torch (version 0.8.1)

nnf_pad: Pad

Description

Pads tensor.

Usage

nnf_pad(input, pad, mode = "constant", value = 0)

Arguments

input

(Tensor) N-dimensional tensor

pad

(tuple) m-elements tuple, where $\frac{m}{2}\le$ input dimensions and $m$ is even.

mode

'constant', 'reflect', 'replicate' or 'circular'. Default: 'constant'

value

fill value for 'constant' padding. Default: 0.

Padding size

The padding size by which to pad some dimensions of input are described starting from the last dimension and moving forward. $\lfloor \frac{\text{len(pad)}}{2}\rfloor$ dimensions of input will be padded. For example, to pad only the last dimension of the input tensor, then pad has the form $(\text{padding\_left},\text{padding\_right})$; to pad the last 2 dimensions of the input tensor, then use $(\text{padding\_left},\text{padding\_right},$ $\text{padding\_top},\text{padding\_bottom})$; to pad the last 3 dimensions, use $(\text{padding\_left},\text{padding\_right},$ $\text{padding\_top},\text{padding\_bottom}$ $\text{padding\_front},\text{padding\_back})$.

Padding mode

See nn_constant_pad_2d, nn_reflection_pad_2d, and nn_replication_pad_2d for concrete examples on how each of the padding modes works. Constant padding is implemented for arbitrary dimensions. tensor, or the last 2 dimensions of 4D input tensor, or the last dimension of 3D input tensor. Reflect padding is only implemented for padding the last 2 dimensions of 4D input tensor, or the last dimension of 3D input tensor.