code: def setUp(self):
      self.data = SparkContextForTest.spark.read.option(
          "header", "true"
      ).csv(
          path="file:///"
          + os.getcwd()
          + "/../src/test/resources/embeddings/sentence_embeddings.csv"
      )
  
      self.tested_annotator = (
          XlmRoBertaForTokenClassification.pretrained()
          .setInputCols(["document", "token"])
          .setOutputCol("ner")
      )
  
file_path: spark-nlp/python/test/annotator/classifier_dl/xlm_roberta_for_token_classification_test.py
imports: import os
  import unittest
  import pytest
  from sparknlp.annotator import *
  from sparknlp.base import *
  from test.annotator.common.has_max_sentence_length_test import HasMaxSentenceLengthTests
  from test.util import SparkContextForTest
label_desc: Use image node_id 1 for calling the XlmRoBertaForTokenClassificationTestSpec obj's underlying member method code with example usage: obj.setUp() without return types