code: def evaluate_stsb_test(model, expected_score, test_samples) -> None:
      evaluator = EmbeddingSimilarityEvaluator.from_input_examples(
          test_samples, name="sts-test"
      )
      score = model.evaluate(evaluator) * 100
      print(
          "STS-Test Performance: {:.2f} vs. exp: {:.2f}".format(
              score, expected_score
          )
      )
      assert score > expected_score or abs(score - expected_score) < 0.1
  
file_path: sentence-transformers/tests/test_train_stsb.py
imports: import csv
  import gzip
  import os
  from typing import Generator, List, Tuple
  import pytest
  from torch.utils.data import DataLoader
  from sentence_transformers import SentencesDataset, SentenceTransformer, losses, util
  from sentence_transformers.evaluation import EmbeddingSimilarityEvaluator
  from sentence_transformers.readers import InputExample
label_desc: Use image node_id 3 for calling a global function with example usage: evaluate_stsb_test(model, expected_score, test_samples) without return types