code: def dkn_files(deeprec_resource_path):
      data_path = os.path.join(deeprec_resource_path, "dkn")
      yaml_file = os.path.join(data_path, "dkn.yaml")
      news_feature_file = os.path.join(data_path, "doc_feature.txt")
      user_history_file = os.path.join(data_path, "user_history.txt")
      wordEmb_file = os.path.join(data_path, "word_embeddings_100.npy")
      entityEmb_file = os.path.join(
          data_path, "TransE_entity2vec_100.npy"
      )
      contextEmb_file = os.path.join(
          data_path, "TransE_context2vec_100.npy"
      )
  
      download_deeprec_resources(
          "https://recodatasets.z20.web.core.windows.net/deeprec/",
          data_path,
          "mind-demo.zip",
      )
      return (
          data_path,
          yaml_file,
          news_feature_file,
          user_history_file,
          wordEmb_file,
          entityEmb_file,
          contextEmb_file,
      )
  
file_path: recommenders/tests/unit/recommenders/models/test_deeprec_model.py
imports: import os
  import pytest
  from recommenders.datasets import movielens
  from recommenders.datasets.amazon_reviews import download_and_extract, data_preprocessing
  from recommenders.datasets.python_splitters import python_stratified_split
label_desc: Use image node_id 1 for calling a global function with example usage: dkn_files(deeprec_resource_path) and returns: data_path,  yaml_file,  news_feature_file,  user_history_file,  wordEmb_file,  entityEmb_file,  contextEmb_file