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# Wasserstein Generative Adversarial Networks | ||
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## Loss Function | ||
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* used ``sce loss`` at D/G nets. | ||
* used ``gradient penalty`` | ||
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## Architecture Networks | ||
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* Same with the WGAN paper. | ||
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*DIFFS* | *WGAN Paper* | *ME* | | ||
:---: | :---: | :---: | | ||
**Networks** | ``Resnet like`` | ``simple 4 conv nets`` | | ||
* Same with the `WGAN` paper. | ||
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## Tensorboard | ||
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![result](./wgan_tb.png) | ||
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> Elapsed time : 1h 7m 7s with ``GTX 1060 6GB x 1`` | ||
| *Difference* | *Paper* | *Mine* | | ||
| :---: | :---: | :---: | | ||
| **Networks** | ``ResNet like`` | ``simple 4 conv nets`` | | ||
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## Result | ||
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*Name* | *Global Step 10k* | *Global Step 25k* | *Global Step 50k* | ||
:---: | :---: | :---: | :---: | ||
**WGAN-GP** | ![img](./gen_img/train_00010000.png) | ![img](./gen_img/train_00025000.png) | ![img](./gen_img/train_00050000.png) | ||
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## To-Do | ||
* | ||
*Name* | *Epoch 1* | *Epoch 20* | *Epoch 1 ~ 35* | | ||
:---: | :---: | :---: | :---: | | ||
**WGAN** | ![img](outputs/1.png) | ![img](outputs/20.png) | ![gif](outputs/1-35.gif) | |
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