code: def setUp(self):
      self.vectors_cache_dir = ".cache"
      if os.path.exists(self.vectors_cache_dir):
          shutil.rmtree(self.vectors_cache_dir)
  
      self.data_cache_path = os.path.join(
          test_dir_path, "test_datasets", "train_cache.pth"
      )
      if os.path.exists(self.data_cache_path):
          os.remove(self.data_cache_path)
  
      vec_dir = os.path.abspath(
          os.path.join(test_dir_path, "test_datasets")
      )
      filename = "fasttext_sample.vec.zip"
      url_base = urljoin("file:", pathname2url(vec_dir)) + os.path.sep
      ft = FastText(
          filename, url_base=url_base, cache=self.vectors_cache_dir
      )
  
      self.train, self.valid, self.test = process(
          path=os.path.join(test_dir_path, "test_datasets"),
          cache="train_cache.pth",
          train="test_train.csv",
          validation="test_valid.csv",
          test="test_test.csv",
          embeddings=ft,
          embeddings_cache_path="",
          ignore_columns=("left_id", "right_id"),
      )
  
imports: from nose.tools import *
  import io
  import os
  import shutil
  import pandas
  import torch
  import unittest
  from deepmatcher import attr_summarizers
  from deepmatcher.data.field import MatchingField, FastText
  from deepmatcher.data.process import process, process_unlabeled
  from deepmatcher import MatchingModel
  from urllib.parse import urljoin
  from urllib.request import pathname2url
  from test import test_dir_path
label_desc: Use image node_id 1 for calling the ModelPredictUnlabeledTest obj's underlying member method code with example usage: obj.setUp() without return types