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PyTorch implementation of "Auto-Encoding Variational Bayes", arxiv:1312.6114

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VAE PyTorch Implementation

PyTorch implementation of Auto-Encoding Variational Bayes, arxiv:1312.6114

vae-graphical-model

Installation

$ git clone https://github.com/kuc2477/pytorch-vae && cd pytorch-vae
$ pip install -r requirements.txt

CLI

Implementation CLI is provided by main.py

Usage

$ ./main.py --help
$ usage: VAE PyTorch implementation [-h] [--dataset {mnist,cifar10,cifar100}]
                                  [--kernel-num KERNEL_NUM] [--z-size Z_SIZE]
                                  [--epochs EPOCHS] [--batch-size BATCH_SIZE]
                                  [--sample-size SAMPLE_SIZE] [--lr LR]
                                  [--weight-decay WEIGHT_DECAY]
                                  [--loss-log-interval LOSS_LOG_INTERVAL]
                                  [--image-log-interval IMAGE_LOG_INTERVAL]
                                  [--resume] [--checkpoint-dir CHECKPOINT_DIR]
                                  [--sample-dir SAMPLE_DIR] [--no-gpus]
                                  (--test | --train)

optional arguments:
  -h, --help            show this help message and exit
  --dataset {mnist,cifar10,cifar100}
  --kernel-num KERNEL_NUM
  --z-size Z_SIZE
  --epochs EPOCHS
  --batch-size BATCH_SIZE
  --sample-size SAMPLE_SIZE
  --lr LR
  --weight-decay WEIGHT_DECAY
  --loss-log-interval LOSS_LOG_INTERVAL
  --image-log-interval IMAGE_LOG_INTERVAL
  --resume
  --checkpoint-dir CHECKPOINT_DIR
  --sample-dir SAMPLE_DIR
  --no-gpus
  --test
  --train

Train

./main.py --train

Test

./main.py --test

Reference

Author

Ha Junsoo / @kuc2477 / MIT License

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PyTorch implementation of "Auto-Encoding Variational Bayes", arxiv:1312.6114

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