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
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