code: def test_encode_tuple_sentences(
      paraphrase_distilroberta_base_v1_model: SentenceTransformer,
  ) -> None:
      model = paraphrase_distilroberta_base_v1_model
      # Input a sentence tuple
      emb = model.encode(
          [("Hello Word, a test sentence", "Second input for model")]
      )
      assert emb.shape == (1, 768)
      assert abs(np.sum(emb) - 9.503508) < 0.001
  
      # List of sentence tuples
      emb = model.encode(
          [
              ("Hello Word, a test sentence", "Second input for model"),
              ("My second tuple", "With two inputs"),
              ("Final tuple", "final test"),
          ]
      )
      assert emb.shape == (3, 768)
      assert abs(np.sum(emb) - 32.14627) < 0.001
  
imports: import numpy
  from sentence_transformers import SentenceTransformer
label_desc: Use image node_id 4 for calling a global function with example usage: test_encode_tuple_sentences(paraphrase_distilroberta_base_v1_model) without return types