nnf_avg_pool3d: Avg_pool3d
In torch: Tensors and Neural Networks with 'GPU' Acceleration

nnf_avg_pool3d

R Documentation

Avg_pool3d

Description

Applies 3D average-pooling operation in kT * kH * kW regions by step size sT * sH * sW steps. The number of output features is equal to \lfloor \frac{ \mbox{input planes} }{sT} \rfloor.

Usage

nnf_avg_pool3d(
  input,
  kernel_size,
  stride = NULL,
  padding = 0,
  ceil_mode = FALSE,
  count_include_pad = TRUE,
  divisor_override = NULL
)

Arguments

`input`	input tensor (minibatch, in_channels , iT * iH , iW)
`kernel_size`	size of the pooling region. Can be a single number or a tuple `⁠(kT, kH, kW)⁠`
`stride`	stride of the pooling operation. Can be a single number or a tuple `⁠(sT, sH, sW)⁠`. Default: `kernel_size`
`padding`	implicit zero paddings on both sides of the input. Can be a single number or a tuple `⁠(padT, padH, padW)⁠`, Default: 0
`ceil_mode`	when True, will use `ceil` instead of `floor` in the formula to compute the output shape
`count_include_pad`	when True, will include the zero-padding in the averaging calculation
`divisor_override`	NA if specified, it will be used as divisor, otherwise size of the pooling region will be used. Default: `NULL`