class

ML::NN::Linear

Linear layer: out_features = in_features @ weight^T + bias

Constructors

new(in_features : Int32, out_features : Int32, bias : Bool = true, device : Tensor::Device = Tensor.default_device)

bias

call(x : Autograd::Variable) : Autograd::Variable

forward(x : Autograd::Variable) : Autograd::Variable

Forward pass: y = x @ W^T + b x: [..., in_features] - arbitrary batch dimensions output: [..., out_features]

in_features

out_features

parameters

Get all trainable parameters

weight