code: def setUp(self):
      self.spark = SparkContextForTest.spark
      self.text = "I have a problem with my iphone that needs to be resolved asap!!"
      self.inputDataset = self.spark.createDataFrame(
          [[self.text]]
      ).toDF("text")
  
      self.tested_annotator = (
          BertForZeroShotClassification.pretrained(
              "bert_base_cased_zero_shot_classifier_xnli"
          )
          .setInputCols(["document", "token"])
          .setOutputCol("class")
          .setCandidateLabels(
              [
                  "urgent",
                  "mobile",
                  "travel",
                  "movie",
                  "music",
                  "sport",
                  "weather",
                  "technology",
              ]
          )
      )
  
file_path: spark-nlp/python/test/annotator/classifier_dl/bert_for_zero_shot_classification_test.py
imports: 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 BertForZeroShotClassificationTestSpec obj's underlying member method code with example usage: obj.setUp() without return types