TCML Tensorflow Save

Tensorflow implementation of Meta-Learning with Temporal Convolutions

Project README

TCML-tensorflow

A tensorflow implementation of Meta-Learning with Temporal Convolutions

Embedding for Omniglot dataset is only available now.

Prerequisites

  • Python 3.6+
  • Tensorflow 1.3
  • Image dataset for training/validation (Python dictionary-like object)

Usage

python train.py --dataset omniglot --n 5 --k 1 --dilation 1 2 1 2 4 8 16 --lr 5e-4 --batch_size 64

It will print valiation loss and accuracy. Checkpoints and summaries for other metrics are saved in ./runs/tcml_{input_dim}_{num_dense_filter}_{attention_value_dim}_{lr}

Results

Omniglot 5-way, 1-shot 5-way, 5-shot
Accuracy 95.12% 95.01%

Since the paper didn't share exact hyperparameters, it is hard to make same results with the paper. This code performs ~95% accuracy for 5-way environment with way smaller numbers of dilation stacks.

When I tried to use same dilation stack with paper(1 2 1 2 1 2 1 2 1 2 4 8 16), it is too deep, thus the loss converges at 1.60 with poor accuracy.

Still trying to find better hyperparameters to get higher performance.

License

MIT

Author

Donghwa Kim (@storykim)

Open Source Agenda is not affiliated with "TCML Tensorflow" Project. README Source: devsisters/TCML-tensorflow
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