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https://github.com/seujung/SNAIL-gluon
Implementation of SNAIL(A Simple Neural Attentive Meta-Learner) with Gluon
https://github.com/seujung/SNAIL-gluon
gluon metalearning mxnet
Last synced: about 2 months ago
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Implementation of SNAIL(A Simple Neural Attentive Meta-Learner) with Gluon
- Host: GitHub
- URL: https://github.com/seujung/SNAIL-gluon
- Owner: seujung
- Created: 2018-07-11T23:36:06.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-02-22T13:40:12.000Z (almost 6 years ago)
- Last Synced: 2024-07-31T23:44:54.495Z (4 months ago)
- Topics: gluon, metalearning, mxnet
- Language: Python
- Size: 16.5 MB
- Stars: 11
- Watchers: 3
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-few-shot-meta-learning - code (MXNet? Gluon)
- Awesome-MXNet - SNAIL
README
# SNAIL with Gluon
---
Gluon inplementation of [A Simple Neural Attentive Meta-Learniner](https://openreview.net/pdf?id=B1DmUzWAW)
##### network structore
![net_structure](assets/net_structure.png)##### building block structure
![block_structure](assets/blocks.png)## Requirements
- Python 3.6.1
- mxnet 1.3.1
- mxboard 0.1.0
- tqdm 4.29.0## Application
- Omniglot## Usage
- arguments
- batch_size : Define batch size (defualt=64)
- epochs : Define total epoches (default=50)
- N : the nunber of N-way (default=10)
- K : the number of K-shot (default=5)
- iterations : the number of data iteration (default=1000)
- input_dims : embedding dimension of input data (default=64)
- download : download omniglot dataset (default=False)
- GPU_COUNT : use gpu count (default=1)
- logdir : location of mxboard log file (default=./log)
- modeldir : location of model parameter file (default=./models)###### default setting
```
python main.py
```
or###### manual setting
```
python main.py --batch_size=24 --epochs=200 ..
```## Results
##### 10-way 5-shot case
![perf_acc](assets/perf_acc.png)## Reference
- https://github.com/sagelywizard/snail
- https://github.com/eambutu/snail-pytorch