code: def _build_item_extractions(self, train=True):
      self._add_module(
          "item_vec",
          TemporalLatentFactor(
              l2_reg=self._l2_reg,
              init=self._pretrained_item_embeddings,
              ids=self._get_input("item_id", train=train),
              mlp_dims=self._item_dims,
              shape=[self._max_item, self._dim_embed],
              train=train,
              scope="item",
              reuse=not train,
          ),
          train=train,
      )
      self._add_module(
          "item_bias",
          LatentFactor(
              l2_reg=self._l2_reg,
              init="zero",
              ids=self._get_input("item_id", train=train),
              shape=[self._max_item, 1],
              scope="item_bias",
              reuse=not train,
          ),
          train=train,
      )
  
file_path: openrec/openrec/tf1/legacy/recommenders/itr_mlp.py
imports: from __future__ import print_function
  from termcolor import colored
  from openrec.tf1.legacy.recommenders import Recommender
  from openrec.tf1.legacy.modules.extractions import LatentFactor
  from openrec.tf1.legacy.modules.interactions import PointwiseMSE
  from openrec.tf1.legacy.modules.extractions import TemporalLatentFactor
label_desc: Use image node_id 9 for calling the ItrMLP obj's underlying member method code with example usage: obj._build_item_extractions(train) without return types