code: def forward(self, feats):
      cls_scores = []
      bbox_preds = []
      for x, scale in zip(feats, self.scales):
          cls_feat = x
          reg_feat = x
          for cls_conv in self.cls_convs:
              cls_feat = cls_conv(cls_feat)
          for reg_conv in self.reg_convs:
              reg_feat = reg_conv(reg_feat)
  
          cls_score = self.gfl_cls(cls_feat)
          cls_score = F.sigmoid(cls_score)
          cls_score = cls_score.flatten(2).transpose([0, 2, 1])
          cls_scores.append(cls_score)
  
          bbox_pred = scale(self.gfl_reg(reg_feat))
          bbox_pred = bbox_pred.flatten(2).transpose([0, 2, 1])
          bbox_preds.append(bbox_pred)
  
      cls_scores = paddle.concat(cls_scores, axis=1)
      bbox_preds = paddle.concat(bbox_preds, axis=1)
      return cls_scores, bbox_preds
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from paddle import ParamAttr
  from paddle.nn.initializer import KaimingNormal
  from paddle.nn.initializer import Normal, Constant
  from ..bbox_utils import batch_distance2bbox
  from ..losses import GIoULoss
  from ..initializer import bias_init_with_prob, constant_, normal_
  from ..assigners.utils import generate_anchors_for_grid_cell
  from ppdet.modeling.backbones.cspresnet import ConvBNLayer, RepVggBlock
  from ppdet.modeling.ops import get_static_shape, get_act_fn
  from ppdet.modeling.layers import MultiClassNMS
label_desc: Use image node_id 2 for calling the SimpleConvHead obj's underlying member method code with example usage: obj.forward(feats) and returns: cls_scores,  bbox_preds