code: def test_rouge1():
      predictions = pd.Series(["a", "d c"])
      targets = pd.Series(["d", "b c"])
      result = rouge1().eval_fn(predictions, targets, {})
      assert result.scores[0] == 0.0
      assert result.scores[1] == 0.5
      assert result.aggregate_results["mean"] == 0.25
      assert result.aggregate_results["p90"] == 0.45
      assert result.aggregate_results["variance"] == 0.0625
  
imports: from unittest import mock
  import pandas
  import pytest
  from mlflow.metrics import MetricValue, ari_grade_level, exact_match, f1_score, flesch_kincaid_grade_level, mae, mape, max_error, mse, ndcg_at_k, precision_at_k, precision_score, r2_score, recall_at_k, recall_score, rmse, rouge1, rouge2, rougeL, rougeLsum, toxicity
label_desc: Use image node_id 7 for calling a global function with example usage: test_rouge1() without return types