code: def test_metric_kwargs_init():
      y_true = np.array([1, 1, 1, 0, 0, 0])
      y_pred = np.array([0, 1, 1, 0, 1, 1])
      f1_pos_label_0 = make_scorer(
          "f1", sklearn.metrics.f1_score, pos_label=0
      )
      f1_pos_label_0_v2 = make_scorer(
          "f1",
          sklearn.metrics.f1_score,
          metric_kwargs=dict(pos_label=0),
      )
      f1_pos_label_0_test_override = make_scorer(
          "f1",
          sklearn.metrics.f1_score,
          metric_kwargs=dict(pos_label=0),
          pos_label=1,
      )
  
      score_og = f1(y_true, y_pred)
      score_pos_label_0_og = f1(y_true, y_pred, pos_label=0)
      score_pos_label_0 = f1_pos_label_0(y_true, y_pred)
      score_pos_label_0_v2 = f1_pos_label_0_v2(y_true, y_pred)
      score_pos_label_0_test_override = f1_pos_label_0_test_override(
          y_true, y_pred
      )
  
      assert score_og > score_pos_label_0_og
      assert score_pos_label_0_og == score_pos_label_0
      assert score_pos_label_0_og == score_pos_label_0_v2
      assert score_pos_label_0_og == score_pos_label_0_test_override
  
      # assert that kwargs passed during call override init kwargs
      assert score_og == f1_pos_label_0(y_true, y_pred, pos_label=1)
  
imports: import numpy
  import sklearn.metrics
  from autogluon.core.metrics import f1, make_scorer
label_desc: Use image node_id 2 for calling a global function with example usage: test_metric_kwargs_init() without return types