Error when trying to compile

[akonstantinou]

This is what i get after i type "make all"

nvcc -g -std=c++11 -Ipython -c "import tensorflow; print(tensorflow.sysconfig.get_include())" -I"/usr/local/cuda-8.0/include" -DGOOGLE_CUDA=1 -D_MWAITXINTRIN_H_INCLUDED -D_FORCE_INLINES -D__STRICT_ANSI__ -D_GLIBCXX_USE_CXX11_ABI=0 -c -gencode=arch=compute_30,code=sm_30 FlowNet2_src/ops/preprocessing/kernels/data_augmentation.cu.cc -x cu -Xcompiler -fPIC -o FlowNet2_src/ops/build/data_augmentation.o
/home/user/virtualenvs/virtual3/lib/python3.5/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
In file included from /home/user/virtualenvs/virtual3/lib/python3.5/site-packages/tensorflow/include/tensorflow/core/platform/mutex.h:31:0,
from /home/user/virtualenvs/virtual3/lib/python3.5/site-packages/tensorflow/include/tensorflow/core/framework/variant.h:31,
from /home/user/virtualenvs/virtual3/lib/python3.5/site-packages/tensorflow/include/tensorflow/core/framework/allocator.h:26,
from /home/user/virtualenvs/virtual3/lib/python3.5/site-packages/tensorflow/include/tensorflow/core/framework/op_kernel.h:23,
from FlowNet2_src/ops/preprocessing/kernels/data_augmentation.h:4,
from FlowNet2_src/ops/preprocessing/kernels/data_augmentation.cu.cc:6:
/home/user/virtualenvs/virtual3/lib/python3.5/site-packages/tensorflow/include/tensorflow/core/platform/default/mutex.h:25:22: fatal error: nsync_cv.h: No such file or directory
compilation terminated.
Makefile:62: recipe for target 'preprocessing' failed
make: *** [preprocessing] Error 1

[Yuliang-Zou]

Which TF version are you using?

And maybe you can check this

[Timthony]

同样错误，用的tensorflow1.4版本，make all出错

[Yuliang-Zou]

@Timthony You need to use 1.2. We don't support other versions currently.

[Timthony]

@Timthony You need to use 1.2. We don't support other versions currently.

Why do the results run differently from yours?