param_candidates = [
    {
        'C': [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 3, 5, 10, 20, 30, 100],
        'gamma': [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 3, 5, 10, 20, 30, 100],
        'kernel': ['rbf']
    }
]

clf = model_selection.GridSearchCV(
    estimator=CustomEstimator(),
    param_grid=param_candidates,
    cv=5,
    refit=True,
    error_score=0,
    n_jobs=-1
)

from sklearn import base
from sklearn import model_selection
from sklearn import ensemble

class CustomEstimator(base.BaseEstimator):
    def __init__(self):
        pass

    def fit(self, X, y=None, **params):
        return self

    def score(self, X, y=None):
        # Here how can i got the param_candidates?
        pass