源代码编译tensorflow和tensorrt

提示：使用tensorrt 6一直莫名其妙编译失败，追踪问题也没有打印，所以改成tensorrt 5后成功了，后面有时间我再试试源码编译tensorrt。

环境

• cuda 10.1
• cudnn 7.6.3
• tensorrt 5.1.5
• tensorflow 1.14.0

步骤

将tensorrt 5解压后的include、lib文件夹复制到/usr目录下（合并）

解压tensorflow，进入之后

./configure

接下来弹出交互式选项

spicker@spicker-1:~/software/tensorflow$ ./configure 
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.25.2 installed.
Please specify the location of python. [Default is /home/spicker/anaconda3/bin/python]: 


Found possible Python library paths:
  /home/spicker/anaconda3/lib/python3.6/site-packages
Please input the desired Python library path to use.  Default is [/home/spicker/anaconda3/lib/python3.6/site-packages]

Do you wish to build TensorFlow with XLA JIT support? [Y/n]: n
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: N
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with ROCm support? [y/N]: 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.

Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.

Found CUDA 10.1 in:
    /usr/local/cuda/lib64
    /usr/local/cuda/include
Found cuDNN 7.6.3 in:
    /usr/local/cuda/lib64
    /usr/local/cuda/include
Found TensorRT 5 in:
    /usr/lib
    /usr/include


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, and that TensorFlow only supports compute capabilities >= 3.5 [Default is: 6.1]: 


Do you want to use clang as CUDA compiler? [y/N]: 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]: 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]: 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=numa        	# Build with NUMA 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 Apache Ignite support.
	--config=nokafka     	# Disable Apache Kafka support.
	--config=nonccl      	# Disable NVIDIA NCCL support.
Configuration finished

GPU support
To make the TensorFlow package builder with GPU support:

bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

Bazel build options
See the Bazel command-line reference for build options.
Building TensorFlow from source can use a lot of RAM. If your system is memory-constrained, limit Bazel’s RAM usage with: --local_ram_resources=2048.
The official TensorFlow packages are built with GCC 4 and use the older ABI. For GCC 5 and later, make your build compatible with the older ABI using: --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0". ABI compatibility ensures that custom ops built against the official TensorFlow package continue to work with the GCC 5 built package.

Build the package

./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

编译成C api库

bazel build --config opt --config=cuda //tensorflow/tools/lib_package:libtensorflow

ref: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/lib_package/README.md

ref：
https://blog.csdn.net/surtol/article/details/97638399#26GPU_237
https://yuxy.tk/2019/09/23/tensorflow_build_with_local_repository/