- class torch.nn.LPPool1d(norm_type, kernel_size, stride=None, ceil_mode=False)[source]¶
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.
Input: or .
Output: or , 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)