code: def test_label_encoder_empty_array(values):
      le = LabelEncoder()
      le.fit(values)
      # test empty transform
      transformed = le.transform([])
      assert_array_equal(np.array([]), transformed)
      # test empty inverse transform
      inverse_transformed = le.inverse_transform([])
      assert_array_equal(np.array([]), inverse_transformed)
  
imports: import numpy
  import pytest
  from scipy.sparse import issparse
  from sklearn import datasets
  from sklearn.preprocessing._label import LabelBinarizer, LabelEncoder, MultiLabelBinarizer, _inverse_binarize_multiclass, _inverse_binarize_thresholding, label_binarize
  from sklearn.utils import _to_object_array
  from sklearn.utils._testing import assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 12 for calling a global function with example usage: test_label_encoder_empty_array(values) without return types