def model2(self):
input_dim = 4
output_dim = 1
model = Model2.LinearRegressionModel(input_dim, output_dim)
criterion = nn.MSELoss() # 损失函数为均方差
learning_rate = 0.01
self.optimizer21 = torch.optim.SGD(model.parameters(),
lr=learning_rate)
'''训练网络'''
for epoch in range(self.epochs21):
epoch += 1
# 清空梯度参数
self.optimizer21.zero_grad()
# 获得输出
outputs = model(self.x)
# 计算损失
loss = criterion(outputs, self.y)
# 反向传播
loss.backward()
# 更新参数
self.optimizer21.step()
return model
def __init__(self):
self.train_number = 200
self.model11 = Model1.NonLinearRegression()
self.model21 = Model2.LinearRegressionModel(4, 1)
learning_rate = 0.01
self.optimizer11 = torch.optim.SGD(self.model11.parameters(),
lr=learning_rate)
self.optimizer21 = torch.optim.SGD(self.model21.parameters(),
lr=learning_rate)
self.max = 0
self.min = 0
