PyTorchIntroduction - GitHub Pages
CSI4108-01 ARTIFICIAL INTELLIGENCE
1
PyTorch Introduction
2018. 5. 11.
Lee, Gyeongbok
PyTorch Introduction
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Contents
? Very Basic about PyTorch
? Tensor
?
? Network Composition
?
? Some Examples
? Simple Linear Network (1x1) ? Image classification with CNN
?
PyTorch Introduction
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Recap: Training Process
1. Sample labeled data (batch input)
2. Forward it through the network, get predictions
4. Update the network weights
3. Back-propagate the errors
Optimize (min. or max.) objective/cost function () Generate error signal that measures difference between predictions and target values
PyTorch Introduction
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Deep Learning Frameworks
? Early days:
? Caffe, Torch, Theano
? Tensorflow (by Google) ? PyTorch (by Facebook Research) ? DyNet (by CMU)
? Keras (TF backend)
PyTorch Introduction
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Why use framework?
Without using framework...
We needs to define all of things
Forward definition Loss definition
Backpropagate definition Manual weight update
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