Yolo in colab # Make error in google COLAB !!

[Rahul-Venugopal]

Hi ,

I am trying to train YOLOv3 using colab and I get an error when I run make in yolo Steps I have followed to run make is as in the figure

After running !make in my darknet directory in google drive , I am getting following error

nvcc  -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/  -DOPENCV `pkg-config --cflags opencv`  -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options "-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include" -c ./src/network_kernels.cu -o obj/network_kernels.o
include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

nvcc  -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=[sm_50,compute_50] -gencode arch=compute_52,code=[sm_52,compute_52] -gencode arch=compute_61,code=[sm_61,compute_61] -Iinclude/  -DOPENCV `pkg-config --cflags opencv`  -DGPU -I/usr/local/cuda/include/ -DCUDNN --compiler-options "-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include" -c ./src/avgpool_layer_kernels.cu -o obj/avgpool_layer_kernels.o
include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

include/darknet.h(48): warning: declaration requires a typedef name

g++ -std=c++11 -Iinclude/  -DOPENCV `pkg-config --cflags opencv`  -DGPU -I/usr/local/cuda/include/ -DCUDNN -Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -Ofast -DOPENCV -DGPU -DCUDNN -I/usr/local/cudnn/include obj/http_stream.o obj/gemm.o obj/utils.o obj/cuda.o obj/convolutional_layer.o obj/list.o obj/image.o obj/activations.o obj/im2col.o obj/col2im.o obj/blas.o obj/crop_layer.o obj/dropout_layer.o obj/maxpool_layer.o obj/softmax_layer.o obj/data.o obj/matrix.o obj/network.o obj/connected_layer.o obj/cost_layer.o obj/parser.o obj/option_list.o obj/darknet.o obj/detection_layer.o obj/captcha.o obj/route_layer.o obj/writing.o obj/box.o obj/nightmare.o obj/normalization_layer.o obj/avgpool_layer.o obj/coco.o obj/dice.o obj/yolo.o obj/detector.o obj/layer.o obj/compare.o obj/classifier.o obj/local_layer.o obj/swag.o obj/shortcut_layer.o obj/activation_layer.o obj/rnn_layer.o obj/gru_layer.o obj/rnn.o obj/rnn_vid.o obj/crnn_layer.o obj/demo.o obj/tag.o obj/cifar.o obj/go.o obj/batchnorm_layer.o obj/art.o obj/region_layer.o obj/reorg_layer.o obj/reorg_old_layer.o obj/super.o obj/voxel.o obj/tree.o obj/yolo_layer.o obj/upsample_layer.o obj/convolutional_kernels.o obj/activation_kernels.o obj/im2col_kernels.o obj/col2im_kernels.o obj/blas_kernels.o obj/crop_layer_kernels.o obj/dropout_layer_kernels.o obj/maxpool_layer_kernels.o obj/network_kernels.o obj/avgpool_layer_kernels.o -o darknet -lm -pthread  `pkg-config --libs opencv`  -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand -L/usr/local/cudnn/lib64 -lcudnn -lstdc++ 
/usr/bin/ld: obj/yolo.o: relocation R_X86_64_32 against `.rodata.str1.8' can not be used when making a PIE object; recompile with -fPIC
/usr/bin/ld: obj/yolo_layer.o: relocation R_X86_64_32 against `.rodata.str1.1' can not be used when making a PIE object; recompile with -fPIC
/usr/bin/ld: final link failed: Nonrepresentable section on output
collect2: error: ld returned 1 exit status
Makefile:133: recipe for target 'darknet' failed
make: *** [darknet] Error 1

I read that it may be a problem related to gcc and if it is of any help the output of !gcc -v is

Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper
OFFLOAD_TARGET_NAMES=nvptx-none
OFFLOAD_TARGET_DEFAULT=1
Target: x86_64-linux-gnu
Configured with: ../src/configure -v --with-pkgversion='Ubuntu 7.3.0-27ubuntu1~18.04' --with-bugurl=file:///usr/share/doc/gcc-7/README.Bugs --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --prefix=/usr --with-gcc-major-version-only --program-suffix=-7 --program-prefix=x86_64-linux-gnu- --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-vtable-verify --enable-libmpx --enable-plugin --enable-default-pie --with-system-zlib --with-target-system-zlib --enable-objc-gc=auto --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-offload-targets=nvptx-none --without-cuda-driver --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu
Thread model: posix
gcc version 7.3.0 (Ubuntu 7.3.0-27ubuntu1~18.04) 

[AlexeyAB]

@Rahul-Venugopal Did you solve it?

[Rahul-Venugopal]

@AlexeyAB not yet

Any suggestions ?

[AlexeyAB]

@Rahul-Venugopal Try to change this line: https://github.com/AlexeyAB/darknet/blob/bf6b40f4e92bd8a4eb2d94ca8ef456ac2ebc2508/Makefile#L60 to this CFLAGS=-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC

and do

make clean
make

[Rahul-Venugopal]

Hi @AlexeyAB , Thanks for your quick response . Yes now it works fine and I have tested on on some images too. Everything is fine .

I have started training with colab and after 100 iterations chart.png is created as well as weights got saved in backup folder. Till now everything works fine and hope that training goes well.

Thanks again @AlexeyAB for your great support.

[Rahul-Venugopal]

Hi @AlexeyAB , I have to make darknet whenever I start a new session in colab. Is it normal or Is there any way to save the settings ?