Qt官网没有提供适用于VS2015的Qt4版本，自己编译比较费劲。在此分享自己编译的32位版Qt4.8.7，适用于Vistual Studio 2015下的Qt4开发。
使用方法：下载解压后，放到自己需要的目录下，如C://Qt/Qt4.8.7，然后在VS2015的Qt-Addin插件菜单中添加Qt版本及路径即可。
Qt官网没有提供适用于VS2015的Qt4版本，自己编译比较费劲。在此分享自己编译的64位版Qt4.8.7，适用于Vistual Studio 2015下的Qt4开发。
使用方法：下载解压后，放到自己需要的目录下，如C://Qt/Qt4.8.7，然后在VS2015的Qt-Addin插件菜单中添加Qt版本及路径即可。
Qt官网没有提供适用于VS2015的Qt4版本，自己编译比较费劲。在此分享自己编译的32位版Qt4.7.1，适用于Vistual Studio 2015下的Qt4开发。
使用方法：下载解压后，放到自己需要的目录下，如C://Qt/Qt4.7.1，然后在VS2015的Qt-Addin插件菜单中添加Qt版本及路径即可。
Qt官网没有提供适用于VS2015的Qt4版本，自己编译比较费劲。在此分享自己编译的64位版Qt4.7.1，适用于Vistual Studio 2015下的Qt4开发。
使用方法：下载解压后，放到自己需要的目录下，如C://Qt/Qt4.7.1，然后在VS2015的Qt-Addin插件菜单中添加Qt版本及路径即可。
自编译tensorflow：
1.python3.5,tensorflow1.12;
2.支持cuda10.0,cudnn7.3.1,TensorRT-5.0.2.6-cuda10.0-cudnn7.3;
3.支持mkl,无MPI;
软硬件硬件环境：Ubuntu16.04,GeForce GTX 1080
配置信息：
hp@dla:~/work/ts_compile/tensorflow$ ./configure
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.19.1 installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3
Found possible Python library paths:
/usr/local/lib/python3.5/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/usr/local/lib/python3.5/dist-packages]
Do you wish to build TensorFlow with XLA JIT support? [Y/n]:
XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]:
No OpenCL SYCL support will be enabled for TensorFlow.
Do you wish to build TensorFlow with ROCm support? [y/N]:
No ROCm support will be enabled for TensorFlow.
Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.
Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 10.0]:
Please specify the location where CUDA 10.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-10.0
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]: 7.3.1
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-10.0]:
Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.
Please specify the location where TensorRT is installed. [Default is /usr/lib/x86_64-linux-gnu]:/home/hp/bin/TensorRT-5.0.2.6-cuda10.0-cudnn7.3/targets/x86_64-linux-gnu
Please specify the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1,6.1,6.1]:
Do you want to use clang as CUDA compiler? [y/N]:
nvcc will be used as CUDA compiler.
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Do you wish to build TensorFlow with MPI support? [y/N]:
No MPI support will be enabled for TensorFlow.
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]:
Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:
Not configuring the WORKSPACE for Android builds.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
--config=gdr # Build with GDR support.
--config=verbs # Build with libverbs support.
--config=ngraph # Build with Intel nGraph support.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
--config=noaws # Disable AWS S3 filesystem support.
--config=nogcp # Disable GCP support.
--config=nohdfs # Disable HDFS support.
--config=noignite # Disable Apacha Ignite support.
--config=nokafka # Disable Apache Kafka support.
--config=nonccl # Disable NVIDIA NCCL support.
Configuration finished
编译：
hp@dla:~/work/ts_compile/tensorflow$ bazel build --config=opt --config=mkl --verbose_failures //tensorflow/tools/pip_package:build_pip_package
卸载已有tensorflow：
hp@dla:~/temp$ sudo pip3 uninstall tensorflow
安装自己编译的成果：
hp@dla:~/temp$ sudo pip3 install tensorflow-1.12.0-cp35-cp35m-linux_x86_64.whl
自编译tensorflow：
1.python3.5,tensorflow1.12;
2.支持cuda10.0,cudnn7.3.1,TensorRT-5.0.2.6-cuda10.0-cudnn7.3;
3.无mkl支持;
软硬件硬件环境：Ubuntu16.04,GeForce GTX 1080 TI
配置信息：
hp@dla:~/work/ts_compile/tensorflow$ ./configure
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.19.1 installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3
Found possible Python library paths:
/usr/local/lib/python3.5/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/usr/local/lib/python3.5/dist-packages]
Do you wish to build TensorFlow with XLA JIT support? [Y/n]:
XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]:
No OpenCL SYCL support will be enabled for TensorFlow.
Do you wish to build TensorFlow with ROCm support? [y/N]:
No ROCm support will be enabled for TensorFlow.
Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.
Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 10.0]:
Please specify the location where CUDA 10.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-10.0
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]: 7.3.1
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-10.0]:
Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.
Please specify the location where TensorRT is installed. [Default is /usr/lib/x86_64-linux-gnu]://home/hp/bin/TensorRT-5.0.2.6-cuda10.0-cudnn7.3/targets/x86_64-linux-gnu
Please specify the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1,6.1,6.1]:
Do you want to use clang as CUDA compiler? [y/N]:
nvcc will be used as CUDA compiler.
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Do you wish to build TensorFlow with MPI support? [y/N]:
No MPI support will be enabled for TensorFlow.
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]:
Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:
Not configuring the WORKSPACE for Android builds.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
--config=gdr # Build with GDR support.
--config=verbs # Build with libverbs support.
--config=ngraph # Build with Intel nGraph support.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
--config=noaws # Disable AWS S3 filesystem support.
--config=nogcp # Disable GCP support.
--config=nohdfs # Disable HDFS support.
--config=noignite # Disable Apacha Ignite support.
--config=nokafka # Disable Apache Kafka support.
--config=nonccl # Disable NVIDIA NCCL support.
Configuration finished
编译：
bazel build --config=opt --verbose_failures //tensorflow/tools/pip_package:build_pip_package
卸载已有tensorflow：
hp@dla:~/temp$ sudo pip3 uninstall tensorflow
安装自己编译的成果：
hp@dla:~/temp$ sudo pip3 install tensorflow-1.12.0-cp35-cp35m-linux_x86_64.whl
