#Setting parameters
                          # (note that we have mapped "0" to label 10)

# Traning Parameters
hyper_para = {}
hyper_para['batch_size'] = 2
hyper_para['epochs'] = 170

hyper_para['learning_rate'] = 0.01        #Learning rate for w

hyper_para['decay'] = 0.0005      #weight decay
hyper_para['random_seed'] = 0
hyper_para['k'] = 20     #Gibbs sampling steps

#Unroll parameters and randomly initialize them
hyper_para['w_init_mu'] = 0
hyper_para['w_init_sig'] = 0.1 # mean and standard deviation

#
hyper_para['no_of_h_layer'] = 1

hyper_para['input_layer_size']  = 784  # 28x28 Input Images of Digits
input_layer_size = hyper_para['input_layer_size']

hyper_para['hidden_layer_1_size'] = 100   # 100 hidden units
hidden_layer_1_size = hyper_para['hidden_layer_1_size']

hyper_para['hidden_layer_2_size'] = 100   # 100 hidden units
hyper_para['num_labels'] = 10          # 10 labels, from 1 to 10
