code: def forward(self, feat_list):
      logit_list = []
      x = feat_list[self.backbone_indices[1]]
  
      feature = self.conv_bn_relu(x)
      gru_output = self.gru_module(feature)
      output = self.dropout(gru_output)
      logit = self.classifier(output)
      logit_list.append(logit)
  
      if self.enable_auxiliary_loss:
          low_level_feat = feat_list[self.backbone_indices[0]]
          auxiliary_logit = self.auxlayer(low_level_feat)
          logit_list.append(auxiliary_logit)
  
      return logit_list
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the GloReHead obj's underlying member method code with example usage: obj.forward(feat_list) and returns: logit_list