class_docstr: Quantized 2D average pool
class_docstr_tok: ["Quantized","2D","average","pool"]
code: def __init__(
      self,
      kernel_size,
      stride=None,
      padding=0,
      ceil_mode=False,
      count_include_pad=True,
      divisor_override=None,
      **kwargs,
  ):
      super(QuantAvgPool2d, self).__init__(
          kernel_size,
          stride,
          padding,
          ceil_mode,
          count_include_pad,
          divisor_override,
      )
      quant_desc_input = _utils.pop_quant_desc_in_kwargs(
          self.__class__, input_only=True, **kwargs
      )
      self.init_quantizer(quant_desc_input)
  
imports: from torch.nn.modules import pooling
  from .None import _utils
label_desc: Use image node_id 1 to create a new QuantAvgPool2d object from inherited base classes: pooling, _utils with example: obj = QuantAvgPool2d(kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override)