Jun Deng jundengdeng

jundengdeng / build-tensorflow-from-source.md

Created September 21, 2017 14:07 — forked from Brainiarc7/build-tensorflow-from-source.md

Build Tensorflow from source, for better performance

Building Tensorflow from source on Linux for maximum performance:

TensorFlow is now distributed under an Apache v2 open source license on GitHub.

Step 1. Install NVIDIA CUDA:

To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit.

Step 2. Install NVIDIA cuDNN:

jundengdeng / waya-dl-setup.sh

Created September 21, 2017 11:46 — forked from mjdietzx/waya-dl-setup.sh

Install CUDA Toolkit v8.0 and cuDNN v6.0 on Ubuntu 16.04

	#!/bin/bash

	# install CUDA Toolkit v8.0
	# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
	CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
	wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
	sudo dpkg -i ${CUDA_REPO_PKG}
	sudo apt-get update
	sudo apt-get -y install cuda

jundengdeng / install_driver_375.sh

Created September 18, 2017 08:35 — forked from jcjohnson/install_driver_375.sh

	# Installs 375.66 for CUDA 8 on Ubuntu 16.04

	wget http://us.download.nvidia.com/tesla/375.66/nvidia-diag-driver-local-repo-ubuntu1604_375.66-1_amd64.deb
	sudo dpkg -i nvidia-diag-driver-local-repo-ubuntu1604_375.66-1_amd64.deb
	sudo apt-get update
	sudo apt-get --allow-unauthenticated --assume-yes install cuda-drivers
	sudo reboot now

jundengdeng / tensorflow_finetune.py

Created September 18, 2017 08:32 — forked from omoindrot/tensorflow_finetune.py

Example TensorFlow script for fine-tuning a VGG model (uses tf.contrib.data)

	"""
	Example TensorFlow script for finetuning a VGG model on your own data.
	Uses tf.contrib.data module which is in release v1.2
	Based on PyTorch example from Justin Johnson
	(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

	Required packages: tensorflow (v1.2)
	Download the weights trained on ImageNet for VGG:
	```
	wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

jundengdeng / gist:90424db1f2fb0f04221782b9809129b1

Created August 23, 2016 07:15 — forked from farrajota/conv_to_linear.lua

Fully connected to convolution layer

	require 'nn'

	-- you just need to provide the linear module you want to convert,
	-- and the dimensions of the field of view of the linear layer

	function convertLinear2Conv1x1(linmodule,in_size)
	--[[
	Convert Linear modules to convolution modules.

	Arguments