/tf-boilerplate

Tensorflow Boilerplate

Primary LanguagePythonOtherNOASSERTION

Tensorflow Boiler-plate

Ayan Chakrabarti <ayanc@ttic.edu>

This repository contains boiler-plate code that you can use as a starting point to write your tensorflow code for neural-network training. This isn't a library of classes for general purpose use: modify the code to adapt it to your task. I have created this repo mainly as a place to put reference code for students I work with. But all code is released for public use under the MIT license.

There are currently two directories:

  1. cifar100: Somewhat simpler of the two setups. See train_val.py and test.py and follow pointers from there. If you want to run a quick test, remember to set the environment variable CIFAR100 to the directory where you extracted the cifar100 dataset, before you run train_val.py.

  2. imagenet: Imagenet training and validation with a vgg-16 architecture network. Start by looking at train.py / train_avg.py and val.py. You'll need to create the train.txt and val.txt with lists of JPEG file names and labels: you can use data/mk_data.sh to do this.