code: def multibox_transform_loc(
      cls_prob,
      loc_pred,
      anchor,
      clip=True,
      threshold=0.01,
      variances=(0.1, 0.1, 0.2, 0.2),
      keep_background=False,
  ):
      """Location transformation for multibox detection
  
      Parameters
      ----------
      cls_prob : tvm.relay.Expr
          Class probabilities.
  
      loc_pred : tvm.relay.Expr
          Location regression predictions.
  
      anchor : tvm.relay.Expr
          Prior anchor boxes.
  
      clip : boolean, optional
          Whether to clip out-of-boundary boxes.
  
      threshold : double, optional
          Threshold to be a positive prediction.
  
      variances : Tuple of float, optional
          variances to be decoded from box regression output.
  
      keep_background : boolean, optional
          Whether to keep boxes detected as background or not.
  
      Returns
      -------
      ret : tuple of tvm.relay.Expr
      """
      return expr.TupleWrapper(
          _make.multibox_transform_loc(
              cls_prob,
              loc_pred,
              anchor,
              clip,
              threshold,
              variances,
              keep_background,
          ),
          2,
      )
  
imports: from tvm.relay import expr
  from .None import _make
label_desc: Use image node_id 2 for calling a global function with example usage: multibox_transform_loc(cls_prob, loc_pred, anchor, clip, threshold, variances, keep_background) and returns: expr