old_contents: # -*- coding: utf-8 -*-
  
  import numpy as np
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/'
  # IMAGE_PATH = './data/original_images/'
  IMAGE_SHAPE = (256, 256, 3)
  BATCH_SIZE = 128
  MAX_STEPS = 500
  ALPHA = 1e-3
  BETA = 1e-2
  
  TAGS = np.array(
         ['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]
  
new_contents: # -*- coding: utf-8 -*-
  
  import numpy as np
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/'
  # IMAGE_PATH = './data/original_images/'
  IMAGE_SHAPE = (64, 64, 3)
  BATCH_SIZE = 64
  MAX_STEPS = 500
  ALPHA = 1e-3
  BETA = 1e-2
  
  TAGS = np.array(
         ['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]
  
subject: update settings