0, from ./include/caffe/util/device_alternate.hpp:40, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: /usr/local/cuda-8.0/include/cudnn.h:1031:27: note: declared here cudnnStatus_t CUDNNWINAPI cudnnSetPooling2dDescriptor( ^ Makefile:533: recipe for target '.build_release/src/caffe/util/im2col.o' failed make: *** [.build_release/src/caffe/util/im2col.o] Error 1
@sadeepj @bittnt Thanks for sharing this awesome piece of work.
I have run the caffe version on a Tesla K80 GPU. And the timing is ~4second. Now I am trying to use cuDNN to see what speedup it does to the code. I have tried - cudnn-8.0-linux-x64-v5.1, v6.0, v7. And all of them are taking me to the same error -
:~/cudnn_version/crfasrnn/caffe$ make PROTOC src/caffe/proto/caffe.proto CXX .build_release/src/caffe/proto/caffe.pb.cc CXX src/caffe/util/im2col.cpp In file included from ./include/caffe/util/device_alternate.hpp:40:0, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: ./include/caffe/util/cudnn.hpp: In function ‘const char* cudnnGetErrorString(cudnnStatus_t)’: ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING’ not handled in switch [-Wswitch] switch (status) { ^ ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_IN_PROGRESS’ not handled in switch [-Wswitch] ./include/caffe/util/cudnn.hpp:18:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_FP_OVERFLOW’ not handled in switch [-Wswitch] ./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::setConvolutionDesc(cudnnConvolutionStruct**, cudnnTensorDescriptor_t, cudnnFilterDescriptor_t, int, int, int, int)’: ./include/caffe/util/cudnn.hpp:105:70:error: too few arguments to function ‘cudnnStatus_t cudnnSetConvolution2dDescriptor(cudnnConvolutionDescriptor_t, int, int, int, int, int, int, cudnnConvolutionMode_t, cudnnDataType_t)’pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION)); ^ ./include/caffe/util/cudnn.hpp:12:28: note: in definition of macro ‘CUDNN_CHECK’ cudnnStatus_t status = condition; \ ^ In file included from ./include/caffe/util/cudnn.hpp:5:0, from ./include/caffe/util/device_alternate.hpp:40, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: /usr/local/cuda-8.0/include/cudnn.h:537:27: note: declared here cudnnStatus_t CUDNNWINAPI cudnnSetConvolution2dDescriptor( cudnnConvolutionDescriptor_t convDesc, ^ In file included from ./include/caffe/util/device_alternate.hpp:40:0, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: ./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::createPoolingDesc(cudnnPoolingStruct**, caffe::PoolingParameter_PoolMethod, cudnnPoolingMode_t*, int, int, int, int, int, int)’: ./include/caffe/util/cudnn.hpp:124:41: error: too few arguments to function ‘cudnnStatus_t cudnnSetPooling2dDescriptor(cudnnPoolingDescriptor_t, cudnnPoolingMode_t, cudnnNanPropagation_t, int, int, int, int, int, int)’ pad_h, pad_w, stride_h, stride_w)); ^ ./include/caffe/util/cudnn.hpp:12:28: note: in definition of macro ‘CUDNN_CHECK’ cudnnStatus_t status = condition; \ ^ In file included from ./include/caffe/util/cudnn.hpp:5:0, from ./include/caffe/util/device_alternate.hpp:40, from ./include/caffe/common.hpp:19, from ./include/caffe/util/math_functions.hpp:9, from src/caffe/util/im2col.cpp:6: /usr/local/cuda-8.0/include/cudnn.h:1031:27: note: declared here cudnnStatus_t CUDNNWINAPI cudnnSetPooling2dDescriptor( ^ Makefile:533: recipe for target '.build_release/src/caffe/util/im2col.o' failed make: *** [.build_release/src/caffe/util/im2col.o] Error 1Any suggestion on what I could be missing here ?