code: def _run(  # type: ignore
      self,
      x,
      x_scale,
      x_zero_point,
      w,
      w_scale,
      w_zero_point,
      y_scale,
      y_zero_point,
      B=None,
      auto_pad=None,
      dilations=None,
      group=None,
      kernel_shape=None,
      pads=None,
      strides=None,
  ):
      auto_pad = auto_pad or self.auto_pad  # type: ignore
      dilations = dilations or self.dilations  # type: ignore
      group = group or self.group  # type: ignore
      kernel_shape = kernel_shape or self.kernel_shape  # type: ignore
      pads = pads or self.pads  # type: ignore
      strides = strides or self.strides  # type: ignore
  
      X = x.astype(np.int32)
      if x_zero_point is not None:
          X -= x_zero_point
      W = w.astype(np.int32)
      if w_zero_point is not None:
          if (
              len(w_zero_point.shape) == 1
              and w_zero_point.shape[0] == W.shape[0]
          ):
              missing = (w_zero_point.shape[0],) + (1,) * (
                  len(W.shape) - 1
              )
              W -= w_zero_point.reshape(missing)
          else:
              W -= w_zero_point
  
      res = _conv_implementation(
          X,
          W,
          B,
          auto_pad,
          dilations,
          group,
          kernel_shape,
          pads,
          strides,
      ).astype(np.int32)
  
      R = res * (x_scale * w_scale / y_scale)
      if y_zero_point is not None:
          R += y_zero_point
          if y_zero_point.dtype == np.int8:
              R = np.clip(R, -128, 127)
          else:
              R = np.clip(R, 0, 255)
          return (np.round(R).astype(y_zero_point.dtype),)
      if x.dtype == np.int8:
          R = np.clip(R, -128, 127)
      else:
          R = np.clip(R, 0, 255)
      return (np.round(R).astype(x.dtype),)
  
imports: import numpy
  from onnx.reference.op_run import OpRun
  from onnx.reference.ops.op_conv import _conv_implementation
label_desc: Use image node_id 1 for calling the QLinearConv obj's underlying member method code with example usage: obj._run(x, x_scale, x_zero_point, w, w_scale, w_zero_point, y_scale, y_zero_point, B, auto_pad, dilations, group, kernel_shape, pads, strides) and returns: np, np