High Level APIs In

TensorflowSCG AI Research Group

Hyungjoo Cho

Who I am• (ex) LG Electronics, VC company

- Printing image processing - Proximity sensing - Gesture recognition

• Seoul City Gas, AI Research Group - Gas meter recognition - Text classification - Automatic pipeline network design system

• Interest - Human Action Recognition - Medical Image Processing - Generative Adversarial Networks

What is Tensorflow??

Tensorflow

• Open source software library for numerical computation using data flow graphs.

Why should we use Tensorflow??

*http://chainer.org/general/2017/02/08/Performance-of-Distributed-Deep-Learning-Using-ChainerMN.html

*https://arxiv.org/pdf/1608.07249.pdf

…???

Features

• Very low level (Flexible)

• Extensible

• Maintainable

• Higher level primitives (X)

High level API

Imagenet challenge

Break-through

2012 CHALLANGE

What happened??

Alex-net

Alex-net in Tensorflow

How about deeper net

VGG-Net

Its code

How about more deeper …

Deep Residual Networks

We might use a network which has more than 1k layers

* https://github.com/daviddao/awesome-very-deep-learning

…

Let’s make it as a module

VGG-Net

Wide-Res-Net

*https://github.com/szagoruyko/wide-residual-networks

Wide-Res-Net

Fusion-Net

Activation functions

tf.nn.sigmoid tf.nn.tanh tf.nn.relu

*http://adilmoujahid.com/posts/2016/06/introduction-deep-learning-python-caffe/

Others…

Leaky Relu/Parametric Relu

There’s no function…

Let’s make!!

Loss functions• L1

• L2

• Binomial Cross Entropy

• Multinomial Cross Entropy

• Gan loss

• Pixel wise loss

• …

Make!!

Benefits

• Fast iteration

• Best practices

• Easily modify

Should we make this ourselves?

There is a number of High level API in

Tensorflow

High level API in TF

• TF-Slim

• TF-layers, losses, metrics

• TF-Learn

• Keras

Thanks❤https://github.com/NySunShine/fusion-net