message: training: default max learning rate depends on batch size, increased default batch size
diff: @@ -50,7 +50,7 @@ def parse_args(cmd=None, description=None):
  parser.add_argument('--valid_epochs', type=int, default=10, help='perform validation every this many epochs')
  parser.add_argument('--save_epochs', type=int, default=10, help='save checkpoints every this many epochs')
  parser.add_argument('--lr', '--learning_rate', type=float, help='initial learning rate')
  - parser.add_argument('--max_lr', '--max_learning_rate', type=float, default=2e-4, help='maximum learning rate')
  + parser.add_argument('--max_lr', '--max_learning_rate', type=float, help='maximum learning rate')
  parser.add_argument('--lr_warmup', type=float, default=0.15, help='the percentage of the cycle spent increasing the learning rate (warm-up)')
  if cmd in {'find_lr'}:
  @@ -58,7 +58,7 @@ def parse_args(cmd=None, description=None):
  parser.add_argument('--max_lr', '--max_learning_rate', type=float, default=0.1, help='maximum learning rate')
  if cmd in {'train', 'find_lr'}:
  - parser.add_argument('--batch_size', '--bs', '-b', type=int, default=8, help='mini-batch size (total batch size of all devices)')
  + parser.add_argument('--batch_size', '--bs', '-b', type=int, default=16, help='mini-batch size (total batch size of all devices)')
  parser.add_argument('--loaders', '-j', type=int, default=4, help='number of data loader threads per device')
  advanced.add_argument('--model', '-m', type=str, choices=['unet'], default='unet', help='network model')
  advanced.add_argument('--loss', '-l', type=str, choices=['l1', 'mape', 'smape', 'l2', 'ssim', 'msssim', 'l1_msssim', 'l1_grad'], default='l1_msssim', help='loss function')
  @@ -134,6 +134,11 @@ def parse_args(cmd=None, description=None):
  if not cfg.result:
  cfg.result = '%x' % int(time.time())
  + if cmd in {'train'}:
  + # Set the default maximum learning rate
  + if cfg.max_lr is None:
  + cfg.max_lr = 3.125e-6 * cfg.batch_size
  +
  # Print PyTorch version
  print('PyTorch:', torch.__version__)
  