ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (9,) + inhomogeneous part.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[46], line 26
     11 spline_reg_pipe = sklearn.pipeline.make_pipeline(
     12             sklearn.preprocessing.SplineTransformer(extrapolation="periodic"), 
     13             sklearn.linear_model.LinearRegression(fit_intercept=False)
     14             )
     16 spline_reg_pipe_cv = sklearn.model_selection.GridSearchCV(
     17     estimator=spline_reg_pipe,
     18     param_grid={
   (...)
     23     verbose=1
     24 )
---> 26 spline_reg_pipe_cv.fit(X=x_train, y=y_train_noise)
     28 plt.scatter(x_train, y_train_noise, s=1, label='noisy data')
     29 plt.plot(x, y_true, label='truth')

File ~/Library/Python/3.12/lib/python/site-packages/sklearn/base.py:1473, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs)
   1466     estimator._validate_params()
   1468 with config_context(
   1469     skip_parameter_validation=(
   1470         prefer_skip_nested_validation or global_skip_validation
   1471     )
   1472 ):
-> 1473     return fit_method(estimator, *args, **kwargs)

File ~/Library/Python/3.12/lib/python/site-packages/sklearn/model_selection/_search.py:968, in BaseSearchCV.fit(self, X, y, **params)
    962     results = self._format_results(
    963         all_candidate_params, n_splits, all_out, all_more_results
    964     )
    966     return results
--> 968 self._run_search(evaluate_candidates)
    970 # multimetric is determined here because in the case of a callable
    971 # self.scoring the return type is only known after calling
    972 first_test_score = all_out[0]["test_scores"]

File ~/Library/Python/3.12/lib/python/site-packages/sklearn/model_selection/_search.py:1543, in GridSearchCV._run_search(self, evaluate_candidates)
   1541 def _run_search(self, evaluate_candidates):
   1542     """Search all candidates in param_grid"""
-> 1543     evaluate_candidates(ParameterGrid(self.param_grid))

File ~/Library/Python/3.12/lib/python/site-packages/sklearn/model_selection/_search.py:962, in BaseSearchCV.fit.<locals>.evaluate_candidates(candidate_params, cv, more_results)
    959         all_more_results[key].extend(value)
    961 nonlocal results
--> 962 results = self._format_results(
    963     all_candidate_params, n_splits, all_out, all_more_results
    964 )
    966 return results

File ~/Library/Python/3.12/lib/python/site-packages/sklearn/model_selection/_search.py:1098, in BaseSearchCV._format_results(self, candidate_params, n_splits, out, more_results)
   1094     arr_dtype = object
   1095 if len(param_list) == n_candidates and arr_dtype != object:
   1096     # Exclude `object` else the numpy constructor might infer a list of
   1097     # tuples to be a 2d array.
-> 1098     results[key] = MaskedArray(param_list, mask=False, dtype=arr_dtype)
   1099 else:
   1100     # Use one MaskedArray and mask all the places where the param is not
   1101     # applicable for that candidate (which may not contain all the params).
   1102     ma = MaskedArray(np.empty(n_candidates), mask=True, dtype=arr_dtype)

File ~/Library/Python/3.12/lib/python/site-packages/numpy/ma/core.py:2820, in MaskedArray.__new__(cls, data, mask, dtype, copy, subok, ndmin, fill_value, keep_mask, hard_mask, shrink, order)
   2811 """
   2812 Create a new masked array from scratch.
   2813 
   (...)
   2817 
   2818 """
   2819 # Process data.
-> 2820 _data = np.array(data, dtype=dtype, copy=copy,
   2821                  order=order, subok=True, ndmin=ndmin)
   2822 _baseclass = getattr(data, '_baseclass', type(_data))
   2823 # Check that we're not erasing the mask.

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (9,) + inhomogeneous part.