class_docstr: Quantized 1D maxpool
class_docstr_tok: ["Quantized","1D","maxpool"]
code: def __init__(
      self,
      kernel_size,
      stride=None,
      padding=0,
      dilation=1,
      return_indices=False,
      ceil_mode=False,
      **kwargs,
  ):
      super(QuantMaxPool1d, self).__init__(
          kernel_size,
          stride,
          padding,
          dilation,
          return_indices,
          ceil_mode,
      )
      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 QuantMaxPool1d object from inherited base classes: pooling, _utils with example: obj = QuantMaxPool1d(kernel_size, stride, padding, dilation, return_indices, ceil_mode)