nnf_avg_pool2d function

Avg_pool2d

Applies 2D average-pooling operation in $kH * kW$ regions by step size $sH * sW$ steps. The number of output features is equal to the number of input planes.

nnf_avg_pool2d(
  input,
  kernel_size,
  stride = NULL,
  padding = 0,
  ceil_mode = FALSE,
  count_include_pad = TRUE,
  divisor_override = NULL
)

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
• ceil_mode: when True, will use ceil instead of floor in the formula to compute the output shape. Default: FALSE
• count_include_pad: when True, will include the zero-padding in the averaging calculation. Default: TRUE
• divisor_override: if specified, it will be used as divisor, otherwise size of the pooling region will be used. Default: NULL