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| # 仅在scheduler中启动定时任务，dev local_model celery 不需要 | ||
| if os.environ.get('ENABLE_SCHEDULER') == '1': | ||
| post_scheduler_handler() No newline at end of file | ||
| post_scheduler_handler() |
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No significant issues were found in the provided code. The changes made to intercept and disable imports of popular machine learning libraries like torch could potentially be beneficial in environments where these should not be used due to security concerns, performance penalties, or dependency conflicts with other applications running on the same system.
However, please note that this change may require adjustments depending on whether you want certain parts of your Django app (e.g., using PyTorch modules directly during development) to work without restrictions imposed by this interceptor. You will also need ensure compatibility across different versions and configurations of software dependencies. Finally, consider documenting the impact of this change within your project documentation for users who might use it.
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fix: dependency package