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ZeroPad3d#

class torch.nn.ZeroPad3d(padding)[source]#

用零填充输入张量边界。

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

参数

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

形状
  • 输入: (N,C,Din,Hin,Win)(N, C, D_{in}, H_{in}, W_{in})(C,Din,Hin,Win)(C, D_{in}, H_{in}, W_{in})

  • 输出: (N,C,Dout,Hout,Wout)(N, C, D_{out}, H_{out}, W_{out})(C,Dout,Hout,Wout)(C, D_{out}, H_{out}, W_{out}),其中

    Dout=Din+padding_front+padding_backD_{out} = D_{in} + \text{padding\_front} + \text{padding\_back}

    Hout=Hin+padding_top+padding_bottomH_{out} = H_{in} + \text{padding\_top} + \text{padding\_bottom}

    Wout=Win+padding_left+padding_rightW_{out} = W_{in} + \text{padding\_left} + \text{padding\_right}

示例

>>> m = nn.ZeroPad3d(3)
>>> input = torch.randn(16, 3, 10, 20, 30)
>>> output = m(input)
>>> # using different paddings for different sides
>>> m = nn.ZeroPad3d((3, 3, 6, 6, 0, 1))
>>> output = m(input)