code: def testBasicPipeline(self):
      if not context.executing_eagerly():
          self.skipTest(
              "testBasicPipeline only supported in eager mode."
          )
  
      sp = SentencepieceTokenizer(self.model)
  
      strings = ["hello", "world"]
      dataset = dataset_ops.Dataset.from_tensor_slices(strings)
      # Ensure we can map the tokenizer across the dataset.
      dataset1 = dataset.map(sp.tokenize)
      # Ensure there's no error with a second map call.
      dataset2 = dataset.map(sp.tokenize)
  
      expected = sp.tokenize(strings)
      for i, result in enumerate(dataset1):
          self.assertAllEqual(result, expected[i])
      for i, result in enumerate(dataset2):
          self.assertAllEqual(result, expected[i])
  
imports: import sys
  import tempfile
  from absl.testing import parameterized
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.module import module
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_gather_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import load
  from tensorflow.python.saved_model import save
  from tensorflow_text.python.ops.sentencepiece_tokenizer import SentencepieceTokenizer
label_desc: Use image node_id 26 for calling the SentencepieceTokenizerOpTest obj's underlying member method code with example usage: obj.testBasicPipeline() without return types