class_docstr: This is a common part of auto-encoders. All the auto-encoder models should inherit this class,
  including CDAE, MacridVAE, MultiDAE, MultiVAE, RaCT and RecVAE.
  The base AutoEncoderMixin class provides basic dataset information and rating matrix function.
class_docstr_tok: ["This","is","a","common","part","of","auto-encoders",".","All","the","auto-encoder","models","should","inherit","this","class",",","including","CDAE",",","MacridVAE",",","MultiDAE",",","MultiVAE",",","RaCT","and","RecVAE",".","The","base","AutoEncoderMixin","class","provides","basic","dataset","information","and","rating","matrix","function","."]
code: def build_histroy_items(self, dataset):
      (
          self.history_item_id,
          self.history_item_value,
          _,
      ) = dataset.history_item_matrix()
      self.history_item_id = self.history_item_id.to(self.device)
      self.history_item_value = self.history_item_value.to(self.device)
  
imports: from logging import getLogger
  import numpy
  import torch
  import torch.nn
  from recbole.model.layers import FMEmbedding, FMFirstOrderLinear, FLEmbedding
  from recbole.utils import ModelType, InputType, FeatureSource, FeatureType, set_color
label_desc: Use image node_id 1 for calling the AutoEncoderMixin obj's underlying member method code with example usage: obj.build_histroy_items(dataset) without return types