nextkitt

## Install tensorflow on OS X with GPU enabled.md

      
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                nextkitt
                / Install tensorflow on OS X with GPU enabled.md
            
            
              Created
              June 5, 2019 03:39
                — forked from myh1000/Install tensorflow on OS X with GPU enabled.md
            
              
                How to enable cuda support for tensor flow on Mac OS X (Tensorflow 0.9 on OS X 10.10)
              
          
    Instructions based off of  Mistobaan's gist.
These instructions are what I did to install tensorflow on my machine after a segmentation error occured while trying to import tensorflow in python took me 2 days to fix.
Prerequisites

Update brew and install latest packages.
brew update
brew install coreutils swig bazel


## build-tensorflow-from-source.md

      
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                nextkitt
                / build-tensorflow-from-source.md
            
            
              Created
              June 5, 2019 03:39
                — forked from Brainiarc7/build-tensorflow-from-source.md
            
              
                Build Tensorflow from source, for better performance on Ubuntu.
              
          
    Building Tensorflow from source on Ubuntu 16.04LTS for maximum performance:
TensorFlow is now distributed under an Apache v2 open source license on GitHub.
On Ubuntu 16.04LTS+:
Step 1. Install NVIDIA CUDA:
To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit as shown:

  
## build-tensorflow-from-source.md

      
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                nextkitt
                / build-tensorflow-from-source.md
            
            
              Created
              June 5, 2019 03:39
                — forked from Brainiarc7/build-tensorflow-from-source.md
            
              
                Build Tensorflow from source, for better performance on Ubuntu.
              
          
    Building Tensorflow from source on Ubuntu 16.04LTS for maximum performance:
TensorFlow is now distributed under an Apache v2 open source license on GitHub.
On Ubuntu 16.04LTS+:
Step 1. Install NVIDIA CUDA:
To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit as shown:

  
## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>


## get_local_ip.c
#include <stdio.h>
#include <string.h>
#include <sys/types.h>
#include <sys/socket.h>
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>
	#include <stdio.h>
	#include <string.h>
	#include <sys/types.h>
	#include <sys/socket.h>
	#include <sys/socket.h>
	#include <netinet/in.h>
	#include <arpa/inet.h>
	#include <unistd.h>