torch.nn.functional.avg_pool2d
torch.nn.functional.avg_pool2d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=None) -> Tensor
Applies 2D average-pooling operation in kH \times kW regions by
   step size sH \times sW steps. The number of output features is
   equal to the number of input planes.
See "AvgPool2d" for details and output shape.
Parameters:
      * input -- input tensor (\text{minibatch} ,
        \text{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*
