code: def test_onehot_drop_one_of_each(as_array):
      X = DataFrame(
          {"chars": ["c", "b"], "int": [2, 2], "letters": ["a", "b"]}
      )
      drop = dict({"chars": "b", "int": 2, "letters": "b"})
      X_ary = from_df_to_numpy(X)
      drop_ary = ["b", 2, "b"]
      if as_array:
          X = _from_df_to_cupy(X)
          X_ary = cp.asnumpy(X)
          drop = drop_ary = _convert_drop(drop)
  
      enc = OneHotEncoder(sparse=False, drop=drop, categories="auto")
      ohe = enc.fit_transform(X)
      print(ohe.dtype)
      ref = SkOneHotEncoder(
          sparse=False, drop=drop_ary, categories="auto"
      ).fit_transform(X_ary)
      cp.testing.assert_array_equal(ohe, ref)
      inv = enc.inverse_transform(ohe)
      assert_inverse_equal(inv, 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 11 for calling a global function with example usage: test_onehot_drop_one_of_each(as_array) without return types