I have run in to problem for finding an easy to implement AutoEncoder(AE) code for CIFAR10 dataset.
After dozen of days to search a proper and easy to understading that how a simple autoencoder model should be implemented, I eventually decide to write it by myself. Every body knows that putting machine learning technique to learn can takes long time to finish. So I put my model, and optimizer's learned parameter to this repository too.
I hope this code can be useful for everybody.
This code is written by Python program and need the following packages to be able to execute:
Use the package manager pip to install the following packages.
- pytorch
- pytorch-lightning
- torchvision
- matplotlib
- argparse it is better to create an environment using 'venv' or 'conda' command.
[AE project current address]@ python main_AE --help
optional arguments:
-h, --help show this help message and exit
- dataset DATASET
- epochs EPOCHS
- batch_size BATCH_SIZE
- lr LR
- weight-decay WEIGHT_DECAY
- load_model
- save_model
For instance, if you want to load pretrained model you need to use --load_model keyword after calling the file
[AE project current address]@ python main_AE --load_model
one example of run load model:
Another model load output:
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.