docstr: Test if the component ranks documents correctly.
docstr_tok: ["Test","if","the","component","ranks","documents","correctly","."]
code: def test_run(
      self, query, docs_before_texts, expected_first_text, scores
  ):
      """
      Test if the component ranks documents correctly.
      """
      ranker = TransformersSimilarityRanker(
          model="cross-encoder/ms-marco-MiniLM-L-6-v2"
      )
      ranker.warm_up()
      docs_before = [
          Document(content=text) for text in docs_before_texts
      ]
      output = ranker.run(query=query, documents=docs_before)
      docs_after = output["documents"]
  
      assert len(docs_after) == 3
      assert docs_after[0].content == expected_first_text
  
      sorted_scores = sorted(scores, reverse=True)
      assert docs_after[0].score == pytest.approx(
          sorted_scores[0], abs=1e-6
      )
      assert docs_after[1].score == pytest.approx(
          sorted_scores[1], abs=1e-6
      )
      assert docs_after[2].score == pytest.approx(
          sorted_scores[2], abs=1e-6
      )
  
file_path: haystack/test/components/rankers/test_transformers_similarity.py
imports: from unittest.mock import MagicMock, patch
  import pytest
  import torch
  from transformers.modeling_outputs import SequenceClassifierOutput
  from haystack import Document, ComponentError
  from haystack.components.rankers.transformers_similarity import TransformersSimilarityRanker
label_desc: Use image node_id 8 for calling the TestSimilarityRanker obj's underlying member method code with example usage: obj.test_run(query, docs_before_texts, expected_first_text, scores) without return types