minerva.models.nets.mlp

Classes

MLP	A multilayer perceptron (MLP) implemented as a subclass of nn.Sequential.

Module Contents

class minerva.models.nets.mlp.MLP(layer_sizes, activation_cls=nn.ReLU, *args, **kwargs)

Bases: torch.nn.Sequential

A multilayer perceptron (MLP) implemented as a subclass of nn.Sequential.

This MLP is composed of a sequence of linear layers interleaved with ReLU activation functions, except for the final layer which remains purely linear.

Example

>>> mlp = MLP(10, 20, 30, 40)
>>> print(mlp)
MLP(
    (0): Linear(in_features=10, out_features=20, bias=True)
    (1): ReLU()
    (2): Linear(in_features=20, out_features=30, bias=True)
    (3): ReLU()
    (4): Linear(in_features=30, out_features=40, bias=True)
)

Initializes the MLP with specified layer sizes.

Parameters

layer_sizesSequence[int]

A sequence of positive integers indicating the size of each layer. At least two integers are required, representing the input and output layers.

activation_clstype

The class of the activation function to use between layers. Default is nn.ReLU.

*args

Additional arguments passed to the activation function.

**kwargs

Additional keyword arguments passed to the activation function.

Raises

AssertionError

If fewer than two layer sizes are provided or if any layer size is not a positive integer.

AssertionError

If activation_cls does not inherit from torch.nn.Module.

Parameters:

• layer_sizes (Sequence[int])

• activation_cls (type)