之前LZ在编译tf1.14接口的时候，其实就已经强调了Eigen 版本选择的重要性，但是我们经常使用不止一种三方库，在使用不同算法库的时候其实就会存在这样那样动态库冲突的情况，而且这种情况最为头疼。。。
下面是LZ的一段测试代码
#include<stdio.h>#include<iostream>...tf的一些头文件...#include"opencv2/opencv.hpp"#include"opencv2/core/cuda.hpp"#include"opencv2/cudawarping.hpp"#include"opencv2/gpu/gpu.hpp"intmain(){intnum_devices=cv::cuda::getCudaEnabledDeviceCount();if(num_devices<=0){std::cerr<<"There is no device."<<std::endl;return-1;}intenable_device_id=-1;for(inti=0;i<num_devices;i++){cv::cuda::DeviceInfodev_info(i);if(dev_info.isCompatible()){enable_device_id=i;}}if(enable_device_id<0){std::cerr<<"GPU module isn't built for GPU"<<std::endl;return-1;}cv::cuda::setDevice(enable_device_id);std::cout<<"GPU is ready, device ID is "<<num_devices<<"\n";// read one imagecv::Mat src_image=cv::imread("../111.jpg");cv::Mat dst_image;cv::cuda::GpuMatg_src_img(src_image);cv::cuda::GpuMat g_dst_image;cv::cuda::resize(g_src_img,g_dst_image,cv::Size(WIDTH,HEIGHT));g_dst_image.download(dst_image);cv::imshow("test",dst_image);cv::waitKey(0);cv::imwrite("test.jpg",dst_image);return0;}后来编译就出问题了，主要还是Eigen的问题
tensorflow-r1.14/tensorflow/contrib/makefile/downloads/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h: In static member function ‘static void Eigen::internal::TensorBlockIO<Scalar, StorageIndex, NumDims, Layout, BlockRead>::Copy(const Block&, StorageIndex, const Dimensions&, const Dimensions&, const Scalar*, Scalar*)’: tensorflow-r1.14/tensorflow/contrib/makefile/downloads/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h:393:63: error: the value of ‘j’ is not usable in a constant expression if (++block_iter_state[j].count < block_iter_state[j].size) { ^ tensorflow-r1.14/tensorflow/contrib/makefile/downloads/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h:392:16: note: ‘int j’ is not const for (int j = 0; j < num_squeezed_dims; ++j) { ^ tensorflow-r1.14/tensorflow/contrib/makefile/downloads/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h:393:35: error: parse error in template argument list if (++block_iter_state[j].count < block_iter_state[j].size) { ...提取出主要问题
error: the value of ‘j’ is not usable in a constant expression发现在github上也有类似问题https://github.com/tensorflow/tensorflow/issues/33280
但是并没有解决方案啊。。。
最后在LZ的仔细排查下最后发现了自己犯了一个很愚蠢的错误，在LZ的笔记本上有两个版本的OpenCV，
//这三行使用的是OpenCV4.2.0版本的#include"opencv2/opencv.hpp"#include"opencv2/core/cuda.hpp"#include"opencv2/cudawarping.hpp"//这个头文件使用的是OpenCV2.4.9版本的，这种肯定会出问题的，#include"opencv2/gpu/gpu.hpp"但是报的居然是tf中Eigen的问题，排查好久，差点以为要重新编译库了/(ㄒoㄒ)/~~
不知道github上那小哥解决问题了没有。。。
