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README.md

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<a href="https://black.readthedocs.io/en/stable/"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
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</p>
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This repository is the reimplementation of MAML(TODO) algorithm. The default
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settings are used for training on Omniglot (5-way 5-shot) problem but It can be
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easily extended for other few-shot datasets thanks to Torchmeta library.
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## Quickstart
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## Quickrun
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**On Local Machine**
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```bash
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git clone https://github.com/rcmalli/lightning-maml.git
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cd ./lightning-maml/src && python3 run.py train.pl_trainer.gpus=1
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```
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**On Google Colab**
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There is already prepared notebook on Google Colab to try it. TODO GOOGLE COLAB
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## Customization
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## Notes
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## References
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TODO

conf/model/default.yaml

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torch_module:
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_target_: common.models.OmniConv
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_target_: common.models.omniconv.OmniConv
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num_layers : 4
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kernel_size: 3
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num_filters: 64

requirements.txt

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wandb
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dvc
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python-dotenv
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# hydra-joblib-launcher
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higher
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torchmeta

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