code: def _varifocal_loss(
      pred_score, gt_score, label, alpha=0.75, gamma=2.0
  ):
      weight = (
          alpha * pred_score.pow(gamma) * (1 - label) + gt_score * label
      )
      loss = F.binary_cross_entropy(
          pred_score, gt_score, weight=weight, reduction="sum"
      )
      return loss
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ..losses import ProbIoULoss
  from ..initializer import bias_init_with_prob, constant_, normal_, vector_
  from ppdet.modeling.backbones.cspresnet import ConvBNLayer
  from ppdet.modeling.ops import get_static_shape, get_act_fn, anchor_generator
  from ppdet.modeling.layers import MultiClassNMS
label_desc: Use image node_id 11 for calling the PPYOLOERHead obj's underlying member method code with example usage: obj._varifocal_loss(pred_score, gt_score, label, alpha, gamma) and returns: loss