[-]boost python notes

本文深入探讨了面向对象编程中的调用策略和多态性概念,解释了如何通过调用策略实现不同行为,以及多态性在提升代码复用性和灵活性中的作用。

I’ve known the basics under the hood, next step:

  • Call Policies
  • Polymophism
Traceback (most recent call last): File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\src\models\catboost_info\2.py", line 1511, in <module> main() File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\src\models\catboost_info\2.py", line 1464, in main cl_position_results = process_single_cl_position_v2( File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\src\models\catboost_info\2.py", line 1298, in process_single_cl_position_v2 model_pipeline, train_time, metrics, cv_results, best_params = train_single_model_v3( File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\src\models\catboost_info\2.py", line 818, in train_single_model_v3 optimized_params = bayesian_optimization_for_model( File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\src\models\catboost_info\2.py", line 451, in bayesian_optimization_for_model optimizer = BayesianOptimization( File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\.venv\lib\site-packages\bayes_opt\bayesian_optimization.py", line 73, in __init__ self._space = TargetSpace(f, pbounds, random_state) File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\.venv\lib\site-packages\bayes_opt\target_space.py", line 49, in __init__ dtype=np.float File "E:\01.KT\02.Python code\kt_data_code\01.inrush_current_project\.venv\lib\site-packages\numpy\__init__.py", line 305, in __getattr__ raise AttributeError(__former_attrs__[attr]) 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
最新发布
12-19
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