## Usage

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

## Arguments

input

(Tensor) N-dimensional tensor

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

mode

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

value

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

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