code: def test_onehot_random_inputs(drop, sparse, n_samples, as_array):
      X, ary = generate_inputs_from_categories(
          n_samples=n_samples, as_array=as_array
      )
  
      enc = OneHotEncoder(sparse=sparse, drop=drop, categories="auto")
      sk_enc = SkOneHotEncoder(
          sparse=sparse, drop=drop, categories="auto"
      )
      ohe = enc.fit_transform(X)
      ref = sk_enc.fit_transform(ary)
      if sparse:
          cp.testing.assert_array_equal(ohe.toarray(), ref.toarray())
      else:
          cp.testing.assert_array_equal(ohe, ref)
      inv_ohe = enc.inverse_transform(ohe)
      assert_inverse_equal(inv_ohe, X)
  
imports: from sklearn.preprocessing import OneHotEncoder
  from cuml.testing.utils import stress_param, from_df_to_numpy, assert_inverse_equal, generate_inputs_from_categories
  from cuml.preprocessing import OneHotEncoder
  from cuml.internals.safe_imports import gpu_only_import_from
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
  import math
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 9 for calling a global function with example usage: test_onehot_random_inputs(drop, sparse, n_samples, as_array) without return types