code: def setUp(self):
      self.images_path = os.getcwd() + "/../src/test/resources/image/"
      self.data = SparkSessionForTest.spark.read.format("image").load(
          path=self.images_path
      )
  
      image_assembler = (
          ImageAssembler()
          .setInputCol("image")
          .setOutputCol("image_assembler")
      )
  
      image_classifier = (
          ViTForImageClassification.pretrained()
          .setInputCols("image_assembler")
          .setOutputCol("class")
      )
  
      pipeline = Pipeline(
          stages=[
              image_assembler,
              image_classifier,
          ]
      )
  
      self.vit_model = pipeline.fit(self.data)
  
imports: import os
  import unittest
  import pytest
  from pyspark.sql.functions import col
  from sparknlp.pretrained import PretrainedPipeline
  from test.util import SparkSessionForTest, SparkContextForTest
  from sparknlp.annotator import *
  from sparknlp.base import *
label_desc: Use image node_id 1 for calling the LightPipelineImageSetUp obj's underlying member method code with example usage: obj.setUp() without return types