How do you do a grid search with cuml without a datatype error? - cupy

Question

I tried doing a grid search with cuml. (rapids 21.10) I get a cupy conversion error. This doesn't happen if I build the model with the same dataset without a grid search. It also works doing it with the Data not lying in Videomemory, but it is then obviously slower than cpu.
The data is float32 for X and int32 for y:
X_cudf_train = cudf.DataFrame.from_pandas(X_train)
X_cudf_test = cudf.DataFrame.from_pandas(X_test)
​
y_cudf_train = cudf.Series(y_train.values)
RF_classifier_cu = RandomForestClassifier_cu(random_state = 123)
grid_search_RF_cu = GridSearchCV_cu(estimator=RF_classifier_cu, param_grid=grid_RF, cv=3, verbose=1)
grid_search_RF_cu.fit(X_cudf_train,y_cudf_train)
print(grid_search_RF_cu.best_params_)
The error:
/home/asdanjer/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/cuml/internals/api_decorators.py:794: UserWarning: For reproducible results in Random Forest Classifier or for almost reproducible results in Random Forest Regressor, n_streams==1 is recommended. If n_streams is > 1, results may vary due to stream/thread timing differences, even when random_state is set
return func(**kwargs)
---------------------------------------------------------------------------
TypeError
Traceback (most recent call last)
<timed exec> in <module>
~/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/sklearn/model_selection/_search.py in fit(self, X, y, groups, **fit_params)
800 fit_params = _check_fit_params(X, fit_params)
801
--> 802 cv_orig = check_cv(self.cv, y, classifier=is_classifier(estimator))
803 n_splits = cv_orig.get_n_splits(X, y, groups)
804
~/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/sklearn/model_selection/_split.py in check_cv(cv, y, classifier)
2301 classifier
2302 and (y is not None)
-> 2303 and (type_of_target(y) in ("binary", "multiclass"))
2304 ):
2305 return StratifiedKFold(cv)
~/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/sklearn/utils/multiclass.py in type_of_target(y)
277 raise ValueError("y cannot be class 'SparseSeries' or 'SparseArray'")
278
--> 279 if is_multilabel(y):
280 return "multilabel-indicator"
281
~/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/sklearn/utils/multiclass.py in is_multilabel(y)
149 warnings.simplefilter("error", np.VisibleDeprecationWarning)
150 try:
--> 151 y = np.asarray(y)
152 except np.VisibleDeprecationWarning:
153 # dtype=object should be provided explicitly for ragged arrays,
~/miniconda3/envs/rapids-21.10/lib/python3.8/site-packages/cudf/core/frame.py in __array__(self, dtype)
1636
1637 def __array__(self, dtype=None):
-> 1638 raise TypeError(
1639 "Implicit conversion to a host NumPy array via __array__ is not "
1640 "allowed, To explicitly construct a GPU array, consider using "
TypeError: Implicit conversion to a host NumPy array via __array__ is not allowed, To explicitly construct a GPU array, consider using cupy.asarray(...)
To explicitly construct a host array, consider using .to_array()