快速上手

用熟悉的 Module、优化器与反向传播接口，完成一次训练循环。

定义、训练、更新

import tensorplay as tp
import tensorplay.nn as nn
import tensorplay.optim as optim

class Net(nn.Module):
    def __init__(self):
        super().__init__()
        self.fc1 = nn.Linear(10, 20)
        self.fc2 = nn.Linear(20, 1)

    def forward(self, x):
        return self.fc2(tp.relu(self.fc1(x)))

model = Net()
criterion = nn.MSELoss()
optimizer = optim.SGD(model.parameters(), lr=0.01)

inputs = tp.randn(32, 10)
target = tp.randn(32, 1)

for epoch in range(100):
    optimizer.zero_grad()
    output = model(inputs)
    loss = criterion(output, target)
    loss.backward()
    optimizer.step()

继续拆解

理解四层架构进入教程查看 NN API