[Python] grid_search.fit() report exception with RAPIDS api

Got exceptions from the code. Develop enviroment is: win10, WSL2, RAPIDS 24.02. Please help to check. I have puzzled for long time.

Implicit conversion to a host NumPy array via array is not allowed, To explicitly construct a GPU matrix, consider using .to_cupy() To explicitly construct a host matrix, consider using .to_numpy().
​

import cudf
import cupy as cp
import numpy as np
from cuml.datasets import make_classification
from cuml.svm import SVC
from cuml.preprocessing import StandardScaler
from cuml.model_selection import GridSearchCV

# Set seeds
cp.random.seed(42)
np.random.seed(42)

# Generate synthetic classification dataset (CuPy format)
X_cupy, y_cupy = make_classification(n_samples=500, n_features=10,
n_informative=5, n_classes=2,
random_state=42)

# Convert to cuDF directly without using .asnumpy()
X_cudf = cudf.DataFrame({f'feat_{i}': X_cupy[:, i] for i in range(X_cupy.shape[1])})
y_cudf = cudf.Series(y_cupy)

# Use cuML StandardScaler (keeps everything on GPU)
scaler = StandardScaler()
X_scaled = scaler.fit_transform(X_cudf) # stays cuDF

# Define cuML SVC
svc = SVC(class_weight='balanced')

# Define parameter grid
param_grid = {
'C': [0.1, 1.0],
'gamma': ['scale', 0.1],
'kernel': ['rbf']
}

# cuML GridSearchCV — must use cuDF input only
grid_search = GridSearchCV(
estimator=svc,
param_grid=param_grid,
cv=3,
scoring='accuracy',
verbose=2
)

# Fit the grid search using cuDF inputs only
grid_search.fit(X_scaled, y_cudf)

# Print best result
print("✅ Best Parameters:", grid_search.best_params_)
print("✅ Best Score:", grid_search.best_score_)

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