ConstantPad3d

class torch.nn.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)