def __init__(self, num_classes=15, nms_pre=2000, min_bbox_size=0, nms=None):
    super(S2ANetBBoxPostProcess, self).__init__()
    self.num_classes = num_classes
    self.nms_pre = paddle.to_tensor(nms_pre)
    self.min_bbox_size = min_bbox_size
    self.nms = nms
    self.origin_shape_list = []
    self.fake_pred_cls_score_bbox = paddle.to_tensor(np.array([[(- 1), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype='float32'))
    self.fake_bbox_num = paddle.to_tensor(np.array([1], dtype='int32'))
def __init__(self, num_classes=15, nms_pre=2000, min_bbox_size=0, nms=None):
    super(S2ANetBBoxPostProcess, self).__init__()
    self.num_classes = num_classes
    self.nms_pre = paddle.to_tensor(nms_pre)
    self.min_bbox_size = min_bbox_size
    self.nms = nms
    self.origin_shape_list = []
    self.fake_pred_cls_score_bbox = paddle.to_tensor(np.array([[(- 1), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype='float32'))
    self.fake_bbox_num = paddle.to_tensor(np.array([1], dtype='int32'))