cfg.PRINT_EVERY = conf['print_every']
"""
Training settings
"""
cfg.NUM_EPOCHS = conf['num_epochs']
cfg.BATCH_SIZE = conf['batch_size']
cfg.DEVICE = torch.device('cuda:1' if torch.cuda.is_available() else 'cpu')
cfg.PATIENCE = conf['patience']
cfg.RESUME = conf['resume']
cfg.NUM_WORKERS = conf['num_workers']
cfg.LEARNING_RATE = conf['learning_rate']
cfg.WEIGHT_DECAY = conf['weight_decay']
"""
Model saving
"""
cfg.CHECKPOINT_DIR = os.path.join(cfg.ROOT_DIR, 'checkpoint')
cfg.BEST_MODEL_PATH = os.path.join(cfg.CHECKPOINT_DIR, 'best_model.pth')
cfg.BEST_ACC_PATH = os.path.join(cfg.CHECKPOINT_DIR, 'best_acc.txt')
cfg.CHECKPOINT_PATH = os.path.join(cfg.CHECKPOINT_DIR, cfg.RUN_NAME + '.tar')
"""
Clear history
"""
if cfg.CLEAR_HISTORY:
if os.path.exists(cfg.LOG_DIR):
for f in os.listdir(cfg.LOG_DIR):
os.remove(os.path.join(cfg.LOG_DIR, f))
if os.path.exists(cfg.CHECKPOINT_PATH):
os.remove(cfg.CHECKPOINT_PATH)
