Max_pool2d — nnf_max_pool2d • torch

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

Usage

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

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.