Models

Commonly, sampled features are fed into an MLP-like model. TorchSample provides classes for common models that are used with coordinate sampling.

MLP

MLP is a multilayer-perceptron that can handle arbitrary dimension input. The last input dimension is features, and the returned prediction will have the same shape as the input, except for the feature dimension.

# A simple network that takes in (x, y) coordinates and predicts RGB.
model = ts.models.MLP(2, 256, 256, 256, 3)

By default, MLP uses relu activation, and applies activation between all layers except the output layer.

The activation function can be specified. For example, if we want to use a sine activation function (see SIREN), we could:

model = ts.models.MLP(2, 256, 256, 256, 3, activation=torch.sin)