nn_avg_pool1d function

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

In the simplest case, the output value of the layer with input size $(N, C, L)$, output $(N, C, L_{out})$ and kernel_size $k$

can be precisely described as:

nn_avg_pool1d(
  kernel_size,
  stride = NULL,
  padding = 0,
  ceil_mode = FALSE,
  count_include_pad = TRUE
)

Arguments

• kernel_size: the size of the window
• stride: the stride of the window. Default value is kernel_size
• padding: implicit zero padding to be added on both sides
• ceil_mode: when TRUE, will use ceil instead of floor to compute the output shape
• count_include_pad: when TRUE, will include the zero-padding in the averaging calculation

Details

If padding is non-zero, then the input is implicitly zero-padded on both sides for padding number of points.

The parameters kernel_size, stride, padding can each be an int or a one-element tuple.

Shape

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

Examples

if (torch_is_installed()) {

# pool with window of size=3, stride=2
m <- nn_avg_pool1d(3, stride = 2)
m(torch_randn(1, 1, 8))
}