nnf_max_pool2d: Max_pool2d
In torch: Tensors and Neural Networks with 'GPU' Acceleration

nnf_max_pool2d

R Documentation

Max_pool2d

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
)

`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.