nnf_max_pool2d: Max_pool2d

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

Max_pool2d

Description

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
)

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.

torch documentation built on June 7, 2023, 6:19 p.m.