code: def get_test_pipeline(self, model, tokenizer, processor):
      token_classifier = TokenClassificationPipeline(
          model=model, tokenizer=tokenizer
      )
      return token_classifier, [
          "A simple string",
          "A simple string that is quite a bit longer",
      ]
  
imports: import unittest
  import numpy
  from transformers import MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, AutoModelForTokenClassification, AutoTokenizer, TokenClassificationPipeline, pipeline
  from transformers.pipelines import AggregationStrategy, TokenClassificationArgumentHandler
  from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, require_torch_accelerator, slow, torch_device
  from .test_pipelines_common import ANY
label_desc: Use image node_id 1 for calling the TokenClassificationPipelineTests obj's underlying member method code with example usage: obj.get_test_pipeline(model, tokenizer, processor) and returns: token_classifier,  list