ValueError:optimizer got an empty parameter list基本都跟__init__()及其里面的代码有关,比如下划线打错了、init拼错了、没有super、没在__init__函数内定义网络等。
import torch
import numpy as np
import matplotlib.pyplot as plt
#准备数据集
x_data=torch.Tensor([[1.0],[2.0],[3.0]])
y_data=torch.Tensor([[0],[0],[1]])
# 使用类设计模型
class LogisticRegressionModel(torch.nn.Module):
def _init_(self):
super(LogisticRegressionModel,self).__init__()
self.linear = torch.nn.Linear(1,1)
def forward(self,x):
y_pred=torch.sigmoid(self.linear(x))
return y_pred
model = LogisticRegressionModel()
# 构造损失函数和优化器
criterion = torch.nn.BCELoss(size_average = False)
optimizer = torch.optim.SGD(model.parameters(), lr=0.01)
# 训练周期:前馈,反馈,和更新
for epoch in range(1000):
y_pred = model(x_data)
loss = criterion(y_pred,y_data)
print(epoch, loss.item)
optimizer.zero_grad()
loss.backward()
optimizer.step()
print('w = ', model.linear.weight.item())
print('b = ', model.linear.bias.item())
x_test = torch.Tensor([[4.0]])
y_test = model(x_test)
print('y_pred = ', y_test.data)
# x=np.linspace(0,10,200)
# x_t=torch.Tensor(x).view(200,1)
# y_t=model(x_t)
# y=y_t.data.numpy()
# plt.plot(x,y)
# plt.xlabel('Hours')
# plt.ylabel('Probability of Pass')
# plt.grid()
# plt.show()
实验代码如上,报错如下:
参考博客:https://blog.csdn.net/qazwsxrx/article/details/107936711
解决办法:
这里应该是双下划綫:
OK,成功~
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