message: training: randomly zero the color only if there are auxiliary features
diff: @@ -201,7 +201,6 @@ class PreprocessedDataset(Dataset):
  self.features = cfg.features
  self.data_channels = get_channels(data_cfg.features)
  self.channels = get_channels(cfg.features)
  - self.num_channels = len(self.channels)
  self.channel_order = get_channel_indices(self.channels, self.data_channels)
  # Get the image samples
  @@ -293,9 +292,9 @@ class TrainingDataset(PreprocessedDataset):
  input_image = np.pad(input_image, pad_size, mode='constant')
  target_image = np.pad(target_image, pad_size, mode='constant')
  - # Randomly zero the color channels
  + # Randomly zero the color channels if there are auxiliary features
  # This prevents "ghosting" artifacts when the color buffer is entirely black
  - if np.random.rand() < 0.02:
  + if len(self.channels) > 3 and np.random.rand() < 0.02:
  input_image[:, :, 0:3] = 0
  target_image[:] = 0
  