nn_lp_pool1d function

Applies a 1D power-average pooling over an input signal composed of several input planes.

On each window, the function computed is:

nn_lp_pool1d(norm_type, kernel_size, stride = NULL, ceil_mode = FALSE)

Arguments

• norm_type: if inf than one gets max pooling if 0 you get sum pooling ( proportional to the avg pooling)
• kernel_size: a single int, the size of the window
• stride: a single int, the stride of the window. Default value is kernel_size
• ceil_mode: when TRUE, will use ceil instead of floor to compute the output shape

Details

• At p = $\infty$, one gets Max Pooling
• At p = 1, one gets Sum Pooling (which is proportional to Average Pooling)

Note

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.

Shape

• Input: $(N, C, L_{in})$
• Output: $(N, C, L_{out})$, where

Examples

if (torch_is_installed()) {
# power-2 pool of window of length 3, with stride 2.
m <- nn_lp_pool1d(2, 3, stride = 2)
input <- torch_randn(20, 16, 50)
output <- m(input)
}