LPPool1d(norm_type: float, kernel_size: Union[T, Tuple[T, ...]], stride: Optional[Union[T, Tuple[T, ...]]] = None, ceil_mode: bool = False)¶
Applies a 1D power-average pooling over an input signal composed of several input planes.
On each window, the function computed is:
At p = , one gets Max Pooling
At p = 1, one gets Sum Pooling (which is proportional to Average Pooling)
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.
kernel_size – a single int, the size of the window
stride – a single int, the stride of the window. Default value is
ceil_mode – when True, will use ceil instead of floor to compute the output shape
Output: , where
>>> # power-2 pool of window of length 3, with stride 2. >>> m = nn.LPPool1d(2, 3, stride=2) >>> input = torch.randn(20, 16, 50) >>> output = m(input)