old_contents: # encoding: utf-8
  
  """
  @author: ouwj
  @position: ouwj-win10
  @file: params_config.py
  @time: 2017/4/25 14:12
  """
  
  def get_config(dataset):
      if dataset == 'MNIST':
          return MNIST_Config()
      elif dataset == 'CIFAR':
          return CIFAR_Config()
      else:
          return None
  
  class MNIST_Config:
      # parameters of model
      learning_rate = 0.1
      momentum = 0.5
      batch_size = 64
      n_epoch = 10001
      n_train_discriminator = 2
      n_train_generator = 1
  
      # parameters of input & output
      image_size = 28*28
      input_size = 10*10
  
      # hidden parameters of generator
      g_n_hidden1 = 1200
      g_n_hidden2 = 1200
  
      # hidden parameters of discriminator
      d_n_hidden1 = 240
      d_n_hidden2 = 240
  
  
  class CIFAR_Config:
      # parameters of model
      learning_rate = 0.025
      momentum = 0.5
      batch_size = 100
      n_epoch = 40001
      n_train_discriminator = 2
      n_train_generator = 1
  
      # parameters of input & output
      image_size = 32*32*3
      input_size = 10*10
  
      # hidden parameters of generator
      g_n_hidden1 = 8000
      g_n_hidden2 = 8000
  
      # hidden parameters of discriminator
      d_n_hidden1 = 1600
      d_n_hidden2 = 1600
  
new_contents: # encoding: utf-8
  
  """
  @author: ouwj
  @position: ouwj-win10
  @file: params_config.py
  @time: 2017/4/25 14:12
  """
  
  def get_config(dataset):
      if dataset == 'MNIST':
          return MNIST_Config()
      elif dataset == 'CIFAR':
          return CIFAR_Config()
      else:
          return None
  
  class MNIST_Config:
      # parameters of model
      learning_rate = 0.025
      momentum = 0.5
      batch_size = 64
      n_epoch = 10001
      n_train_discriminator = 1
      n_train_generator = 1
  
      # parameters of input & output
      image_size = 28*28
      input_size = 10*10
  
      # hidden parameters of generator
      g_n_hidden1 = 1200
      g_n_hidden2 = 1200
  
      # hidden parameters of discriminator
      d_n_hidden1 = 240
      d_n_hidden2 = 240
  
  
  class CIFAR_Config:
      # parameters of model
      learning_rate = 0.025
      momentum = 0.5
      batch_size = 100
      n_epoch = 40001
      n_train_discriminator = 2
      n_train_generator = 1
  
      # parameters of input & output
      image_size = 32*32*3
      input_size = 10*10
  
      # hidden parameters of generator
      g_n_hidden1 = 8000
      g_n_hidden2 = 8000
  
      # hidden parameters of discriminator
      d_n_hidden1 = 1600
      d_n_hidden2 = 1600
  
subject: update model