nnf_pad function

Pad

Pads tensor.

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

Arguments

• input: (Tensor) N-dimensional tensor
• pad: (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.

#ding size

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 $(\mbox{padding\_left}, \mbox{padding\_right},$

$\mbox{padding\_top}, \mbox{padding\_bottom}$

$\mbox{padding\_front}, \mbox{padding\_back})$.

#ding 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.