text: # Basic training configuration file
  from pathlib import Path
  from torchvision.transforms import RandomVerticalFlip, RandomHorizontalFlip
  from torchvision.transforms import RandomResizedCrop
  from torchvision.transforms import ToTensor, Normalize
  from common.dataset import get_test_data_loader
  
  
  SEED = 12345
  DEBUG = True
  
  OUTPUT_PATH = "output"
  dataset_path = Path("/home/fast_storage/imaterialist-challenge-furniture-2018/")
  
  SAVE_PROBAS = True
  # SAMPLE_SUBMISSION_PATH = dataset_path / "sample_submission_randomlabel.csv"
  
  
  TEST_TRANSFORMS = [
      RandomResizedCrop(350, scale=(0.7, 1.0), interpolation=3),
      RandomVerticalFlip(p=0.5),
      RandomHorizontalFlip(p=0.5),
      ToTensor(),
      Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
  ]
  
  N_CLASSES = 128
  BATCH_SIZE = 24
  NUM_WORKERS = 15
  
  TEST_LOADER = get_test_data_loader(
      dataset_path=dataset_path / "test",
      test_data_transform=TEST_TRANSFORMS,
      batch_size=BATCH_SIZE,
      num_workers=NUM_WORKERS,
      cuda=True)
  
  
  MODEL = (Path(OUTPUT_PATH) / "training_FurnitureInceptionV4_350_20180427_1512" /
           "model_FurnitureInceptionV4_350_13_val_loss=0.5497886.pth").as_posix()
  
  N_TTA = 12
  