python main.py
optional arguments:
-h, --help show this help message and exit
--run RUN Which operation to run. [train|inference]
--nb_epoch NB_EPOCH Number of epochs
--batch_size BATCH_SIZE
Number of samples per batch.
--nb_batch_per_epoch NB_BATCH_PER_EPOCH
Number of batches per epoch
--learning_rate LEARNING_RATE
Learning rate used for AdamOptimizer
--noise_dim NOISE_DIM
Noise dimension for GAN generation
--random_seed RANDOM_SEED
Seed used to initialize rng.
--use_XLA [USE_XLA] Whether to use XLA compiler.
--nouse_XLA
--num_threads NUM_THREADS
Number of threads to fetch the data
--capacity_factor CAPACITY_FACTOR
Nuumber of batches to store in queue
--data_format DATA_FORMAT
Tensorflow image data format.
--celebA_path CELEBA_PATH
Path to celebA images
--channels CHANNELS Number of channels
--central_fraction CENTRAL_FRACTION
Central crop as a fraction of total image
--img_size IMG_SIZE Image size
--model_dir MODEL_DIR
Output folder where checkpoints are dumped.
--log_dir LOG_DIR Logs for tensorboard.
--fig_dir FIG_DIR Where to save figures.
--raw_dir RAW_DIR Where raw data is saved
--data_dir DATA_DIR Where processed data is saved
python main.py --run train --use_XLA
N.B. At this stage, only data_format = NHWC has been tested. It is recommended to use the XLA option to improve runtime speed.
Check validity of both data format and batch norm implementation