code: def forward(self, rois_feat):
      for i in range(self.num_convs):
          rois_feat = F.relu(self.bbox_head_convs[i](rois_feat))
      rois_feat = paddle.flatten(rois_feat, start_axis=1, stop_axis=-1)
      fc6 = F.relu(self.fc6(rois_feat))
      return fc6
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import Normal, XavierUniform, KaimingNormal
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register, create
  from .roi_extractor import RoIAlign
  from ..shape_spec import ShapeSpec
  from ..bbox_utils import bbox2delta
  from ..cls_utils import _get_class_default_kwargs
  from ppdet.modeling.layers import ConvNormLayer
label_desc: Use image node_id 4 for calling the XConvNormHead obj's underlying member method code with example usage: obj.forward(rois_feat) and returns: fc6