code: def finalize_minibatch(
      self, accumulated_minibatch_data: Dict[str, Any], device: Any
  ) -> Dict[str, Any]:
      return {
          "node_data": self.__str_node_annotation.finalize_minibatch(
              accumulated_minibatch_data["node_data"], device=device
          ),
          "is_candidate": torch.tensor(
              accumulated_minibatch_data["is_candidate"],
              dtype=torch.float32,
              device=device,
          ),
      }
  
imports: import torch
  from torch import nn
  from typing import Any, Dict, Tuple
  from ptgnn.baseneuralmodel import AbstractNeuralModel
  from ptgnn.neuralmodels.embeddings.strelementrepresentationmodel import StrElementRepresentationModel
  from ptgnn.neuralmodels.gnn.structs import AbstractNodeEmbedder
label_desc: Use image node_id 7 for calling the CandidateNodeAnnotationModel obj's underlying member method code with example usage: obj.finalize_minibatch(accumulated_minibatch_data, device) and returns: dict