code: def test_return_tensors_tf(self):
      feature_extractor = pipeline(
          task="feature-extraction",
          model="hf-internal-testing/tiny-random-distilbert",
          framework="tf",
      )
      outputs = feature_extractor("This is a test", return_tensors=True)
      self.assertTrue(tf.is_tensor(outputs))
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_feature_extraction.py
imports: import unittest
  import numpy
  from transformers import FEATURE_EXTRACTOR_MAPPING, MODEL_MAPPING, TF_MODEL_MAPPING, FeatureExtractionPipeline, LxmertConfig, is_tf_available, is_torch_available, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch
  from .test_pipelines_common import PipelineTestCaseMeta
label_desc: Use image node_id 6 for calling the FeatureExtractionPipelineTests obj's underlying member method code with example usage: obj.test_return_tensors_tf() without return types