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.

## Usage

```
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`