old_contents: # -*- coding: utf-8 -*-
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/'
  OUTPUT_PATH = './output/'
  DEFAULT_BUCKET = 'rainforest-satellite-images'
  EXT = ('.png', '.csv')
  IMAGE_SHAPE = (128, 128, 4)
  BATCH_SIZE = 128
  N_THREADS = 1
  # roughly 10 epochs of training data
  MAX_STEPS = 5000
  EPOCHS = 5
  
  ALPHA = 5e-4
  BETA = 1e-2
  VALID_SIZE = .20
  KEEP_RATE = .8
  
  # Ioffe and Szegedy 2015 suggests 5x learning rate with batch normalization
  ALPHA *= 5
  
  # with data augmentation turned on, need long training steps
  AUGMENT = True
  if AUGMENT:
      MAX_STEPS *= 2
  
  TAGS = ['agriculture', 'artisinal_mine', 'bare_ground', 'blooming',
          'blow_down', 'clear', 'cloudy', 'conventional_mine', 'cultivation',
          'habitation', 'haze', 'partly_cloudy', 'primary', 'road',
          'selective_logging', 'slash_burn', 'water']
  
  TAGS_WEIGHTINGS = [0.8941, 0.9971, 0.9926, 0.9971, 0.9991, 0.7579, 0.98,
                     0.9991, 0.961, 0.9686, 0.9769, 0.9378, 0.6751, 0.9307,
                     0.9971, 0.9982, 0.9377]
  
  # TAGS_THRESHOLDS = [0.3, 0.2, 0.2, 0.2, 0.1, 0.4, 0.2,
  #                    0.1, 0.2, 0.2, 0.2, 0.2, 0.5, 0.2,
  #                    0.2, 0.1, 0.2]
  
  TAGS_THRESHOLDS = [0.245, 0.1375, 0.2225, 0.19, 0.0475, 0.2375, 0.12,
                     0.0875, 0.265, 0.2175, 0.1925, 0.1625, 0.2625, 0.21,
                     0.14, 0.085, 0.205]
  
new_contents: # -*- coding: utf-8 -*-
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/'
  OUTPUT_PATH = './output/'
  DEFAULT_BUCKET = 'rainforest-satellite-images'
  EXT = ('.jpg', '.csv')
  IMAGE_SHAPE = (128, 128, 3)
  BATCH_SIZE = 128
  N_THREADS = 1
  # roughly 10 epochs of training data
  MAX_STEPS = 5000
  EPOCHS = 5
  
  ALPHA = 5e-4
  BETA = 1e-2
  VALID_SIZE = .20
  KEEP_RATE = .8
  
  # Ioffe and Szegedy 2015 suggests 5x learning rate with batch normalization
  ALPHA *= 5
  
  # with data augmentation turned on, need long training steps
  AUGMENT = False
  if AUGMENT:
      MAX_STEPS *= 2
  
  TAGS = ['agriculture', 'artisinal_mine', 'bare_ground', 'blooming',
          'blow_down', 'clear', 'cloudy', 'conventional_mine', 'cultivation',
          'habitation', 'haze', 'partly_cloudy', 'primary', 'road',
          'selective_logging', 'slash_burn', 'water']
  
  TAGS_WEIGHTINGS = [0.8941, 0.9971, 0.9926, 0.9971, 0.9991, 0.7579, 0.98,
                     0.9991, 0.961, 0.9686, 0.9769, 0.9378, 0.6751, 0.9307,
                     0.9971, 0.9982, 0.9377]
  
  # TAGS_THRESHOLDS = [0.3, 0.2, 0.2, 0.2, 0.1, 0.4, 0.2,
  #                    0.1, 0.2, 0.2, 0.2, 0.2, 0.5, 0.2,
  #                    0.2, 0.1, 0.2]
  
  TAGS_THRESHOLDS = [0.245, 0.1375, 0.2225, 0.19, 0.0475, 0.2375, 0.12,
                     0.0875, 0.265, 0.2175, 0.1925, 0.1625, 0.2625, 0.21,
                     0.14, 0.085, 0.205]
  
subject: use jpeg instead