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nash

Implementation for NASH: Toward End-to-End Neural Architecture for Generative Semantic

Run

bash prepare.sh
python main.py

Result

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.79it/s]
train epoch 1 : 8.408826106259612
Top 100 precision : 0.2

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.79it/s]
train epoch 2 : 8.1568154226355
Top 100 precision : 0.33

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.84it/s]
train epoch 3 : 8.077799324275684
Top 100 precision : 0.41

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.93it/s]
train epoch 4 : 8.008174208556714
Top 100 precision : 0.46

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 76.38it/s]
train epoch 5 : 7.952126769792466
Top 100 precision : 0.49

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 76.08it/s]
train epoch 6 : 7.902592514647918
Top 100 precision : 0.51

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.69it/s]
train epoch 7 : 7.859901969935618
Top 100 precision : 0.51

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.63it/s]
train epoch 8 : 7.819372190910132
Top 100 precision : 0.52

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.93it/s]
train epoch 9 : 7.786398746529404
Top 100 precision : 0.53

100%|████████████████████████████████████████████████████████████████████| 588/588 [00:07<00:00, 75.61it/s]
train epoch 10 : 7.7529468520158
Top 100 precision : 0.53

nash's People

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nash's Issues

Code helping

Great job! Could you please provide the code of model NASH-DN-S ? I am bothered by some details. Very appreciate it!

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