nnf_max_pool1d: Max_pool1d
In torch: Tensors and Neural Networks with 'GPU' Acceleration

nnf_max_pool1d

R Documentation

Max_pool1d

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

nnf_max_pool1d(
  input,
  kernel_size,
  stride = NULL,
  padding = 0,
  dilation = 1,
  ceil_mode = FALSE,
  return_indices = FALSE
)

`input`	input tensor of shape (minibatch , 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
`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` to compute the output shape. Default: `FALSE`
`return_indices`	whether to return the indices where the max occurs.