TensorPlay AI

Quickstart

Use familiar Module, optimizer, and backward APIs to complete a training loop.

Define, train, update

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()

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