text: from pathlib import Path
  
  
  # API_TOKEN = " <YOUR TOKEN> "
  # ADMIN_ID = <YOUR TELEGRAM ID>
  
  MAX_IMAGE_SIZE = 1280  # Stylized image size
  EVAL_ITER = 500000  # State iteration for eval
  
  BASE_DIR = Path(__file__).parent.parent
  
  STATE_DICTS_DIR = BASE_DIR / 'app/net/state_dicts'
  
  IMAGES_DIR = Path('static/images')
  CONTENT_PRESETS_DIR = IMAGES_DIR / 'content_presets'
  STYLE_PRESETS_DIR = IMAGES_DIR / 'style_presets'
  
  CONTENTS_PRESETS_PATHS = [path.as_posix() for path in CONTENT_PRESETS_DIR.glob('*.jpg')]
  STYLES_PRESETS_PATHS = [path.as_posix() for path in STYLE_PRESETS_DIR.glob('*.jpg')]
  
  
  # Train-specific parameters
  START_ITER = 500000  # At this iteration neural network will start learn
  MAX_ITER = 1000000  # To what iteration the neural network will learn
  SAVE_ITER = 5000  # At which iteration the states will saved
  BATCH_SIZE = 5
  NUM_WORKERS = 4
  TRAIN_RESIZE = 512  # Train images resizing value (for dataloader). Change only if you train from scratch!
  TRAIN_CONTENT_DIR = Path('app/net/train_images/content')
  TRAIN_STYLE_DIR = Path('app/net/train_images/style')
  