# torch.nn.functional.linear¶

torch.nn.functional.linear(input, weight, bias=None)

Applies a linear transformation to the incoming data: $y = xA^T + b$.

This operation supports 2-D weight with sparse layout

Warning

Sparse support is a beta feature and some layout(s)/dtype/device combinations may not be supported, or may not have autograd support. If you notice missing functionality please open a feature request.

This operator supports TensorFloat32.

Shape:

• Input: $(*, in\_features)$ where * means any number of additional dimensions, including none

• Weight: $(out\_features, in\_features)$ or $(in\_features)$

• Bias: $(out\_features)$ or $()$

• Output: $(*, out\_features)$ or $(*)$, based on the shape of the weight