DP-GEN Auto-test
This article is based on Bohrium and takes the Al-Mg-Cu potential function in DP-Library as an example (upgraded with DeePMD-kit after downloading from DPLibrary) for property calculation.
Note: The software versions used in this tutorial: DP-GEN 0.10.6, DP-Dispatcher 0.4.16, dpdata 0.2.8.
Step 1: Prepare files and folders
First, create a new working directory, here we use a folder named autotest as an example, and put the model file you want to calculate (e.g., graph.pb) inside.
In this example, the model file needs to be upgraded to the corresponding version of dp. You can use the dp convert-from 1.1 -i graph.pb -o new_graph.pb command to upgrade the model under the DeePMD-kit image. You can view the usage of this command with dp convert-from -h.
You can rename the old model to old_graph.pb and use this script to submit jobs and recycle files in Bohrium without opening a new node, which is very convenient.
submit.json
{
"job_name": "dp-update-model",
"job_type": "container",
"image_address": "registry.dp.tech/dptech/deepmd-kit:2.1.5-cuda11.6",
"command": "dp convert-from 1.1 -i old_graph.pb -o graph.pb",
"log_file": "tmp_log",
"backward_files": ["graph.pb"],
"program_id": 0000,
"platform": "ali",
"disk_size": 200,
"machine_type": "c16_m32_cpu"
}
Note: Replace the 0000 after "project_id": with your own project ID, which can be viewed on the "Project Management" page.
Run the following commands respectively:
mkdir autotest
cd autotest
mv <the-path-where-you-download-graph.pb>/graph.pb old_graph.pb
bohr job submit -i submit.json -p ./
(If the file graph.pb is not automatically returned, you need to download it from the job management page and place it in the current autotest folder.)
Note: If your model does not require an upgrade, you only need the following command.
mkdir autotest
cd autotest
mv <the-path-where-graph.pb-is>/graph.pb graph.pb
Prepare the configuration folder and parameter files:
mkdir confs
cd confs
mkdir mp-3034
cd ..
touch relaxation.json
touch machine.json
touch property.json
In the confs folder, use the MaterialsProject configuration number mp-xxx to name the folder, and autotest will automatically download the corresponding POSCAR file from the MaterialsProject.
If you obtain the configuration through MaterialsProject, you need to configure the API key for the server.
If you use autotest without configuring the MaterialsProject API key, you will see an error like this:
(base) ➜ autotest_demo dpgen autotest make relaxation.json
NOTE: Some configuration directories are not set up yet:
/root/.gromacswrapper
/root/.gromacswrapper/qscripts
/root/.gromacswrapper/templates
NOTE: You can create the configuration file and directories with:
>>> import gromacs
>>> gromacs.config.setup()
/opt/anaconda3/lib/python3.9/site-packages/gromacs/__init__.py:286: GromacsImportWarning: Some Gromacs commands were NOT found; maybe source GMXRC first? The following are missing:
['release']
warnings.warn("Some Gromacs commands were NOT found; "
DeepModeling
------------
Version: 0.10.6
Date: Jul-11-2022
Path: /opt/anaconda3/lib/python3.9/site-packages/dpgen
Dependency
------------
numpy 1.20.3 /opt/anaconda3/lib/python3.9/site-packages/numpy
dpdata 0.2.8 /opt/anaconda3/lib/python3.9/site-packages/dpdata
pymatgen unknown version or path
monty 2022.3.12 /opt/anaconda3/lib/python3.9/site-packages/monty
ase 3.22.1 /opt/anaconda3/lib/python3.9/site-packages/ase
paramiko 2.10.3 /opt/anaconda3/lib/python3.9/site-packages/paramiko
custodian 2022.2.13 /opt/anaconda3/lib/python3.9/site-packages/custodian
Reference
------------
Please cite:
Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, and Weinan E,
DP-GEN: A concurrent learning platform for the generation of reliable deep learning
based potential energy models, Computer Physics Communications, 2020, 107206.
------------
Description
------------
You have to get a MAPI_KEY from materials.org
and execute following command:
echo "export MAPI_KEY=yourkey">> ~/.bashrc
source ~/.bashrc
Of course, you can also configure with ~ / .zshrc on Bohrium:
echo "export MAPI_KEY=yourkey">> ~/.zshrc
source ~/.zshrc
The API key for MaterialsProject can be obtained here (if you haven't registered/logged in, log in and then click this link)
If you use the
std-xxxnaming, autotest can also automatically generate the corresponding configuration. DP-GEN 0.10.6 and later versions supportstd-fcc,std-hcp,std-bcc,std-dhcp,std-diamond, andstd-sc.Of course, you can also use other naming methods, place the corresponding POSCAR file in
confs/<your-conf-name>, and then use the same steps (make-run-post).
The specific reading method of POSCAR in DP-GEN is as follows:
if len(ele_list) == 1 or 'single' in inter_param:
if 'single' in inter_param:
element_label = int(inter_param['single'])
else:
element_label = 0
for ii in conf_dirs:
os.chdir(ii)
crys_type = ii.split('/')[-1]
dlog.debug('crys_type: %s' % crys_type)
dlog.debug('pwd: %s' % os.getcwd())
if crys_type == 'std-fcc':
if not os.path.exists('POSCAR'):
crys.fcc1(ele_list[element_label]).to('POSCAR', 'POSCAR')
elif crys_type == 'std-hcp':
if not os.path.exists('POSCAR'):
crys.hcp(ele_list[element_label]).to('POSCAR', 'POSCAR')
elif crys_type == 'std-dhcp':
if not os.path.exists('POSCAR'):
crys.dhcp(ele_list[element_label]).to('POSCAR', 'POSCAR')
elif crys_type == 'std-bcc':
if not os.path.exists('POSCAR'):
crys.bcc(ele_list[element_label]).to('POSCAR', 'POSCAR')
elif crys_type == 'std-diamond':
if not os.path.exists('POSCAR'):
crys.diamond(ele_list[element_label]).to('POSCAR', 'POSCAR')
elif crys_type == 'std-sc':
if not os.path.exists('POSCAR'):
crys.sc(ele_list[element_label]).to('POSCAR', 'POSCAR')
os.chdir(cwd)
task_dirs = []
# make task directories like mp-xxx/relaxation/relax_task
# if mp-xxx/exists then print a warning and exit.
# ...
for ii in conf_dirs:
crys_type = ii.split('/')[-1]
dlog.debug('crys_type: %s' % crys_type)
if 'mp-' in crys_type and not os.path.exists(os.path.join(ii, 'POSCAR')):
get_structure(crys_type).to('POSCAR', os.path.join(ii, 'POSCAR'))
poscar = os.path.abspath(os.path.join(ii, 'POSCAR'))
The prepared files are in the folder where you want to perform autotest. For example, let's call this folder autotest. Then the files and folders you created in the above steps are: (Folder names are in bold)
autotest ── relaxation.json
|── property.json
|── machine.json
|── confs ── mp-3034
└── graph.pb
Step 2: Relaxation
In the autotest directory, first prepare the relaxation.json, which is the parameter file needed for autotest to do relaxation.
The example relaxation.json is as follows:
{
"structures": ["confs/mp-3034"],
"interaction": {
"type": "deepmd",
"model": "graph.pb",
"in_lammps": "lammps_input/in.lammps",
"type_map": {"Mg":0,"Al": 1,"Cu":2}
},
"relaxation": {
"cal_setting":{"etol": 1e-12,
"ftol": 1e-6,
"maxiter": 5000,
"maximal": 500000,
"relax_shape": true,
"relax_vol": true}
}
}
Then execute the command in the autotest directory
dpgen autotest make relaxation.json
dpgen autotest run relaxation.json machine.json
dpgen autotest post relaxation.json
Note:
- The old version of DP-GEN has a problem generating scripts in the make step, and you need to add "* *" after pair_coeff. You can add it manually or use the following command
sed -i "s/pair_coeff/pair_coeff * */g" `grep pair_coeff -rl ${_Path}/${array_mp[${i}]}
- The relaxation step only does minimization, without specifying the ensemble.
Step 3: Calculate properties
- Currently, autotest can calculate the following properties:
- EOS
- Elastic
- Vacancy
- Surface
- Interstitial
The example property.json template is as follows:
{
"structures": ["confs/mp-3034"],
"interaction": {
"type": "deepmd",
"model": "graph.pb",
"deepmd_version":"2.1.0",
"type_map": {"Mg":0,"Al": 1,"Cu":2}
},
"properties": [
{
"type": "eos",
"vol_start": 0.9,
"vol_end": 1.1,
"vol_step": 0.01,
"fix_shape":true
},
{
"type": "elastic",
"norm_deform": 2e-2,
"shear_deform": 5e-2
},
{
"type": "vacancy",
"supercell": [1, 1, 1]
},
{
"type": "interstitial",
"supercell": [3, 3, 3],
"insert_ele": ["Mg","Al","Cu"],
"conf_filters":{"min_dist": 1.5},
"cal_setting": {"input_prop": "lammps_input/lammps_high"}
},
{
"type": "surface",
"min_slab_size": 10,
"min_vacuum_size":11,
"max_miller": 1,
"cal_type": "static",
"static-opt": true,
"pert_xz":0.01,
"relax_box":false
}
]
}
Next, run the following commands in the autotest directory:
dpgen autotest make property.json
nohup dpgen autotest run property.json machine.json &
dpgen autotest post property.json
Note: In older versions of DP-GEN, there is a problem with the generated script after the "make" step. You need to add " * *" after "pair_coeff". You can either add it manually or use the following command:
sed -i "s/pair_coeff/pair_coeff * */g" `grep pair_coeff -rl ${_Path}/${array_mp[${i}]}
Step 3: Monitor job status and results
To monitor the job status, refer to Monitoring Tasks.
To obtain the results, refer to DP-GEN and Results Retrieval.
At this point, the autotest is completed, and you can view the results in the confs/mp-3034/<property-name> folder's result file. For example, in this case, the eos result can be found in confs/mp-3034/eos_00/result.out.