avg_pool2d
class torch.ao.nn.quantized.functional.avg_pool2d(input, kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True, divisor_override=None)
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.
Note:
 The input quantization parameters propagate to the output.

See "AvgPool2d" for details and output shape.
Parameters:
      * input -- quantized 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
