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[BUG] Seeds of descriptor/fitting in dpmodel are not passed to network #3799
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Fix #3799. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced flexibility in specifying seed values, allowing either an integer or a list of integers. - Enhanced seed parameter usage across various initialization methods and classes for more controlled randomization. - **Improvements** - Updated seed initialization logic to include additional computations and dynamic adjustments. - Enhanced documentation for parameters in multiple classes, providing clearer usage guidelines. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Jul 3, 2024
Fix deepmodeling#3799. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> - **New Features** - Introduced flexibility in specifying seed values, allowing either an integer or a list of integers. - Enhanced seed parameter usage across various initialization methods and classes for more controlled randomization. - **Improvements** - Updated seed initialization logic to include additional computations and dynamic adjustments. - Enhanced documentation for parameters in multiple classes, providing clearer usage guidelines. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> (cherry picked from commit 0c472d1) Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Sep 18, 2024
Fix deepmodeling#3799. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced flexibility in specifying seed values, allowing either an integer or a list of integers. - Enhanced seed parameter usage across various initialization methods and classes for more controlled randomization. - **Improvements** - Updated seed initialization logic to include additional computations and dynamic adjustments. - Enhanced documentation for parameters in multiple classes, providing clearer usage guidelines. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Bug summary
Seeds of descriptor/fitting in dpmodel are not passed to network
DeePMD-kit Version
3.0.0a
Backend and its version
PyTorch v2.1.2
How did you download the software?
Built from source
Input Files, Running Commands, Error Log, etc.
See above
Steps to Reproduce
See above
Further Information, Files, and Links
No response
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