Can arguments be passed dynamically to outer pipeline which can be used by any steps inside it?

Question

I have the following scenario:

num_cols = ["list", "of", "column", "names"]
cat_cols = ["different", "list", "of", "column", "names"]

col_transformer = ColumnTransformer([
    ('num', Scaler(), num_cols),
    ('cat', OneHotEncoder(), cat_cols)
])

pipeline = Pipeline([
    ('transformer', ColumnTransformer()),
    ('regressor', LogisticRegression())
])

Now I would like set values for num_cols and cat_cols dynamically when calling pipeline.fit().