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OpenLAM结构优化工具的使用
OpenLAM
OpenLAM
zjgemi
更新于 2024-11-20
推荐镜像 :lam-crystal-philately:openlam
推荐机型 :c12_m92_1 * NVIDIA V100
赞 1
19
5
lam-crystal-model(v3)

安装

首先将OpenLAM结构优化工具项目下载到本地

代码
文本
[1]
!git clone https://github.com/deepmodeling/openlam
Cloning into 'openlam'...
remote: Enumerating objects: 103, done.
remote: Counting objects: 100% (103/103), done.
remote: Compressing objects: 100% (73/73), done.
remote: Total 103 (delta 52), reused 68 (delta 26), pack-reused 0 (from 0)
Receiving objects: 100% (103/103), 33.91 KiB | 394.00 KiB/s, done.
Resolving deltas: 100% (52/52), done.
代码
文本

安装项目

代码
文本
[2]
!pip install ./openlam
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Processing /openlam
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... done
Collecting pydflow>=1.7.23 (from lam-crystal-philately==0.1.dev23+g7d4fc12)
  Downloading https://pypi.tuna.tsinghua.edu.cn/packages/6d/b7/2c067e6d5e7a274eb449418948d772c5cb692ddea53fbbec15c97958bb73/pydflow-1.8.85-py3-none-any.whl (163 kB)
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Collecting ase==3.22.1 (from lam-crystal-philately==0.1.dev23+g7d4fc12)
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/38/b0/3c0a7afaf66274588216c251376ac2bea0269eb7a5e1da77521811060553/ase-3.22.1-py3-none-any.whl (2.2 MB)
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Collecting pymatgen==2024.3.1 (from lam-crystal-philately==0.1.dev23+g7d4fc12)
  Using cached https://pypi.tuna.tsinghua.edu.cn/packages/73/43/f7e3b8ab721c488a8b7321012a6585977d638630e4469c8e47644982db58/pymatgen-2024.3.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.1 MB)
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Building wheels for collected packages: lam-crystal-philately
  Building wheel for lam-crystal-philately (pyproject.toml) ... done
  Created wheel for lam-crystal-philately: filename=lam_crystal_philately-0.1.dev23+g7d4fc12-py3-none-any.whl size=31517 sha256=ceed84fdf74cb619ef0c5b30c8b652f0a9001ed9f6c72316640a06768e392af2
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Successfully built lam-crystal-philately
Installing collected packages: argo-workflows, websocket-client, jsonpickle, cloudpickle, argon2-cffi-bindings, pymatgen, kubernetes, ase, argon2-cffi, minio, pydflow, lam-crystal-philately
  Attempting uninstall: pymatgen
    Found existing installation: pymatgen 2024.4.13
    Uninstalling pymatgen-2024.4.13:
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    Found existing installation: ase 3.23.0b1
    Uninstalling ase-3.23.0b1:
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Successfully installed argo-workflows-5.0.0 argon2-cffi-23.1.0 argon2-cffi-bindings-21.2.0 ase-3.22.1 cloudpickle-2.2.0 jsonpickle-3.2.2 kubernetes-30.1.0 lam-crystal-philately-0.1.dev23+g7d4fc12 minio-7.2.8 pydflow-1.8.85 pymatgen-2024.3.1 websocket-client-1.8.0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
代码
文本

DP模型已经存在于此notebook的数据集中,把它软链接到当前目录下

代码
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[1]
!ln -s /bohr/lam-crystal-model-01oe/v3/dp0529.pth dp.pth
代码
文本

本地优化结构

直接使用命令行工具在本地优化项目样例中的结构

优化结构后默认会检查优化后结构的收敛性(可以通过参数--skip-check-convergence跳过)以及在OpenLAM数据库中的是否重复(可以通过参数--skip-check-duplicate跳过),通过检查的结构会存成cif格式的文件。检查在OpenLAM数据库中是否重复需要配置环境变量BOHRIUM_ACCESS_KEY,可以通过https://bohrium.dp.tech/settings/user 页面生成access key

代码
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[20]
%env BOHRIUM_ACCESS_KEY=xxx
env: BOHRIUM_ACCESS_KEY=xxx
代码
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[6]
!lam-opt relax -i openlam/examples/data -m dp.pth -o results.json --skip-check-convergence
To get the best performance, it is recommended to adjust the number of threads by setting the environment variables OMP_NUM_THREADS, DP_INTRA_OP_PARALLELISM_THREADS, and DP_INTER_OP_PARALLELISM_THREADS. See https://deepmd.rtfd.io/parallelism/ for more information.

Start to relax structures.

Relaxing: 0it [00:00, ?it/s]      Step     Time          Energy         fmax
BFGS:    0 11:59:39       -3.432330        1.4856
BFGS:    1 11:59:42       -3.462572        1.2149
BFGS:    2 11:59:52       -3.474138        1.2986
BFGS:    3 11:59:56       -3.499632        0.2218
BFGS:    4 11:59:56       -3.500611        0.0249
BFGS:    5 11:59:56       -3.500631        0.0114
BFGS:    6 11:59:56       -3.500635        0.0110
BFGS:    7 11:59:56       -3.500739        0.0496
BFGS:    8 11:59:57       -3.500918        0.0937
BFGS:    9 11:59:57       -3.501440        0.1756
BFGS:   10 11:59:57       -3.502467        0.2799
BFGS:   11 11:59:57       -3.504224        0.3837
BFGS:   12 11:59:57       -3.540719        0.7027
BFGS:   13 11:59:57       -3.545436        0.2616
BFGS:   14 11:59:57       -3.546308        0.1420
BFGS:   15 11:59:57       -3.546664        0.0037
BFGS:   16 11:59:57       -3.546664        0.0000
Relaxing: 1it [00:22, 22.67s/it]      Step     Time          Energy         fmax
BFGS:    0 11:59:57       -5.405985        0.7214
BFGS:    1 12:00:07       -5.421183        0.7691
BFGS:    2 12:00:07       -5.421177        2.1633
BFGS:    3 12:00:07       -5.503029        0.4127
BFGS:    4 12:00:07       -5.515699        0.5083
BFGS:    5 12:00:07       -5.550243        0.5736
BFGS:    6 12:00:07       -5.302219        3.1964
BFGS:    7 12:00:08       -5.563675        0.8995
BFGS:    8 12:00:08       -5.438606        0.7443
BFGS:    9 12:00:08       -5.545653        0.3734
BFGS:   10 12:00:08       -5.563606        1.3026
BFGS:   11 12:00:08       -5.564468        0.3407
BFGS:   12 12:00:08       -5.577429        0.3208
BFGS:   13 12:00:08       -5.247499        2.8527
BFGS:   14 12:00:08       -5.588167        0.5249
BFGS:   15 12:00:08       -5.569788        0.3426
BFGS:   16 12:00:08       -5.586407        0.2904
BFGS:   17 12:00:08       -5.291737        2.2892
BFGS:   18 12:00:08       -5.568543        1.3995
BFGS:   19 12:00:09       -5.467279        0.7000
BFGS:   20 12:00:09       -5.541057        0.4039
BFGS:   21 12:00:09       -5.550354        1.7077
BFGS:   22 12:00:09       -5.561118        0.3295
BFGS:   23 12:00:09       -5.571989        0.3297
BFGS:   24 12:00:09       -5.325982        1.6277
BFGS:   25 12:00:09       -5.590947        0.4720
BFGS:   26 12:00:09       -5.559236        0.3329
BFGS:   27 12:00:09       -5.581635        0.3157
BFGS:   28 12:00:09       -5.310092        2.1232
BFGS:   29 12:00:09       -5.582313        0.9937
BFGS:   30 12:00:09       -5.460432        0.7097
BFGS:   31 12:00:10       -5.551491        0.3550
BFGS:   32 12:00:10       -5.578869        1.1455
BFGS:   33 12:00:10       -5.568943        0.3095
BFGS:   34 12:00:10       -5.579210        0.3042
BFGS:   35 12:00:10       -5.317244        1.7866
BFGS:   36 12:00:10       -5.587033        0.7966
BFGS:   37 12:00:10       -5.461176        0.7112
BFGS:   38 12:00:10       -5.559699        0.3170
BFGS:   39 12:00:10       -5.592966        0.3663
BFGS:   40 12:00:10       -5.583208        0.2907
BFGS:   41 12:00:11       -5.592933        0.1862
BFGS:   42 12:00:11       -5.545587        1.7609
BFGS:   43 12:00:11       -5.594824        0.1668
BFGS:   44 12:00:11       -5.595295        0.1689
BFGS:   45 12:00:11       -5.595634        0.1508
BFGS:   46 12:00:11       -5.595848        0.1382
BFGS:   47 12:00:11       -5.596218        0.0995
BFGS:   48 12:00:11       -5.596359        0.0997
BFGS:   49 12:00:11       -5.596817        0.1094
BFGS:   50 12:00:11       -5.597326        0.1168
BFGS:   51 12:00:11       -5.598318        0.1175
BFGS:   52 12:00:12       -5.552859        0.4600
BFGS:   53 12:00:12       -5.574159        0.7846
BFGS:   54 12:00:12       -5.588147        0.5505
BFGS:   55 12:00:12       -5.595027        0.2559
BFGS:   56 12:00:12       -5.602665        0.1604
BFGS:   57 12:00:12       -5.604079        0.0749
BFGS:   58 12:00:12       -5.604216        0.1023
BFGS:   59 12:00:12       -5.604481        0.0826
BFGS:   60 12:00:12       -5.605446        0.0526
BFGS:   61 12:00:12       -5.606199        0.0744
BFGS:   62 12:00:13       -5.605357        0.4217
BFGS:   63 12:00:13       -5.607068        0.0346
BFGS:   64 12:00:13       -5.607500        0.0342
BFGS:   65 12:00:13       -5.581688        1.1910
BFGS:   66 12:00:13       -5.607893        0.0296
BFGS:   67 12:00:13       -5.608146        0.0301
BFGS:   68 12:00:13       -5.608311        0.1705
BFGS:   69 12:00:13       -5.608587        0.0554
BFGS:   70 12:00:13       -5.608691        0.0569
BFGS:   71 12:00:13       -5.609182        0.0947
BFGS:   72 12:00:13       -5.609566        0.0651
BFGS:   73 12:00:14       -5.600396        0.7815
BFGS:   74 12:00:14       -5.612574        0.1182
BFGS:   75 12:00:14       -5.614660        0.0937
BFGS:   76 12:00:14       -5.620260        0.0549
BFGS:   77 12:00:14       -5.619484        0.1918
BFGS:   78 12:00:14       -5.620855        0.0646
BFGS:   79 12:00:14       -5.620925        0.0391
BFGS:   80 12:00:14       -5.620993        0.0274
BFGS:   81 12:00:14       -5.621018        0.0179
BFGS:   82 12:00:14       -5.621036        0.0132
BFGS:   83 12:00:14       -5.621049        0.0236
BFGS:   84 12:00:15       -5.621061        0.0309
BFGS:   85 12:00:15       -5.621082        0.0386
BFGS:   86 12:00:15       -5.621136        0.0500
BFGS:   87 12:00:15       -5.621274        0.0678
BFGS:   88 12:00:15       -5.621747        0.0900
BFGS:   89 12:00:15       -5.626878        0.1020
BFGS:   90 12:00:15       -5.626784        0.2829
BFGS:   91 12:00:15       -5.630610        0.1543
BFGS:   92 12:00:15       -5.631596        0.0634
BFGS:   93 12:00:15       -5.631780        0.0422
BFGS:   94 12:00:16       -5.631856        0.0149
BFGS:   95 12:00:16       -5.631868        0.0015
BFGS:   96 12:00:16       -5.631869        0.0004
BFGS:   97 12:00:16       -5.631869        0.0001
Relaxing: 2it [00:41, 20.62s/it]

Saved to df.

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结果文件中包含优化后的结构和能量

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[9]
!cat results.json
{"final_structure":{"MP_mp-1006815":{"@module":"pymatgen.core.structure","@class":"Structure","charge":0,"lattice":{"matrix":[[7.230147594,-0.6129705837,-0.2359834023],[-4.1459218943,7.1809473651,0.4719668046],[-0.4390057784,0.760380313,14.2020498528]],"pbc":[true,true,true],"a":7.2599211658,"b":8.3052649614,"c":14.2291645685,"alpha":83.2045861827,"beta":93.8807974416,"gamma":124.8894017167,"volume":698.8008411647},"properties":{},"sites":[{"species":[{"element":"Cs","occu":1}],"abc":[-0.0,-0.0,0.0],"xyz":[0.0,-0.0,0.0],"properties":{},"label":"Cs"},{"species":[{"element":"H","occu":1}],"abc":[-0.0,0.1209169629,0.7997949989],"xyz":[-0.8524269099,1.4764467177,11.4157972395],"properties":{},"label":"H"},{"species":[{"element":"H","occu":1}],"abc":[0.0,0.8790830371,0.2002050011],"xyz":[-3.7325007628,6.4648809604,3.258219418],"properties":{},"label":"H"}]},"MP_mp-1093779":{"@module":"pymatgen.core.structure","@class":"Structure","charge":0,"lattice":{"matrix":[[16.0670444689,-0.0,-0.0],[-0.0,14.2111,-0.0],[-0.0,-0.0,20.0251]],"pbc":[true,true,true],"a":16.0670444689,"b":14.2111,"c":20.0251,"alpha":90.0000000001,"beta":90.0,"gamma":90.0,"volume":4572.3386054619},"properties":{},"sites":[{"species":[{"element":"K","occu":1}],"abc":[0.0,0.0,0.0],"xyz":[0.0,0.0,0.0],"properties":{},"label":"K"},{"species":[{"element":"Na","occu":1}],"abc":[0.1905935253,0.5,0.5],"xyz":[3.0622746457,7.10555,10.01255],"properties":{},"label":"Na"},{"species":[{"element":"Na","occu":1}],"abc":[0.8094064747,0.5,0.5],"xyz":[13.0047698232,7.10555,10.01255],"properties":{},"label":"Na"},{"species":[{"element":"Tl","occu":1}],"abc":[0.0,0.5,0.5],"xyz":[0.0,7.10555,10.01255],"properties":{},"label":"Tl"}]}},"final_energy":{"MP_mp-1006815":-5.6318688293,"MP_mp-1093779":-3.5466640916}}
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relaxed文件夹中包含通过检查的cif文件

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[7]
!ls relaxed
final-CsH2.cif	final-KNa2Tl.cif
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提交工作流优化结构

首先新建一个工作流配置文件,优化结构后默认会检查优化后结构的收敛性(可以通过inputs中的参数"check_convergence": false跳过)以及在OpenLAM数据库中的是否重复(可以通过inputs中的参数"check_duplicate": false跳过),通过检查的结构会存成cif格式的文件。检查在OpenLAM数据库中是否重复需要配置环境变量BOHRIUM_ACCESS_KEY,可以通过https://bohrium.dp.tech/settings/user 页面生成access key

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[ ]
%env BOHRIUM_ACCESS_KEY=xxx
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[16]
%%file input.json
{
"relax": {
"inputs": {
"check_convergence": false
},
"image": "registry.dp.tech/dptech/prod-26832/lam-crystal-philately:dp-mptraj-ase-utype",
"executor": {
"image_pull_policy": "IfNotPresent",
"machine_dict": {
"batch_type": "Bohrium",
"context_type": "Bohrium",
"remote_profile": {
"input_data": {
"job_type": "container",
"platform": "ali",
"scass_type": "1 * NVIDIA T4_16g",
"maxRescheduleTimes": 10
}
}
},
"retry_on_submission_error": 10
}
}
}
Overwriting input.json
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将项目样例中的结构分到2个文件夹中,我们将用2个并行任务优化它们

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[9]
!mkdir -p part0 part1
!cp openlam/examples/data/MP_mp-1006815.cif part0
!cp openlam/examples/data/MP_mp-1093779.cif part1
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配置工作流环境变量

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[21]
%env DFLOW_HOST=https://workflows.deepmodeling.com
%env DFLOW_K8S_API_SERVER=https://workflows.deepmodeling.com
%env DFLOW_S3_REPO_KEY=oss-bohrium
%env DFLOW_S3_STORAGE_CLIENT=dflow.plugins.bohrium.TiefblueClient
%env BOHRIUM_USERNAME=xxx
%env BOHRIUM_PASSWORD=xxx
%env BOHRIUM_PROJECT_ID=xxx
env: DFLOW_HOST=https://workflows.deepmodeling.com
env: DFLOW_K8S_API_SERVER=https://workflows.deepmodeling.com
env: DFLOW_S3_REPO_KEY=oss-bohrium
env: DFLOW_S3_STORAGE_CLIENT=dflow.plugins.bohrium.TiefblueClient
env: BOHRIUM_USERNAME=xxx
env: BOHRIUM_PASSWORD=xxx
env: BOHRIUM_PROJECT_ID=xxx
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提交工作流

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[18]
!lam-opt submit input.json -i part0 part1 -m dp.pth

Workflow has been submitted (ID: parallel-relax-ghxnh, UID: d391313a-d9e5-4947-ab11-da0b7c88b13c)
Workflow link: https://workflows.deepmodeling.com/workflows/argo/parallel-relax-ghxnh
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点击工作流链接可查看工作流状态,待工作流完成后

alt

下载结果

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[19]
!lam-opt download parallel-relax-ghxnh -o outputs
!tree outputs
100%|█████████████████████████████████████████████| 5/5 [00:00<00:00,  7.92it/s]
100%|█████████████████████████████████████████████| 5/5 [00:00<00:00,  7.87it/s]
outputs
├── 0
│   ├── relaxed
│   │   └── final-CsH2.cif
│   └── results.json
└── 1
    ├── relaxed
    │   └── final-KNa2Tl.cif
    └── results.json

4 directories, 4 files
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从OpenLAM数据库查询晶体结构

配置环境变量BOHRIUM_ACCESS_KEY,可以通过https://bohrium.dp.tech/settings/user 页面生成access key

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[6]
%env BOHRIUM_ACCESS_KEY=xxx
env: BOHRIUM_ACCESS_KEY=xxx
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通过python接口查询晶体结构(query_by_page接口已经弃用,请使用query_by_offset接口)

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[4]
from lam_optimize import CrystalStructure
data = CrystalStructure.query_by_offset()
print(data)
{'nextStartId': 18, 'items': [<lam_optimize.db.CrystalStructure object at 0x7f2ed5cf8590>, <lam_optimize.db.CrystalStructure object at 0x7f2ed57e71d0>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5bb7290>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5696450>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5247810>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5628950>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5c0f650>, <lam_optimize.db.CrystalStructure object at 0x7f2ed5ba12d0>, <lam_optimize.db.CrystalStructure object at 0x7f2ed6d6ca90>, <lam_optimize.db.CrystalStructure object at 0x7f2ed4b899d0>]}
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query_by_offset方法接收以下参数作为查询条件

formula: Optional[str] = None
min_energy: Optional[float] = None
max_energy: Optional[float] = None
min_submission_time: Optional[datetime.datetime] = None
max_submission_time: Optional[datetime.datetime] = None
offset: int = 0
limit: int = 10

返回的data中除了nextStartId(作为下次查询的offset)外,itemsCrystalStructure对象的列表,该对象包含如下属性

class CrystalStructure:
    formula: str
    structure: pymatgen.core.Structure
    energy: float
    submission_time: datetime.datetime

还提供了query方法自动合并分页结果

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[5]
structures = CrystalStructure.query(formula="Sr2YSbO6")
print(structures)
[<lam_optimize.db.CrystalStructure object at 0x7f2ed5661050>, <lam_optimize.db.CrystalStructure object at 0x7f2ed54a3910>, <lam_optimize.db.CrystalStructure object at 0x7f2ed4baf850>]
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返回的是CrystalStructure对象的列表。

NOTE:不带查询条件地调用非分页方法非常慢。

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从OpenLAM数据库查询hull

配置环境变量BOHRIUM_ACCESS_KEY,可以通过https://bohrium.dp.tech/settings/user 页面生成access key

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%env BOHRIUM_ACCESS_KEY=xxx
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用Python接口通过组成元素查询hull,如果查询组成的hull在OpenLAM数据库中没有计算过会抛出RuntimeError

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from lam_optimize.utils import query_hull_by_composition
hull = query_hull_by_composition(["Ac", "Ag", "Bi", "As", "Rh", "Cl", "O"])
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你可以通过查询得到的hull计算结构高于hull的能量差

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from lam_optimize.utils import get_e_above_hull
ehull = get_e_above_hull(structure, hull, 0.123)
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{/**/}