ConstantPad3d

class torch.nn.modules.padding.ConstantPad3d(padding, value)

Pads the input tensor boundaries with a constant value.

For N-dimensional padding, use torch.nn.functional.pad().

Parameters

padding (int, tuple) – the size of the padding. If is int, uses the same padding in all boundaries. If a 6-tuple, uses ($\text{padding\_left}$, $\text{padding\_right}$, $\text{padding\_top}$, $\text{padding\_bottom}$, $\text{padding\_front}$, $\text{padding\_back}$)

Shape:

• Input: $(N,C,D_{in},H_{in},W_{in})$ or $(C,D_{in},H_{in},W_{in})$.

• Output: $(N,C,D_{out},H_{out},W_{out})$ or $(C,D_{out},H_{out},W_{out})$, where

  $D_{out}=D_{in}+\text{padding\_front}+\text{padding\_back}$

  $H_{out}=H_{in}+\text{padding\_top}+\text{padding\_bottom}$

  $W_{out}=W_{in}+\text{padding\_left}+\text{padding\_right}$

Examples:

>>> m = nn.ConstantPad3d(3, 3.5)
>>> input = torch.randn(16, 3, 10, 20, 30)
>>> output = m(input)
>>> # using different paddings for different sides
>>> m = nn.ConstantPad3d((3, 3, 6, 6, 0, 1), 3.5)
>>> output = m(input)