vellamike/install-tensorflow.md

## install-tensorflow.md

      
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              install-tensorflow.md
            
          
    Building TensorFlow from source for Jetson TX2 with Jetpack 3.2

Jetpack 3.2 includes Cuda 9 and CuDNN 7 so it is necessary to compile it from source.
Step 1 - Get Java

sudo apt-get install openjdk-8-jdk

Step 2 - Get some dependencies

sudo apt-get install python3-numpy swig python3-dev python3-pip python3-wheel -y

Step 3 - Get Bazel

wget --no-check-certificate https://github.com/bazelbuild/bazel/releases/download/0.10.0/bazel-0.10.0-dist.zip
unzip bazel-0.10.0-dist.zip -d bazel-0.10.0-dist
cd bazel-0.10.0-dist
./compile.sh
cp output/bazel /usr/local/bin

Step 4 - clone tensorflow

git clone https://github.com/tensorflow/tensorflow # You may wish to check out a speicfic branch here

Step 5 - configure tensorflow

cd tensorflow
# This will prompt you with various questions, my answers are included as an example of what worked for me.
./configure

You have bazel 0.10.0- (@non-git) 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 jemalloc as malloc support? [Y/n]: 
jemalloc as malloc support will be enabled for TensorFlow.

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

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

Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: n
No Amazon S3 File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Apache Kafka Platform support? [y/N]: n
No Apache Kafka Platform support will be enabled for TensorFlow.

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 GDR support? [y/N]: 
No GDR support will be enabled for TensorFlow.

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

Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 9.0]: 


Please specify the location where CUDA 9.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-9.0


Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]: 


Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-9.0]:


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

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: 3.5,5.2]


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]: 


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 tools/bazel.rc for more details.
	--config=mkl         	# Build with MKL support.
	--config=monolithic  	# Config for mostly static monolithic build.
	--config=tensorrt    	# Build with TensorRT support.
Configuration finished


Step 6 - Build tensorflow

# Build a whl
bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

Step 7 - Make a whl

bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg #put the whl in /tmp/tensorflow_pkg

Step 8 - install the whl

pip3 install /tmp/tensorflow_pkg/tensorflow-1.6.0rc0-cp35-cp35m-linux_aarch64.whl #depending on your tensorflow/python version this file may have a different name