Comments (2)
For the first point, it is quite easy to put the machine-related configurations together or in a separate file, in my opinion, this is a minor point.
For the second point, dpgen2 uses dargs for configuration checks and validation as well as automatic documentation generation (please refer to https://docs.deepmodeling.com/projects/dargs/en/stable/#https://), which can play a role similar to pydantic and support some custom features. Is there anything that does not meet your requirements?
For the third point, dpgen2 supports multiple datasets using different lammps input templates during the configuration exploration phase. E.g.
"configurations": [
{
"type": "alloy",
"lattice" : ["fcc", 4.57],
"replicate" : [2, 2, 2],
"numb_confs" : 30,
"concentration" : [[1.0, 0.0], [0.5, 0.5], [0.0, 1.0]]
},
{
"type" : "file",
"prefix": "/file/prefix",
"files" : ["relpath/to/confs/*"],
"fmt" : "deepmd/npy"
}
],
"stages": [
[
{
"_comment" : "stage 0, task group 0",
"type" : "lmp-md",
"ensemble": "nvt", "nsteps": 50, "temps": [50, 100], "trj_freq": 10,
"conf_idx": [0], "n_sample" : 3
},
{
"_comment" : "stage 0, task group 1",
"type" : "lmp-template",
"lmp" : "template.lammps", "plm" : "template.plumed",
"trj_freq" : 10, "revisions" : {"V_NSTEPS" : [40], "V_TEMP" : [150, 200]},
"conf_idx": [0], "n_sample" : 3
}
],
[
{
"_comment" : "stage 1, task group 0",
"type" : "lmp-md",
"ensemble": "npt", "nsteps": 50, "press": [1e0], "temps": [50, 100, 200], "trj_freq": 10,
"conf_idx": [1], "n_sample" : 3
}
]
]
Here, you can use different LAMMPS template files for different conf_idx
. Is there anything that does not meet your requirements?
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Hi @zjgemi It is not only system-wise LAMMPS configuration is required, but also CP2K. You may check the detail in the pseudo configuration.
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Related Issues (20)
- System.from does not suppot the mixed_type data
- dpgen2 can not support CP2K HOT 1
- Support different backends for DeePMD-kit
- Does dpgen2 support use in HPC? HOT 1
- how to set group_size in run_train_config? HOT 2
- dpgen2 showkey seems not work at debug mode HOT 2
- [BUG] Using DPGEN2 combines DPA2 model and first-princeple calculation(VASP) to label the alloy data, iteration 0 is normal, but iteration 1 is abnormal HOT 4
- Request for new features: stage-specific parameters for explore and fp, finetune/iter-initial-modle distinguishing training parameters HOT 1
- set input.json/train/numb_models = 1 may cause path errors HOT 1
- dpgen2如何直接使用slurm构建input.json HOT 1
- User interface for downloading resultant files.
- User interface for resubmitting workflow HOT 1
- Use dargs to parse the input files. HOT 1
- implement more OPs and workflows HOT 2
- CH4 example needs update HOT 3
- read the doc for dpgen2 HOT 2
- skip the training in the first iteration
- Inpurt script switches to json5 format HOT 1
- Implement Gaussian
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