Binarygan
Code for "Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation"
Install / Use
/learn @salu133445/BinaryganREADME
BinaryGAN
Prepare Training Data
-
Download MNIST database by running the script:
./training_data/download_mnist.sh -
or download it manually:
- Download MNIST database here
- Decompress all the
.gzfiles - Move the decompressed files to
./training_data/mnist
-
Store the data to shared memory (optional)
Make sure the SharedArray package has been installed.
python ./training_data/load_mnist_to_sa.py ./training_data/mnist/ \ --merge --binary
Configuration
Modify config.py for configuration.
-
Quick setup
Change the values in the dictionary
SETUPfor a quick setup. Documentation is provided right after each key. -
More configuration options
Four dictionaries
EXP_CONFIG,DATA_CONFIG,MODEL_CONFIGandTRAIN_CONFIGdefine experiment-, data-, model- and training-related configuration variables, respectively.The automatically-determined experiment name is based only on the values defined in the dictionary
SETUP, so remember to provide the experiment name manually when you modify any other configuration variables so that you won't overwrite a trained model.
Train the model
python train.py
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