Regression example not working AttributeError: 'DataFrame' object has no attribute 'flatten'

The error point out the fit line `reg.fit(X_train, y_train)`
Even when I try toforce to numpy array `reg.fit(X_train.to_numpy(), y_train.to_numpy())` It does not fix it, same error

`/usr/local/lib/python3.12/dist-packages/sklearn/preprocessing/_function_transformer.py:311: UserWarning: When `set_output` is configured to be 'pandas', `func` should return a pandas DataFrame to follow the `set_output` API or `feature_names_out` should be defined.
warnings.warn(warn_msg.format("pandas"))
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
[/tmp/ipykernel_910/3021392855.py](https://localhost:8080/#) in ()
28 # Fit and Predict
29 # Pass y_train and X_train as numpy arrays to ensure consistent behavior with internal reshape and scaler
---> 30 reg.fit(X_train.to_numpy(), y_train.to_numpy())
31 predictions = reg.predict(X_test)
32

1 frames
[/usr/local/lib/python3.12/dist-packages/pandas/core/generic.py](https://localhost:8080/#) in __getattr__(self, name)
6297 ):
6298 return self[name]
-> 6299 return object.__getattribute__(self, name)
6300
6301 @final

AttributeError: 'DataFrame' object has no attribute 'flatten'`

Start with the regression example around the reported `reg.fit(X_train, y_train)` line and reproduce the traceback using the shown NumPy conversion. Inspect the scikit-learn FunctionTransformer warning and the surrounding preprocessing inputs to identify where a DataFrame reaches `flatten`; done means the example fits and predicts without the AttributeError.

Written by the indexing model from the issue text.