code: def test_ParaphraseMiningEvaluator(
      paraphrase_distilroberta_base_v1_model: SentenceTransformer,
  ) -> None:
      """Tests that the ParaphraseMiningEvaluator can be loaded"""
      model = paraphrase_distilroberta_base_v1_model
      sentences = {
          0: "Hello World",
          1: "Hello World!",
          2: "The cat is on the table",
          3: "On the table the cat is",
      }
      data_eval = evaluation.ParaphraseMiningEvaluator(
          sentences, [(0, 1), (2, 3)]
      )
      score = data_eval(model)
      assert score > 0.99
  
file_path: sentence-transformers/tests/test_evaluator.py
imports: import csv
  import gzip
  import os
  import numpy
  from sklearn.metrics import accuracy_score, f1_score
  from torch.utils.data import DataLoader
  from sentence_transformers import InputExample, SentenceTransformer, evaluation, losses, util
label_desc: Use image node_id 4 for calling a global function with example usage: test_ParaphraseMiningEvaluator(paraphrase_distilroberta_base_v1_model) without return types