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ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (20,) + inhomogeneous part.

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AttributeError                            Traceback (most recent call last)
Cell In[60], line 28
     15 kwargs = dict()
     17 f, ax, barplot, bars, all_data = average_roc_curves(cv_results,
     18                                                     colors=palette,
     19                                                     model_keys=model_names,
   (...)
     25                                                     ax=ax,
     26                                                     **kwargs)
---> 28 roc_comparisons_results = roc_comparisons(cv_results, "EBM")
     30 kwargs = dict(space_between_whiskers = 0.07)
     31 order = [
     32     ("EBM", "RF"),
     33     ("EBM", "SVC"),
     34     ("EBM", "LR"),
     35     ("EBM", "KNN")
     36 ]

File ~/Workspace/Research/libraries/modelsight/src/modelsight/curves/compare.py:238, in roc_comparisons(cv_preds, target_algo)
    236 for algo_name in cv_preds.keys():
    237     if algo_name != target_algo:
--> 238         cmp = roc_single_comparison(cv_preds, target_algo, algo_name)
    239         comparisons = dict(cmp, **comparisons)
    241 return comparisons

File ~/Workspace/Research/libraries/modelsight/src/modelsight/curves/compare.py:229, in roc_single_comparison(cv_preds, fst_algo, snd_algo)
    227 print("A"*100)
    228 print(fst_algo_probas.shape, snd_algo_probas.shape)
--> 229 P = delong_roc_test(ground_truths, fst_algo_probas, snd_algo_probas)
    230 cmp_key = f"{fst_algo}_{snd_algo}"
    231 return {cmp_key: (fst_algo, snd_algo, P)}

File ~/Workspace/Research/libraries/modelsight/src/modelsight/curves/_delong.py:123, in delong_roc_test(ground_truth, predictions_one, predictions_two)
    121 order, label_1_count = compute_ground_truth_statistics(ground_truth)
    122 predictions_sorted_transposed = np.vstack((predictions_one, predictions_two))[:, order]
--> 123 aucs, delongcov = fastDeLong(predictions_sorted_transposed, label_1_count)
    124 return 10**calc_pvalue(aucs, delongcov).item()

File ~/Workspace/Research/libraries/modelsight/src/modelsight/curves/_delong.py:61, in fastDeLong(predictions_sorted_transposed, label_1_count)
     58 negative_examples = predictions_sorted_transposed[:, m:]
     59 k = predictions_sorted_transposed.shape[0]
---> 61 tx = np.empty([k, m], dtype=np.float)
     62 ty = np.empty([k, n], dtype=np.float)
     63 tz = np.empty([k, m + n], dtype=np.float)

File ~/Workspace/Research/libraries/modelsight/envs/modelsight_env/lib/python3.10/site-packages/numpy/__init__.py:319, in __getattr__(attr)
    314     warnings.warn(
    315         f"In the future `np.{attr}` will be defined as the "
    316         "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
    318 if attr in __former_attrs__:
--> 319     raise AttributeError(__former_attrs__[attr])
    321 if attr == 'testing':
    322     import numpy.testing as testing

AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations