Max_pool2d — nnf_max_pool2d • torch

Applies a 2D max pooling over an input signal composed of several input planes.

nnf_max_pool2d(
  input,
  kernel_size,
  stride = kernel_size,
  padding = 0,
  dilation = 1,
  ceil_mode = FALSE,
  return_indices = FALSE
)

Arguments

input	input tensor (minibatch, in_channels , iH , iW)
kernel_size	size of the pooling region. Can be a single number or a tuple `(kH, kW)`
stride	stride of the pooling operation. Can be a single number or a tuple `(sH, sW)`. Default: `kernel_size`
padding	implicit zero paddings on both sides of the input. Can be a single number or a tuple `(padH, padW)`. Default: 0
dilation	controls the spacing between the kernel points; also known as the à trous algorithm.
ceil_mode	when True, will use `ceil` instead of `floor` in the formula to compute the output shape. Default: `FALSE`
return_indices	whether to return the indices where the max occurs.