code: def test_model_npa(mind_resource_path):
      train_news_file = os.path.join(
          mind_resource_path, "train", "news.tsv"
      )
      train_behaviors_file = os.path.join(
          mind_resource_path, "train", "behaviors.tsv"
      )
      valid_news_file = os.path.join(
          mind_resource_path, "valid", "news.tsv"
      )
      valid_behaviors_file = os.path.join(
          mind_resource_path, "valid", "behaviors.tsv"
      )
      wordEmb_file = os.path.join(
          mind_resource_path, "utils", "embedding.npy"
      )
      userDict_file = os.path.join(
          mind_resource_path, "utils", "uid2index.pkl"
      )
      wordDict_file = os.path.join(
          mind_resource_path, "utils", "word_dict.pkl"
      )
      yaml_file = os.path.join(
          mind_resource_path, "utils", "lstur.yaml"
      )
  
      if not os.path.exists(train_news_file):
          download_deeprec_resources(
              "https://recodatasets.z20.web.core.windows.net/newsrec/",
              os.path.join(mind_resource_path, "train"),
              "MINDdemo_train.zip",
          )
      if not os.path.exists(valid_news_file):
          download_deeprec_resources(
              "https://recodatasets.z20.web.core.windows.net/newsrec/",
              os.path.join(mind_resource_path, "valid"),
              "MINDdemo_dev.zip",
          )
      if not os.path.exists(yaml_file):
          download_deeprec_resources(
              "https://recodatasets.z20.web.core.windows.net/newsrec/",
              os.path.join(mind_resource_path, "utils"),
              "MINDdemo_utils.zip",
          )
  
      hparams = prepare_hparams(
          yaml_file,
          wordEmb_file=wordEmb_file,
          wordDict_file=wordDict_file,
          userDict_file=userDict_file,
          epochs=1,
      )
      assert hparams is not None
  
      iterator = MINDIterator
      model = LSTURModel(hparams, iterator)
  
      assert (
          model.run_eval(valid_news_file, valid_behaviors_file)
          is not None
      )
      assert isinstance(
          model.fit(
              train_news_file,
              train_behaviors_file,
              valid_news_file,
              valid_behaviors_file,
          ),
          BaseModel,
      )
  
imports: import os
  import pytest
label_desc: Use image node_id 4 for calling a global function with example usage: test_model_npa(mind_resource_path) without return types