Make ModelManager import more robust

[AMOOOMA]

Found out some inconvenience when testing and debugging what packages is missing when ModelManager import failed. This change should help a lot for ease of use instead of getting a vague error thrown.

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Summary of Changes

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This pull request improves the robustness of the ModelManager import process within the Apache Beam ML inference module. By replacing a silent failure with a descriptive error message, it simplifies debugging for users when required dependencies are missing, while maintaining the flexibility of ModelManager as an optional component.

Highlights

• Improved Error Handling: Introduced a helper function _try_import_model_manager to provide clearer error messages when the optional ModelManager dependency is missing.
• Lazy Loading Logic: Refactored the import process to handle ModelManager as an optional dependency globally, while enforcing its presence only when explicitly required by the code path.

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Code Review

This pull request refactors the import of ModelManager in sdks/python/apache_beam/ml/inference/base.py to handle it as an optional dependency, introducing a helper function _try_import_model_manager for dynamic imports. The review feedback highlights a grammatical typo in the error message and a PEP 8 violation where a local variable shadows the global ModelManager name, suggesting a rename to model_manager_cls.

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