torch_avg_pool1d: Avg_pool1d

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Avg_pool1d

Description

Avg_pool1d

Usage

torch_avg_pool1d(
  self,
  kernel_size,
  stride = list(),
  padding = 0L,
  ceil_mode = FALSE,
  count_include_pad = TRUE
)

Arguments

self	input tensor of shape (\mbox{minibatch} , \mbox{in\_channels} , iW)
kernel_size	the size of the window. Can be a single number or a tuple ⁠(kW,)⁠
stride	the stride of the window. Can be a single number or a tuple ⁠(sW,)⁠. Default: kernel_size
padding	implicit zero paddings on both sides of the input. Can be a single number or a tuple ⁠(padW,)⁠. Default: 0
ceil_mode	when TRUE, will use ceil instead of floor to compute the output shape. Default: FALSE
count_include_pad	when TRUE, will include the zero-padding in the averaging calculation. Default: TRUE

avg_pool1d(input, kernel_size, stride=NULL, padding=0, ceil_mode=FALSE, count_include_pad=TRUE) -> Tensor

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

See nn_avg_pool1d() for details and output shape.

torch documentation built on May 29, 2024, 9:54 a.m.