text: # ============ TRAIN CONFIG ==============
  # Dataset options
  DATASET = 'datasets/eccv16_dataset_summe_google_pool5.h5' # path to h5 dataset (required)
  SPLIT = 'datasets/summe_splits.json' # path to split file (required)
  SPLIT_ID = 0 # split index (default: 0)
  METRIC = 'summe' # evaluation metric ['tvsum', 'summe'])
  
  # Model options
  INPUT_DIM = 1024 # input dimension (default: 1024)
  HIDDEN_DIM = 256 # hidden unit dimension of DSN (default: 256)
  NUM_LAYERS = 1 # number of RNN layers (default: 1)
  RNN_CELL = 'lstm' # RNN cell type (default: lstm)
  
  # Optimization options
  LR = 1e-05 # learning rate (default: 1e-05)
  WEIGHT_DECAY = 1e-05 # weight decay rate (default: 1e-05)
  MAX_EPOCH = 60 # maximum epoch for training (default: 60)
  STEP_SIZE = 30 # how many steps to decay learning rate (default: 30)
  GAMMA = 0.1 # learning rate decay (default: 0.1)
  NUM_EPISODE = 5 # number of episodes (default: 5)
  BETA = 0.01 # weight for summary length penalty term (default: 0.01)
  
  # Misc
  SEED = 1 # random seed (default: 1)
  GPU = '0' # which gpu devices to use (default: 0)
  USE_CPU = False # use cpu device
  EVALUATE = False # whether to do evaluation only
  TEST = False # whether to do evaluation only
  RESUME = '' # path to resume file
  VERBOSE = True # whether to show detailed test results
  SAVE_DIR = 'log/summe-split0' # path to save output (default: log/)
  SAVE_RESULTS = True # whether to save output results