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kdgan's Introduction

KDGAN

knowledge distillation generative adversarial network
https://github.com/cvtower/kdgan

[email protected] Unit 1803, 280 Spencer Street 5217295265283899

Extension

Shakeout: A new approach to regularized deep neural network training

Server

ssh [email protected] # cpu
ssh [email protected] # gpu xw
ssh [email protected] # gpu cz

Problem

PermissionError: [Errno 13] Permission denied sudo chmod -R ugo+rw /data

Learning to learn

conda create -n venv python=2.7 pip install tensorflow==1.6.0 pip install dm-sonnet==1.7 pip install tensorflow-probability==0.0.1 pip install dill python train.py --problem=quadratic --save_path=./quadratic

JointGAN

pip install tensorflow==1.0.0 pip install easydict nltk pandas prettytensor progressbar python-dateutil torchfile pip install git+git://github.com/bdusell/rougescore.git git clone [email protected]:tylin/coco-caption.git sys.path.append('Projects/kdgan/code/jointgan')

YFCC100M

wget http://download.maxmind.com/download/worldcities/worldcitiespop.txt.gz gunzip worldcitiespop.txt.gz file -i worldcitiespop.txt

00 Line number
01 Photo/video identifier
02 Photo/video hash
03 User NSID
04 User nickname
05 Date taken
06 Date uploaded
07 Capture device
08 Title
09 Description
10 User tags (comma-separated)
11 Machine tags (comma-separated)
12 Longitude
13 Latitude
14 Accuracy of the longitude and latitude coordinates (1=world level accuracy)
15 Photo/video page URL
16 Photo/video download URL
17 License name
18 License URL
19 Photo/video server identifier
20 Photo/video farm identifier
21 Photo/video secret
22 Photo/video secret original
23 Extension of the original photo
24 Photos/video marker (0=photo, 1=video)

kdgan's People

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kdgan's Issues

Horrible codes.

In this codes, there are no exact explanations for exact training setup.
And there is no cifar-10 evaluation code. Besides these codes are somewhat spaghetti.
Furthermore, according to these codes in utils and lenet_utils, the proposed models cannot be reproduced exactly. More than anything Horrible, Horrible readability.

About KDGAN on CIFAR10

Hi, I'm reading your code but I find there is no code about KDGAN on CIFAR10. Only MNIST is given. If possible, could you please give the kdgan code on CIFAR10 ?

Can't find gumbel_softmax in utils module when running run_pretrain.sh from mdlcompr folder

Traceback (most recent call last):
File "pretrain_gen.py", line 28, in
tn_gen = GEN(flags, mnist.train, is_training=True)
File "/Users/florinmatei/Projects/KDGAN2/KDGAN/mdlcompr/gen_model.py", line 35, in init
self.gumbel_labels = utils.gumbel_softmax(self.logits, self.gumbel_temperature)
AttributeError: 'module' object has no attribute 'gumbel_softmax'

There is a gumbel_softmax.py in mdlcompr folder but if I'm trying to use it directly (by importing it in get_model.py module) I'm running into issues with TensorFlow saying that tf.shape is not a valid method so knowing what TensorFlow version is another important thing we need to know.

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