code: def test_set_leaf_output():
      X, y = load_breast_cancer(return_X_y=True)
      ds = lgb.Dataset(X, y)
      bst = lgb.Booster({"num_leaves": 2}, ds)
      bst.update()
      y_pred = bst.predict(X)
      for leaf_id in range(2):
          leaf_output = bst.get_leaf_output(tree_id=0, leaf_id=leaf_id)
          bst.set_leaf_output(
              tree_id=0, leaf_id=leaf_id, value=leaf_output + 1
          )
      np.testing.assert_allclose(bst.predict(X), y_pred + 1)
  
imports: import filecmp
  import numbers
  import re
  from copy import deepcopy
  from os import getenv
  from pathlib import Path
  import numpy
  import pytest
  from scipy import sparse
  from sklearn.datasets import dump_svmlight_file, load_svmlight_file
  from sklearn.model_selection import train_test_split
  import lightgbm
  from lightgbm.compat import PANDAS_INSTALLED, pd_DataFrame, pd_Series
  from .utils import dummy_obj, load_breast_cancer, mse_obj, np_assert_array_equal
label_desc: Use image node_id 33 for calling a global function with example usage: test_set_leaf_output() without return types