Quickstart
==========

Here is a simple example of how to use TensorPlay to define a neural network and train it.

.. code-block:: python

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

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

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

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

    # Dummy data
    input = tp.randn(32, 10)
    target = tp.randn(32, 1)

    # Training loop
    for epoch in range(100):
        optimizer.zero_grad()
        output = model(input)
        loss = criterion(output, target)
        loss.backward()
        optimizer.step()
        
        if epoch % 10 == 0:
            print(f"Epoch {epoch}, Loss: {loss.item()}")