class torch.nn.LPPool2d(norm_type: float, kernel_size: Union[T, Tuple[T, ...]], stride: Optional[Union[T, Tuple[T, ...]]] = None, ceil_mode: bool = False)
Applies a 2D power-average pooling over an input signal composed of several input planes.
On each window, the function computed is:
stride can either be:
int– in which case the same value is used for the height and width dimension
tupleof two ints – in which case, the first
intis used for the height dimension, and the second
intfor the width dimension
If the sum to the power of
p is zero, the gradient of this function is not defined. This implementation will set the gradient to zero in this case.
floorto compute the output shape
Output: , where
>>> # power-2 pool of square window of size=3, stride=2 >>> m = nn.LPPool2d(2, 3, stride=2) >>> # pool of non-square window of power 1.2 >>> m = nn.LPPool2d(1.2, (3, 2), stride=(2, 1)) >>> input = torch.randn(20, 16, 50, 32) >>> output = m(input)
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