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Provide support for machine learning (ML) force field in OpenMM DMFF plugin. Present version does not yet support well, such as EANN and SGNN models.
Motivation
The OpenMM DMFF plugin uses save_dmff2tf.py script to transform a JAX model trained in DMFF to a tensorflow model used for OpenMM simulations. In this module, both classical and ADMP force field are considered. While the usage of ML force field in ther transformation is not clear. If ML force field are defined in XML file (referenced as https://github.com/deepmodeling/DMFF/blob/master/docs/user_guide/4.4MLForce.md), there will occur errors in running save_dmff2tf.py script (detailed error message can be browsed in Further Information part). The used ML models are EANN and SGNN.
Suggested Solutions
Revise the potential generation function when using ML, and consider the situation of using ADMP and ML simultaneously.
Provide a specific instruction for the usage of ML forces in OpenMM DMFF Plugin docs.
Further Information, Files, and Links
reportbug.zip test.zip
Above files record two different errors when using ML in this plugin.
The text was updated successfully, but these errors were encountered:
Summary
Provide support for machine learning (ML) force field in OpenMM DMFF plugin. Present version does not yet support well, such as EANN and SGNN models.
Motivation
The OpenMM DMFF plugin uses save_dmff2tf.py script to transform a JAX model trained in DMFF to a tensorflow model used for OpenMM simulations. In this module, both classical and ADMP force field are considered. While the usage of ML force field in ther transformation is not clear. If ML force field are defined in XML file (referenced as https://github.com/deepmodeling/DMFF/blob/master/docs/user_guide/4.4MLForce.md), there will occur errors in running save_dmff2tf.py script (detailed error message can be browsed in Further Information part). The used ML models are EANN and SGNN.
Suggested Solutions
Further Information, Files, and Links
reportbug.zip
test.zip
Above files record two different errors when using ML in this plugin.
The text was updated successfully, but these errors were encountered: