在Pytorch中保存性能最佳的模型(但不考虑验证访问权限)

import torch
import torch.nn as nn
import torch.optim as optim

# 定义模型
class MyModel(nn.Module):
    def __init__(self):
        super(MyModel, self).__init__()
        self.fc = nn.Linear(10, 1)

    def forward(self, x):
        return self.fc(x)

# 创建模型实例
model = MyModel()

# 定义损失函数和优化器
criterion = nn.MSELoss()
optimizer = optim.SGD(model.parameters(), lr=0.01)

# 训练模型
for epoch in range(10):
    # 前向传播
    outputs = model(inputs)
    loss = criterion(outputs, labels)

    # 反向传播和优化
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()

# 保存性能最佳的模型参数
best_model_path = 'best_model.pth'
torch.save(model.state_dict(), best_model_path)

# 加载模型参数
loaded_model = MyModel()
loaded_model.load_state_dict(torch.load(best_model_path))