code: def predict(
      self,
      batch_inputs: Tensor,
      batch_data_samples: SampleList,
      rescale: bool = True,
  ) -> SampleList:
      visual_features = self.extract_feat(batch_inputs)
      outputs = self.sem_seg_head.predict(
          visual_features, batch_data_samples
      )
      return outputs
  
file_path: mmdetection/projects/XDecoder/xdecoder/xdecoder.py
imports: from torch import Tensor
  from mmdet.models.detectors.single_stage import SingleStageDetector
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
label_desc: Use image node_id 2 for calling the XDecoder obj's underlying member method code with example usage: obj.predict(batch_inputs, batch_data_samples, rescale) and returns: outputs