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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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-
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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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+
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+ There is already prepared notebook on Google Colab to try it. TODO GOOGLE COLAB
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+
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+ ## Customization
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+
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+
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+ ## Notes
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+
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+ ## References
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+
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+ TODO
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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
Original file line number Diff line number Diff line change @@ -3,4 +3,5 @@ hydra-core
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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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