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--- |
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title: Ae Gen |
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emoji: 💻 |
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colorFrom: yellow |
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colorTo: pink |
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sdk: gradio |
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sdk_version: 3.16.2 |
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app_file: app.py |
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pinned: false |
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license: mit |
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--- |
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Official release of: |
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- ConvAE model (from [`Digits that are not: Generating new types through deep neural nets`](https://arxiv.org/pdf/1606.04345.pdf)) |
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- DeepConvAE model (from [here](https://tel.archives-ouvertes.fr/tel-01838272/file/75406_CHERTI_2018_diffusion.pdf), Section 10.1 with `L=3`) |
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- Dense K-Sparse model (from [`Out-of-class novelty generation`](https://openreview.net/forum?id=r1QXQkSYg)) |
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These models were trained on MNIST only (digits), but were found to generate new kinds of symbols, see the references for more details. |
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# Install requirements |
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`pip install -r requirements.txt` |
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# Download models |
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```bash |
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git lfs pull |
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``` |
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# Training |
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```bash |
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python cli.py train --dataset=mnist --folder=convae --model=convae |
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``` |
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```bash |
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python cli.py train --dataset=mnist --folder=deep_convae --model=deep_convae |
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``` |
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# Generate samples |
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```bash |
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python cli.py test --model-path=convae.th --nb-generate=100 --folder=convae |
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``` |
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```bash |
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python cli.py test --model-path=deep_convae.th --nb-generate=100 --folder=deep_convae |
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``` |
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```bash |
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python cli.py test --model-path=fc_sparse.th --nb-generate=100 --folder=deep_convae |
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``` |
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