Python Keras无法在没有后端的情况下编译

当我尝试编译keras文档中的示例时，出现以下错误

/usr/include/string.h: In function ‘void* __mempcpy_inline(void*, const void*, size_t)’:
/usr/include/string.h:652:42: error: ‘memcpy’ was not declared in this scope
   return (char *) memcpy (__dest, __src, __n) + __n;
                                          ^
ERROR (theano.sandbox.cuda): Failed to compile cuda_ndarray.cu: ('nvcc return status', 1, 'for cmd', 'nvcc -shared -O3 -m64 -Xcompiler -DCUDA_NDARRAY_CUH=mc72d035fdf91890f3b36710688069b2e,-DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION,-fPIC,-fvisibility=hidden -Xlinker -rpath,/home/chase/.theano/compiledir_Linux-4.4--generic-x86_64-with-Ubuntu-16.04-xenial-x86_64-3.5.1+-64/cuda_ndarray -I/usr/local/lib/python3.5/dist-packages/theano/sandbox/cuda -I/usr/lib/python3/dist-packages/numpy/core/include -I/usr/include/python3.5m -I/usr/local/lib/python3.5/dist-packages/theano/gof -o /home/chase/.theano/compiledir_Linux-4.4--generic-x86_64-with-Ubuntu-16.04-xenial-x86_64-3.5.1+-64/cuda_ndarray/cuda_ndarray.so mod.cu -L/usr/lib -lcublas -lpython3.5m -lcudart')

我在Ubuntu 16.04上。我使用的是从默认存储库安装的CUDA 7.5。我使用CUDA编译了一些我自己的CUDA程序以及ArrayFire程序，因此我知道CUDA正在工作

以下是我试图编译的内容

from keras.models import Sequential

model = Sequential()
from keras.layers.core import Dense, Activation

model.add(Dense(output_dim=64, input_dim=100))
model.add(Activation("relu"))
model.add(Dense(output_dim=10))
model.add(Activation("softmax"))

model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy'])

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GCC 5.3和CUDA似乎存在问题。我不得不注释掉/usr/include/string.h中的以下更改，现在它可以工作了