self.gb1_sum_squere += self.gb1 ** 2
self.gW1_sum_squere += self.gW1 ** 2
def param_update(self):
'''
パラメータの更新
'''
self.W2 -= self.eta / (np.sqrt(self.gW2_sum_squere + 1)) * self.gW2_sum / self.batch_size
self.b2 -= self.eta / (np.sqrt(self.gb2_sum_squere + 1)) * self.gb2_sum / self.batch_size
self.W1 -= self.eta / (np.sqrt(self.gW1_sum_squere + 1)) * self.gW1_sum / self.batch_size
self.b1 -= self.eta / (np.sqrt(self.gb1_sum_squere + 1)) * self.gb1_sum / self.batch_size
def init_grad_sum(self):
self.gb2_sum = np.zeros(self.data['D'])
self.gW2_sum = np.zeros((self.data['D'], self.hidden_dim_num))
self.gb1_sum = np.zeros(self.hidden_dim_num)
self.gW1_sum = np.zeros((self.hidden_dim_num, self.data['D']))
self.gb2_sum_squere = np.zeros(self.data['D'])
self.gW2_sum_squere = np.zeros((self.data['D'], self.hidden_dim_num))
self.gb1_sum_squere = np.zeros(self.hidden_dim_num)
self.gW1_sum_squere = np.zeros((self.hidden_dim_num, self.data['D']))
def sigmoid(x):
return 1.0 / (1.0 + np.exp(-x))
if __name__ == '__main__':
ae = AutoEncoderAll('./data/dataset.dat')
ae.calc_loss_and_params()
data.print_params2file(ae.get_best_params(), './results/result_test.txt')
パラメータの更新
'''
self.W2 -= self.eta / (np.sqrt(self.gW2_sum_squere +
1)) * self.gW2_sum / self.batch_size
self.b2 -= self.eta / (np.sqrt(self.gb2_sum_squere +
1)) * self.gb2_sum / self.batch_size
self.W1 -= self.eta / (np.sqrt(self.gW1_sum_squere +
1)) * self.gW1_sum / self.batch_size
self.b1 -= self.eta / (np.sqrt(self.gb1_sum_squere +
1)) * self.gb1_sum / self.batch_size
def init_grad_sum(self):
self.gb2_sum = np.zeros(self.data['D'])
self.gW2_sum = np.zeros((self.data['D'], self.hidden_dim_num))
self.gb1_sum = np.zeros(self.hidden_dim_num)
self.gW1_sum = np.zeros((self.hidden_dim_num, self.data['D']))
self.gb2_sum_squere = np.zeros(self.data['D'])
self.gW2_sum_squere = np.zeros((self.data['D'], self.hidden_dim_num))
self.gb1_sum_squere = np.zeros(self.hidden_dim_num)
self.gW1_sum_squere = np.zeros((self.hidden_dim_num, self.data['D']))
def sigmoid(x):
return 1.0 / (1.0 + np.exp(-x))
if __name__ == '__main__':
ae = AutoEncoderAll('./data/dataset.dat')
ae.calc_loss_and_params()
data.print_params2file(ae.get_best_params(), './results/result_test.txt')