Description
Bug summary
When training a DPA-1 neural network potential using DP-GEN (v0.13.0) with TensorFlow backend, I encountered an error related to mixed type format inconsistency in iter1. While iter0 (including training-exploration-label stages) completed successfully, the training in iter1 failed due to data format mismatch. DP-GEN should automatically convert iter0.02.fp data to mixed type format, maintaining consistency with the initial data format.
In iter1, DP-GEN uses the standard format for iter0.02.fp data instead of maintaining the mixed type format from iter0, causing a format inconsistency error.
Environment
- DP-GEN version: 0.13.0
- DeePMD-kit backend: TensorFlow
- Model type: DPA-1
- Data format: Multisystem mixed type
Error Message
AssertionError: if one of the system is of mixed_type format, then all of the systems should be of mixed_type format!
Would appreciate any guidance on resolving this issue or confirmation if this is a bug that needs to be fixed.
DP-GEN Version
0.13.0
Platform, Python Version, Remote Platform, etc
No response
Input Files, Running Commands, Error Log, etc.
No inputs.
Steps to Reproduce
- Initialize training data using multisystem mixed type dp data format
- Run iter0 (completes successfully)
- Enter iter1, where the error occurs
Further Information, Files, and Links
The error suggests that DP-GEN is not properly carrying over the mixed type format configuration from iter0 to iter1's training data.