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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fix_multiclass_predict_proba(y_proba, # type: np.ndarray seen_classes, complete_classes ):
 """ Add missing columns to predict_proba result. When a multiclass classifier is fit on a dataset which only contains a subset of possible classes its predict_proba result only has columns corresponding to seen classes. This function adds missing columns. """

    assert set(complete_classes) >= set(seen_classes)
    y_proba_fixed = np.zeros(
        shape=(y_proba.shape[0], len(complete_classes)),
        dtype=y_proba.dtype,
    )
    class_mapping = np.searchsorted(complete_classes, seen_classes)
    y_proba_fixed[:, class_mapping] = y_proba
    return y_proba_fixed