Spaces:
Running
Running
add eos notebook
Browse files- .github/workflows/test.yaml +3 -0
- mlip_arena/tasks/combustion/H256O128.extxyz +384 -384
- mlip_arena/tasks/combustion/water.ipynb +100 -126
- mlip_arena/tasks/eos/run.ipynb +645 -0
- mlip_arena/tasks/eos/run.py +39 -11
- mlip_arena/tasks/optimize.py +5 -1
- tests/test_eos.py +1 -1
.github/workflows/test.yaml
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pip install "pynanoflann@git+https://github.com/dwastberg/pynanoflann#egg=af434039ae14bedcbb838a7808924d6689274168"
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- name: Run tests
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run: |
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pytest -v tests
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pip install "pynanoflann@git+https://github.com/dwastberg/pynanoflann#egg=af434039ae14bedcbb838a7808924d6689274168"
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- name: Run tests
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env:
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PREFECT_API_KEY: ${{ secrets.PREFECT_API_KEY }}
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PREFECT_API_URL: ${{ secrets.PREFECT_API_URL }}
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run: |
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pytest -v tests
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mlip_arena/tasks/combustion/H256O128.extxyz
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Lattice="30.0 0.0 0.0 0.0 30.0 0.0 0.0 0.0 30.0" Properties=species:S:1:pos:R:3 Built=T with=T Packmol=T pbc="T T T"
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Lattice="30.0 0.0 0.0 0.0 30.0 0.0 0.0 0.0 30.0" Properties=species:S:1:pos:R:3 Built=T with=T Packmol=T pbc="T T T"
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H 16.87897000 14.36340900 5.78639500
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O 22.63711100 1.37775300 19.58937200
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O 23.87485500 1.47510200 19.48488400
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O 24.56301300 18.58751900 21.22319300
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O 23.67458500 19.30549400 20.72558500
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O 8.94762000 14.49730700 12.31189400
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O 8.63504700 19.77961300 8.44117000
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O 27.39479700 24.64841500 9.77024200
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mlip_arena/tasks/combustion/water.ipynb
CHANGED
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"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n",
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" traj_file=Path(REGISTRY[model.name][\"family\"])\n",
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"14:50:51.449 | \u001b[36mINFO\u001b[0m | prefect.engine - Created flow run\u001b[35m 'liberal-beetle'\u001b[0m for flow\u001b[1;35m 'combustion'\u001b[0m\n"
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">14:50:51.453 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | Flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'liberal-beetle'</span> - View at <span style=\"color: #0000ff; text-decoration-color: #0000ff\">https://app.prefect.cloud/account/f7d40474-9362-4bfa-8950-ee6a43ec00f3/workspace/d4bb0913-5f5e-49f7-bfc5-06509088baeb/flow-runs/flow-run/4803afc0-0472-4cf3-8d76-794fc218e2c3</span>\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 52, in get_call_parameters\n",
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-
" raise ParameterBindError.from_bind_failure(fn, exc, call_args, call_kwargs)\n",
|
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-
"prefect.exceptions.ParameterBindError: Error binding parameters for function 'run': got an unexpected keyword argument 'mb_velocity_seed'.\n",
|
| 360 |
-
"Function 'run' has signature 'atoms: 'Atoms', calculator_name: 'str | MLIPEnum', calculator_kwargs: 'dict | None', dispersion: 'str | None' = None, dispersion_kwargs: 'dict | None' = None, device: 'str | None' = None, ensemble: \"Literal['nve', 'nvt', 'npt']\" = 'nvt', dynamics: 'str | MolecularDynamics' = 'langevin', time_step: 'float | None' = None, total_time: 'float' = 1000, temperature: 'float | Sequence | np.ndarray | None' = 300.0, pressure: 'float | Sequence | np.ndarray | None' = None, ase_md_kwargs: 'dict | None' = None, md_velocity_seed: 'int | None' = None, zero_linear_momentum: 'bool' = True, zero_angular_momentum: 'bool' = True, traj_file: 'str | Path | None' = None, traj_interval: 'int' = 1, restart: 'bool' = True' but received args: () and kwargs: ['atoms', 'calculator_name', 'calculator_kwargs', 'ensemble', 'dynamics', 'time_step', 'ase_md_kwargs', 'total_time', 'temperature', 'pressure', 'mb_velocity_seed', 'traj_file', 'traj_interval', 'restart'].\n",
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],
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-
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-
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 50, in get_call_parameters\n",
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" bound_signature = inspect.signature(fn).bind(*call_args, **call_kwargs)\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/inspect.py\", line 3212, in bind\n",
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" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/inspect.py\", line 3201, in _bind\n",
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"Traceback (most recent call last):\n",
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{
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"evalue": "
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/
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-
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/
|
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-
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/
|
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-
"
|
| 438 |
-
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/engine.py:400\u001b[0m, in \u001b[0;36mcreate_then_begin_flow_run\u001b[0;34m(flow, parameters, wait_for, return_type, client, user_thread)\u001b[0m\n\u001b[1;32m 398\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m state\n\u001b[1;32m 399\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m return_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresult\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 400\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m state\u001b[38;5;241m.\u001b[39mresult(fetch\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 401\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 402\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid return type for flow engine \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mreturn_type\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/states.py:91\u001b[0m, in \u001b[0;36m_get_state_result\u001b[0;34m(state, raise_on_failure)\u001b[0m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnfinishedRun(\n\u001b[1;32m 85\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRun is in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstate\u001b[38;5;241m.\u001b[39mtype\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m state, its result is not available.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 86\u001b[0m )\n\u001b[1;32m 88\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raise_on_failure \u001b[38;5;129;01mand\u001b[39;00m (\n\u001b[1;32m 89\u001b[0m state\u001b[38;5;241m.\u001b[39mis_crashed() \u001b[38;5;129;01mor\u001b[39;00m state\u001b[38;5;241m.\u001b[39mis_failed() \u001b[38;5;129;01mor\u001b[39;00m state\u001b[38;5;241m.\u001b[39mis_cancelled()\n\u001b[1;32m 90\u001b[0m ):\n\u001b[0;32m---> 91\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m get_state_exception(state)\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(state\u001b[38;5;241m.\u001b[39mdata, DataDocument):\n\u001b[1;32m 94\u001b[0m result \u001b[38;5;241m=\u001b[39m result_from_state_with_data_document(\n\u001b[1;32m 95\u001b[0m state, raise_on_failure\u001b[38;5;241m=\u001b[39mraise_on_failure\n\u001b[1;32m 96\u001b[0m )\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/engine.py:867\u001b[0m, in \u001b[0;36morchestrate_flow_run\u001b[0;34m(flow, flow_run, parameters, wait_for, interruptible, client, partial_flow_run_context, user_thread)\u001b[0m\n\u001b[1;32m 862\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 863\u001b[0m from_async\u001b[38;5;241m.\u001b[39mcall_soon_in_new_thread(\n\u001b[1;32m 864\u001b[0m flow_call, timeout\u001b[38;5;241m=\u001b[39mflow\u001b[38;5;241m.\u001b[39mtimeout_seconds\n\u001b[1;32m 865\u001b[0m )\n\u001b[0;32m--> 867\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m flow_call\u001b[38;5;241m.\u001b[39maresult()\n\u001b[1;32m 869\u001b[0m waited_for_task_runs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m wait_for_task_runs_and_report_crashes(\n\u001b[1;32m 870\u001b[0m flow_run_context\u001b[38;5;241m.\u001b[39mtask_run_futures, client\u001b[38;5;241m=\u001b[39mclient\n\u001b[1;32m 871\u001b[0m )\n\u001b[1;32m 872\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m PausedRun \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 873\u001b[0m \u001b[38;5;66;03m# could get raised either via utility or by returning Paused from a task run\u001b[39;00m\n\u001b[1;32m 874\u001b[0m \u001b[38;5;66;03m# if a task run pauses, we set its state as the flow's state\u001b[39;00m\n\u001b[1;32m 875\u001b[0m \u001b[38;5;66;03m# to preserve reschedule and timeout behavior\u001b[39;00m\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py:327\u001b[0m, in \u001b[0;36mCall.aresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 322\u001b[0m \u001b[38;5;124;03mWait for the result of the call.\u001b[39;00m\n\u001b[1;32m 323\u001b[0m \n\u001b[1;32m 324\u001b[0m \u001b[38;5;124;03mFor use from asynchronous contexts.\u001b[39;00m\n\u001b[1;32m 325\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 326\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 327\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m asyncio\u001b[38;5;241m.\u001b[39mwrap_future(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfuture)\n\u001b[1;32m 328\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m asyncio\u001b[38;5;241m.\u001b[39mCancelledError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 329\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CancelledError() \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mexc\u001b[39;00m\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py:352\u001b[0m, in \u001b[0;36mCall._run_sync\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 350\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfuture\u001b[38;5;241m.\u001b[39menforce_sync_deadline() \u001b[38;5;28;01mas\u001b[39;00m cancel_scope:\n\u001b[1;32m 351\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 352\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 353\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 354\u001b[0m \u001b[38;5;66;03m# Forget this call's arguments in order to free up any memory\u001b[39;00m\n\u001b[1;32m 355\u001b[0m \u001b[38;5;66;03m# that may be referenced by them; after a call has happened,\u001b[39;00m\n\u001b[1;32m 356\u001b[0m \u001b[38;5;66;03m# there's no need to keep a reference to them\u001b[39;00m\n\u001b[1;32m 357\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
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"Cell \u001b[0;32mIn[6], line 6\u001b[0m, in \u001b[0;36mcombustion\u001b[0;34m(atoms)\u001b[0m\n\u001b[1;32m 3\u001b[0m futures \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m model \u001b[38;5;129;01min\u001b[39;00m MLIPEnum:\n\u001b[0;32m----> 6\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[43mMD\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43matoms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43matoms\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mcalculator_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mcalculator_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mensemble\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnvt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mdynamics\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnose-hoover\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43mtime_step\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[43mase_md_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mttime\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m25\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43munits\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpfactor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 14\u001b[0m \u001b[43m \u001b[49m\u001b[43mtotal_time\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1000_000\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m300\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m300\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m \u001b[49m\u001b[43mpressure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 17\u001b[0m \u001b[43m \u001b[49m\u001b[43mmb_velocity_seed\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[43m \u001b[49m\u001b[43mtraj_file\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mPath\u001b[49m\u001b[43m(\u001b[49m\u001b[43mREGISTRY\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfamily\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 19\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43matoms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_chemical_formula\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m.traj\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 20\u001b[0m \u001b[43m \u001b[49m\u001b[43mtraj_interval\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1000\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 21\u001b[0m \u001b[43m \u001b[49m\u001b[43mrestart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 22\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 24\u001b[0m futures\u001b[38;5;241m.\u001b[39mappend(future)\n\u001b[1;32m 26\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [future\u001b[38;5;241m.\u001b[39mresult() \u001b[38;5;28;01mfor\u001b[39;00m future \u001b[38;5;129;01min\u001b[39;00m futures]\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/tasks.py:811\u001b[0m, in \u001b[0;36mTask.submit\u001b[0;34m(self, return_state, wait_for, *args, **kwargs)\u001b[0m\n\u001b[1;32m 808\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mprefect\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mengine\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m create_autonomous_task_run, enter_task_run_engine\n\u001b[1;32m 810\u001b[0m \u001b[38;5;66;03m# Convert the call args/kwargs to a parameter dict\u001b[39;00m\n\u001b[0;32m--> 811\u001b[0m parameters \u001b[38;5;241m=\u001b[39m \u001b[43mget_call_parameters\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 812\u001b[0m return_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m return_state \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfuture\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 814\u001b[0m task_viz_tracker \u001b[38;5;241m=\u001b[39m get_task_viz_tracker()\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py:52\u001b[0m, in \u001b[0;36mget_call_parameters\u001b[0;34m(fn, call_args, call_kwargs, apply_defaults)\u001b[0m\n\u001b[1;32m 50\u001b[0m bound_signature \u001b[38;5;241m=\u001b[39m inspect\u001b[38;5;241m.\u001b[39msignature(fn)\u001b[38;5;241m.\u001b[39mbind(\u001b[38;5;241m*\u001b[39mcall_args, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcall_kwargs)\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[0;32m---> 52\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ParameterBindError\u001b[38;5;241m.\u001b[39mfrom_bind_failure(fn, exc, call_args, call_kwargs)\n\u001b[1;32m 54\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m apply_defaults:\n\u001b[1;32m 55\u001b[0m bound_signature\u001b[38;5;241m.\u001b[39mapply_defaults()\n",
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| 446 |
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"\u001b[0;31mParameterBindError\u001b[0m: Error binding parameters for function 'run': got an unexpected keyword argument 'mb_velocity_seed'.\nFunction 'run' has signature 'atoms: 'Atoms', calculator_name: 'str | MLIPEnum', calculator_kwargs: 'dict | None', dispersion: 'str | None' = None, dispersion_kwargs: 'dict | None' = None, device: 'str | None' = None, ensemble: \"Literal['nve', 'nvt', 'npt']\" = 'nvt', dynamics: 'str | MolecularDynamics' = 'langevin', time_step: 'float | None' = None, total_time: 'float' = 1000, temperature: 'float | Sequence | np.ndarray | None' = 300.0, pressure: 'float | Sequence | np.ndarray | None' = None, ase_md_kwargs: 'dict | None' = None, md_velocity_seed: 'int | None' = None, zero_linear_momentum: 'bool' = True, zero_angular_momentum: 'bool' = True, traj_file: 'str | Path | None' = None, traj_interval: 'int' = 1, restart: 'bool' = True' but received args: () and kwargs: ['atoms', 'calculator_name', 'calculator_kwargs', 'ensemble', 'dynamics', 'time_step', 'ase_md_kwargs', 'total_time', 'temperature', 'pressure', 'mb_velocity_seed', 'traj_file', 'traj_interval', 'restart']."
|
| 447 |
]
|
| 448 |
}
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| 449 |
],
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| 34 |
},
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{
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"cell_type": "code",
|
| 37 |
+
"execution_count": 3,
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| 38 |
"metadata": {},
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"outputs": [],
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| 40 |
"source": [
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| 49 |
},
|
| 50 |
{
|
| 51 |
"cell_type": "code",
|
| 52 |
+
"execution_count": 4,
|
| 53 |
"metadata": {},
|
| 54 |
"outputs": [],
|
| 55 |
"source": [
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| 60 |
},
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| 61 |
{
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"cell_type": "code",
|
| 63 |
+
"execution_count": 5,
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| 64 |
"metadata": {},
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| 65 |
"outputs": [],
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"source": [
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},
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{
|
| 80 |
"cell_type": "code",
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| 81 |
+
"execution_count": 6,
|
| 82 |
"metadata": {},
|
| 83 |
+
"outputs": [
|
| 84 |
+
{
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| 85 |
+
"name": "stdout",
|
| 86 |
+
"output_type": "stream",
|
| 87 |
+
"text": [
|
| 88 |
+
"Atoms(symbols='H256O128', pbc=True, cell=[30.0, 30.0, 30.0])\n"
|
| 89 |
+
]
|
| 90 |
+
}
|
| 91 |
+
],
|
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"source": [
|
| 93 |
"tolerance = 2.0\n",
|
| 94 |
"input_gen = PackmolBoxGen(\n",
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},
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| 145 |
{
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"cell_type": "code",
|
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+
"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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| 163 |
"source ~/.bashrc\n",
|
| 164 |
"module load python\n",
|
| 165 |
"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\n",
|
| 166 |
+
"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/bin/python -m distributed.cli.dask_worker tcp://128.55.64.19:39737 --name dummy-name --nthreads 1 --memory-limit 59.60GiB --nanny --death-timeout 60\n",
|
| 167 |
"\n"
|
| 168 |
]
|
| 169 |
},
|
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"text": [
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"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n",
|
| 175 |
"Perhaps you already have a cluster running?\n",
|
| 176 |
+
"Hosting the HTTP server on port 38693 instead\n",
|
| 177 |
+
" warnings.warn(\n",
|
| 178 |
+
"2024-10-08 03:30:05,696 - distributed.scheduler - ERROR - Task run-b8e0881eb1e8959f855ada9515884ada marked as failed because 4 workers died while trying to run it\n",
|
| 179 |
+
"2024-10-08 03:30:05,723 - distributed.scheduler - ERROR - Task run-3307095fc41590db704148cc499bad14 marked as failed because 4 workers died while trying to run it\n"
|
| 180 |
]
|
| 181 |
}
|
| 182 |
],
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},
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{
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"cell_type": "code",
|
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+
"execution_count": 4,
|
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"metadata": {},
|
| 245 |
"outputs": [],
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"source": [
|
|
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| 260 |
" total_time=1000_000,\n",
|
| 261 |
" temperature=[300, 3000, 3000, 300],\n",
|
| 262 |
" pressure=None,\n",
|
| 263 |
+
" md_velocity_seed=0,\n",
|
| 264 |
" traj_file=Path(REGISTRY[model.name][\"family\"])\n",
|
| 265 |
" / f\"{model.name}_{atoms.get_chemical_formula()}.traj\",\n",
|
| 266 |
" traj_interval=1000,\n",
|
|
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| 274 |
},
|
| 275 |
{
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"cell_type": "code",
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+
"execution_count": 5,
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"metadata": {
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"tags": []
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},
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{
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">01:25:41.097 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.engine - Created flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'green-turaco'</span> for flow<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> 'combustion'</span>\n",
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],
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"text/plain": [
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+
"01:25:41.097 | \u001b[36mINFO\u001b[0m | prefect.engine - Created flow run\u001b[35m 'green-turaco'\u001b[0m for flow\u001b[1;35m 'combustion'\u001b[0m\n"
|
| 290 |
]
|
| 291 |
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{
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+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">01:25:41.101 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.engine - View at <span style=\"color: #0000ff; text-decoration-color: #0000ff\">https://app.prefect.cloud/account/f7d40474-9362-4bfa-8950-ee6a43ec00f3/workspace/d4bb0913-5f5e-49f7-bfc5-06509088baeb/runs/flow-run/784dc0e0-9f4f-4320-8bfa-4c5e8d3b35fb</span>\n",
|
| 299 |
"</pre>\n"
|
| 300 |
],
|
| 301 |
"text/plain": [
|
| 302 |
+
"01:25:41.101 | \u001b[36mINFO\u001b[0m | prefect.engine - View at \u001b[94mhttps://app.prefect.cloud/account/f7d40474-9362-4bfa-8950-ee6a43ec00f3/workspace/d4bb0913-5f5e-49f7-bfc5-06509088baeb/runs/flow-run/784dc0e0-9f4f-4320-8bfa-4c5e8d3b35fb\u001b[0m\n"
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{
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"text/html": [
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+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">01:25:41.409 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.task_runner.dask - Connecting to existing Dask cluster SLURMCluster(91d5c261, 'tcp://128.55.64.19:39737', workers=0, threads=0, memory=0 B)\n",
|
| 312 |
"</pre>\n"
|
| 313 |
],
|
| 314 |
"text/plain": [
|
| 315 |
+
"01:25:41.409 | \u001b[36mINFO\u001b[0m | prefect.task_runner.dask - Connecting to existing Dask cluster SLURMCluster(91d5c261, 'tcp://128.55.64.19:39737', workers=0, threads=0, memory=0 B)\n"
|
| 316 |
]
|
| 317 |
},
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"metadata": {},
|
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{
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"data": {
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| 323 |
"text/html": [
|
| 324 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">03:30:05.739 | <span style=\"color: #d70000; text-decoration-color: #d70000\">ERROR</span> | Flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'green-turaco'</span> - Encountered exception during execution: KilledWorker('run-3307095fc41590db704148cc499bad14', <WorkerState 'tcp://128.55.65.2:37007', name: SLURMCluster-1, status: closed, memory: 0, processing: 0>, 3)\n",
|
| 325 |
"Traceback (most recent call last):\n",
|
| 326 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 652, in run_context\n",
|
| 327 |
+
" yield self\n",
|
| 328 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 696, in run_flow_sync\n",
|
| 329 |
+
" engine.call_flow_fn()\n",
|
| 330 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 675, in call_flow_fn\n",
|
| 331 |
+
" result = call_with_parameters(self.flow.fn, self.parameters)\n",
|
| 332 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 333 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 206, in call_with_parameters\n",
|
| 334 |
+
" return fn(*args, **kwargs)\n",
|
| 335 |
+
" ^^^^^^^^^^^^^^^^^^^\n",
|
| 336 |
+
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in combustion\n",
|
| 337 |
+
" return [future.result() for future in futures]\n",
|
| 338 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 339 |
+
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in <listcomp>\n",
|
| 340 |
+
" return [future.result() for future in futures]\n",
|
| 341 |
+
" ^^^^^^^^^^^^^^^\n",
|
| 342 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py\", line 132, in result\n",
|
| 343 |
+
" future_result = self._wrapped_future.result(timeout=timeout)\n",
|
| 344 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 345 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 328, in result\n",
|
| 346 |
+
" return self.client.sync(self._result, callback_timeout=timeout)\n",
|
| 347 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 348 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 336, in _result\n",
|
| 349 |
+
" raise exc.with_traceback(tb)\n",
|
| 350 |
+
"distributed.scheduler.KilledWorker: Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see <span style=\"color: #0000ff; text-decoration-color: #0000ff\">https://distributed.dask.org/en/stable/killed.html.</span>\n",
|
|
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|
| 351 |
"</pre>\n"
|
| 352 |
],
|
| 353 |
"text/plain": [
|
| 354 |
+
"03:30:05.739 | \u001b[38;5;160mERROR\u001b[0m | Flow run\u001b[35m 'green-turaco'\u001b[0m - Encountered exception during execution: KilledWorker('run-3307095fc41590db704148cc499bad14', <WorkerState 'tcp://128.55.65.2:37007', name: SLURMCluster-1, status: closed, memory: 0, processing: 0>, 3)\n",
|
|
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|
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|
|
|
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|
|
|
| 355 |
"Traceback (most recent call last):\n",
|
| 356 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 652, in run_context\n",
|
| 357 |
+
" yield self\n",
|
| 358 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 696, in run_flow_sync\n",
|
| 359 |
+
" engine.call_flow_fn()\n",
|
| 360 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 675, in call_flow_fn\n",
|
| 361 |
+
" result = call_with_parameters(self.flow.fn, self.parameters)\n",
|
| 362 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 363 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 206, in call_with_parameters\n",
|
| 364 |
+
" return fn(*args, **kwargs)\n",
|
| 365 |
+
" ^^^^^^^^^^^^^^^^^^^\n",
|
| 366 |
+
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in combustion\n",
|
| 367 |
+
" return [future.result() for future in futures]\n",
|
| 368 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 369 |
+
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in <listcomp>\n",
|
| 370 |
+
" return [future.result() for future in futures]\n",
|
| 371 |
+
" ^^^^^^^^^^^^^^^\n",
|
| 372 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py\", line 132, in result\n",
|
| 373 |
+
" future_result = self._wrapped_future.result(timeout=timeout)\n",
|
| 374 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 375 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 328, in result\n",
|
| 376 |
+
" return self.client.sync(self._result, callback_timeout=timeout)\n",
|
| 377 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 378 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 336, in _result\n",
|
| 379 |
+
" raise exc.with_traceback(tb)\n",
|
| 380 |
+
"distributed.scheduler.KilledWorker: Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see \u001b[94mhttps://distributed.dask.org/en/stable/killed.html.\u001b[0m\n"
|
| 381 |
]
|
| 382 |
},
|
| 383 |
"metadata": {},
|
|
|
|
| 386 |
{
|
| 387 |
"data": {
|
| 388 |
"text/html": [
|
| 389 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">03:30:06.504 | <span style=\"color: #d70000; text-decoration-color: #d70000\">ERROR</span> | Flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'green-turaco'</span> - Finished in state <span style=\"color: #d70000; text-decoration-color: #d70000\">Failed</span>(\"Flow run encountered an exception: KilledWorker: Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see <span style=\"color: #0000ff; text-decoration-color: #0000ff\">https://distributed.dask.org/en/stable/killed.html.</span>\")\n",
|
| 390 |
"</pre>\n"
|
| 391 |
],
|
| 392 |
"text/plain": [
|
| 393 |
+
"03:30:06.504 | \u001b[38;5;160mERROR\u001b[0m | Flow run\u001b[35m 'green-turaco'\u001b[0m - Finished in state \u001b[38;5;160mFailed\u001b[0m(\"Flow run encountered an exception: KilledWorker: Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see \u001b[94mhttps://distributed.dask.org/en/stable/killed.html.\u001b[0m\")\n"
|
| 394 |
]
|
| 395 |
},
|
| 396 |
"metadata": {},
|
| 397 |
"output_type": "display_data"
|
| 398 |
},
|
| 399 |
{
|
| 400 |
+
"ename": "KilledWorker",
|
| 401 |
+
"evalue": "Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see https://distributed.dask.org/en/stable/killed.html.",
|
| 402 |
"output_type": "error",
|
| 403 |
"traceback": [
|
| 404 |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
| 405 |
+
"\u001b[0;31mKilledWorker\u001b[0m Traceback (most recent call last)",
|
| 406 |
+
"Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mcombustion\u001b[49m\u001b[43m(\u001b[49m\u001b[43matoms\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 407 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flows.py:1345\u001b[0m, in \u001b[0;36mFlow.__call__\u001b[0;34m(self, return_state, wait_for, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1341\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m track_viz_task(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39misasync, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname, parameters)\n\u001b[1;32m 1343\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mprefect\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mflow_engine\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m run_flow\n\u001b[0;32m-> 1345\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun_flow\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1346\u001b[0m \u001b[43m \u001b[49m\u001b[43mflow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1347\u001b[0m \u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1348\u001b[0m \u001b[43m \u001b[49m\u001b[43mwait_for\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mwait_for\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1349\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreturn_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1350\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 408 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:818\u001b[0m, in \u001b[0;36mrun_flow\u001b[0;34m(flow, flow_run, parameters, wait_for, return_type)\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m run_flow_async(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 817\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 818\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun_flow_sync\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 409 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:698\u001b[0m, in \u001b[0;36mrun_flow_sync\u001b[0;34m(flow, flow_run, parameters, wait_for, return_type)\u001b[0m\n\u001b[1;32m 695\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mrun_context():\n\u001b[1;32m 696\u001b[0m engine\u001b[38;5;241m.\u001b[39mcall_flow_fn()\n\u001b[0;32m--> 698\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mstate \u001b[38;5;28;01mif\u001b[39;00m return_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 410 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:255\u001b[0m, in \u001b[0;36mFlowRunEngine.result\u001b[0;34m(self, raise_on_failure)\u001b[0m\n\u001b[1;32m 253\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raised \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m NotSet:\n\u001b[1;32m 254\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raise_on_failure:\n\u001b[0;32m--> 255\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raised\n\u001b[1;32m 256\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raised\n\u001b[1;32m 258\u001b[0m \u001b[38;5;66;03m# This is a fall through case which leans on the existing state result mechanics to get the\u001b[39;00m\n\u001b[1;32m 259\u001b[0m \u001b[38;5;66;03m# return value. This is necessary because we currently will return a State object if the\u001b[39;00m\n\u001b[1;32m 260\u001b[0m \u001b[38;5;66;03m# the State was Prefect-created.\u001b[39;00m\n\u001b[1;32m 261\u001b[0m \u001b[38;5;66;03m# TODO: Remove the need to get the result from a State except in cases where the return value\u001b[39;00m\n\u001b[1;32m 262\u001b[0m \u001b[38;5;66;03m# is a State object.\u001b[39;00m\n",
|
| 411 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:652\u001b[0m, in \u001b[0;36mFlowRunEngine.run_context\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 645\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m timeout_context(\n\u001b[1;32m 646\u001b[0m seconds\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflow\u001b[38;5;241m.\u001b[39mtimeout_seconds,\n\u001b[1;32m 647\u001b[0m timeout_exc_type\u001b[38;5;241m=\u001b[39mFlowRunTimeoutError,\n\u001b[1;32m 648\u001b[0m ):\n\u001b[1;32m 649\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m 650\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExecuting flow \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflow\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m for flow run \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflow_run\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m...\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 651\u001b[0m )\n\u001b[0;32m--> 652\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n\u001b[1;32m 653\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTimeoutError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 654\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_timeout(exc)\n",
|
| 412 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:696\u001b[0m, in \u001b[0;36mrun_flow_sync\u001b[0;34m(flow, flow_run, parameters, wait_for, return_type)\u001b[0m\n\u001b[1;32m 694\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mis_running():\n\u001b[1;32m 695\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mrun_context():\n\u001b[0;32m--> 696\u001b[0m \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_flow_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 698\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mstate \u001b[38;5;28;01mif\u001b[39;00m return_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mresult()\n",
|
| 413 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:675\u001b[0m, in \u001b[0;36mFlowRunEngine.call_flow_fn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 673\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _call_flow_fn()\n\u001b[1;32m 674\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 675\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mcall_with_parameters\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflow\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 676\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_success(result)\n",
|
| 414 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py:206\u001b[0m, in \u001b[0;36mcall_with_parameters\u001b[0;34m(fn, parameters)\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;124;03mCall a function with parameters extracted with `get_call_parameters`\u001b[39;00m\n\u001b[1;32m 200\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 203\u001b[0m \u001b[38;5;124;03mthe args/kwargs using `parameters_to_positional_and_keyword` directly\u001b[39;00m\n\u001b[1;32m 204\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 205\u001b[0m args, kwargs \u001b[38;5;241m=\u001b[39m parameters_to_args_kwargs(fn, parameters)\n\u001b[0;32m--> 206\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 415 |
+
"Cell \u001b[0;32mIn[4], line 26\u001b[0m, in \u001b[0;36mcombustion\u001b[0;34m(atoms)\u001b[0m\n\u001b[1;32m 6\u001b[0m future \u001b[38;5;241m=\u001b[39m MD\u001b[38;5;241m.\u001b[39msubmit(\n\u001b[1;32m 7\u001b[0m atoms\u001b[38;5;241m=\u001b[39matoms,\n\u001b[1;32m 8\u001b[0m calculator_name\u001b[38;5;241m=\u001b[39mmodel,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 21\u001b[0m restart\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 22\u001b[0m )\n\u001b[1;32m 24\u001b[0m futures\u001b[38;5;241m.\u001b[39mappend(future)\n\u001b[0;32m---> 26\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m[\u001b[49m\u001b[43mfuture\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mfuture\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m]\u001b[49m\n",
|
| 416 |
+
"Cell \u001b[0;32mIn[4], line 26\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 6\u001b[0m future \u001b[38;5;241m=\u001b[39m MD\u001b[38;5;241m.\u001b[39msubmit(\n\u001b[1;32m 7\u001b[0m atoms\u001b[38;5;241m=\u001b[39matoms,\n\u001b[1;32m 8\u001b[0m calculator_name\u001b[38;5;241m=\u001b[39mmodel,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 21\u001b[0m restart\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 22\u001b[0m )\n\u001b[1;32m 24\u001b[0m futures\u001b[38;5;241m.\u001b[39mappend(future)\n\u001b[0;32m---> 26\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[43mfuture\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m future \u001b[38;5;129;01min\u001b[39;00m futures]\n",
|
| 417 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py:132\u001b[0m, in \u001b[0;36mPrefectDaskFuture.result\u001b[0;34m(self, timeout, raise_on_failure)\u001b[0m\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_final_state:\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 132\u001b[0m future_result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_wrapped_future\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m distributed\u001b[38;5;241m.\u001b[39mTimeoutError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTimeoutError\u001b[39;00m(\n\u001b[1;32m 135\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTask run \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtask_run_id\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m did not complete within \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtimeout\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m seconds\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 136\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mexc\u001b[39;00m\n",
|
| 418 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py:328\u001b[0m, in \u001b[0;36mFuture.result\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 326\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_verify_initialized()\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m shorten_traceback():\n\u001b[0;32m--> 328\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msync\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_result\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallback_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 419 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py:336\u001b[0m, in \u001b[0;36mFuture._result\u001b[0;34m(self, raiseit)\u001b[0m\n\u001b[1;32m 334\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raiseit:\n\u001b[1;32m 335\u001b[0m typ, exc, tb \u001b[38;5;241m=\u001b[39m exc\n\u001b[0;32m--> 336\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\u001b[38;5;241m.\u001b[39mwith_traceback(tb)\n\u001b[1;32m 337\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 338\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m exc\n",
|
| 420 |
+
"\u001b[0;31mKilledWorker\u001b[0m: Attempted to run task 'run-3307095fc41590db704148cc499bad14' on 4 different workers, but all those workers died while running it. The last worker that attempt to run the task was tcp://128.55.65.2:37007. Inspecting worker logs is often a good next step to diagnose what went wrong. For more information see https://distributed.dask.org/en/stable/killed.html."
|
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|
| 421 |
]
|
| 422 |
}
|
| 423 |
],
|
mlip_arena/tasks/eos/run.ipynb
ADDED
|
@@ -0,0 +1,645 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": 1,
|
| 6 |
+
"metadata": {},
|
| 7 |
+
"outputs": [],
|
| 8 |
+
"source": [
|
| 9 |
+
"import os\n",
|
| 10 |
+
"from mp_api.client import MPRester\n",
|
| 11 |
+
"from dask.distributed import Client\n",
|
| 12 |
+
"from dask_jobqueue import SLURMCluster\n",
|
| 13 |
+
"from prefect import task, flow\n",
|
| 14 |
+
"from prefect_dask import DaskTaskRunner\n",
|
| 15 |
+
"from pymatgen.core.structure import Structure\n",
|
| 16 |
+
"from dotenv import load_dotenv\n",
|
| 17 |
+
"from ase import Atoms\n",
|
| 18 |
+
"from ase.io import write, read\n",
|
| 19 |
+
"from pathlib import Path\n",
|
| 20 |
+
"import pandas as pd\n",
|
| 21 |
+
"from prefect.futures import wait\n",
|
| 22 |
+
"\n",
|
| 23 |
+
"from mlip_arena.tasks.eos.run import fit as EOS\n",
|
| 24 |
+
"from mlip_arena.models.utils import REGISTRY, MLIPEnum\n",
|
| 25 |
+
"\n",
|
| 26 |
+
"load_dotenv()\n",
|
| 27 |
+
"\n",
|
| 28 |
+
"MP_API_KEY = os.environ.get(\"MP_API_KEY\", None)"
|
| 29 |
+
]
|
| 30 |
+
},
|
| 31 |
+
{
|
| 32 |
+
"cell_type": "code",
|
| 33 |
+
"execution_count": 2,
|
| 34 |
+
"metadata": {},
|
| 35 |
+
"outputs": [
|
| 36 |
+
{
|
| 37 |
+
"name": "stdout",
|
| 38 |
+
"output_type": "stream",
|
| 39 |
+
"text": [
|
| 40 |
+
"MP Database version: 2023.11.1\n"
|
| 41 |
+
]
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"data": {
|
| 45 |
+
"application/vnd.jupyter.widget-view+json": {
|
| 46 |
+
"model_id": "bf1668eac663453aa9a20149ecf726c4",
|
| 47 |
+
"version_major": 2,
|
| 48 |
+
"version_minor": 0
|
| 49 |
+
},
|
| 50 |
+
"text/plain": [
|
| 51 |
+
"Retrieving SummaryDoc documents: 0%| | 0/5135 [00:00<?, ?it/s]"
|
| 52 |
+
]
|
| 53 |
+
},
|
| 54 |
+
"metadata": {},
|
| 55 |
+
"output_type": "display_data"
|
| 56 |
+
}
|
| 57 |
+
],
|
| 58 |
+
"source": [
|
| 59 |
+
"\n",
|
| 60 |
+
"with MPRester(MP_API_KEY) as mpr:\n",
|
| 61 |
+
" print(\"MP Database version:\", mpr.get_database_version())\n",
|
| 62 |
+
"\n",
|
| 63 |
+
" summary_docs = mpr.materials.summary.search(\n",
|
| 64 |
+
" num_elements=(1, 2),\n",
|
| 65 |
+
" is_stable=True,\n",
|
| 66 |
+
" fields=[\"material_id\", \"structure\", \"formula_pretty\"]\n",
|
| 67 |
+
" )\n"
|
| 68 |
+
]
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"cell_type": "code",
|
| 72 |
+
"execution_count": 8,
|
| 73 |
+
"metadata": {},
|
| 74 |
+
"outputs": [],
|
| 75 |
+
"source": [
|
| 76 |
+
"\n",
|
| 77 |
+
"atoms_list = []\n",
|
| 78 |
+
"\n",
|
| 79 |
+
"for doc in summary_docs:\n",
|
| 80 |
+
"\n",
|
| 81 |
+
" structure = doc.structure\n",
|
| 82 |
+
" assert isinstance(structure, Structure)\n",
|
| 83 |
+
"\n",
|
| 84 |
+
" atoms = structure.to_ase_atoms()\n",
|
| 85 |
+
"\n",
|
| 86 |
+
" atoms_list.append(atoms)\n"
|
| 87 |
+
]
|
| 88 |
+
},
|
| 89 |
+
{
|
| 90 |
+
"cell_type": "code",
|
| 91 |
+
"execution_count": 5,
|
| 92 |
+
"metadata": {},
|
| 93 |
+
"outputs": [],
|
| 94 |
+
"source": [
|
| 95 |
+
"write(\"all.extxyz\", atoms_list)"
|
| 96 |
+
]
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"cell_type": "code",
|
| 100 |
+
"execution_count": 3,
|
| 101 |
+
"metadata": {
|
| 102 |
+
"tags": []
|
| 103 |
+
},
|
| 104 |
+
"outputs": [],
|
| 105 |
+
"source": [
|
| 106 |
+
"atoms_list = read(\"all.extxyz\", index=':')"
|
| 107 |
+
]
|
| 108 |
+
},
|
| 109 |
+
{
|
| 110 |
+
"cell_type": "code",
|
| 111 |
+
"execution_count": 4,
|
| 112 |
+
"metadata": {},
|
| 113 |
+
"outputs": [
|
| 114 |
+
{
|
| 115 |
+
"name": "stdout",
|
| 116 |
+
"output_type": "stream",
|
| 117 |
+
"text": [
|
| 118 |
+
"#!/bin/bash\n",
|
| 119 |
+
"\n",
|
| 120 |
+
"#SBATCH -A matgen\n",
|
| 121 |
+
"#SBATCH --mem=0\n",
|
| 122 |
+
"#SBATCH -t 00:30:00\n",
|
| 123 |
+
"#SBATCH -N 1\n",
|
| 124 |
+
"#SBATCH -G 4\n",
|
| 125 |
+
"#SBATCH -q debug\n",
|
| 126 |
+
"#SBATCH -C gpu\n",
|
| 127 |
+
"#SBATCH -J eos\n",
|
| 128 |
+
"source ~/.bashrc\n",
|
| 129 |
+
"module load python\n",
|
| 130 |
+
"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\n",
|
| 131 |
+
"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/bin/python -m distributed.cli.dask_worker tcp://128.55.64.41:45323 --name dummy-name --nthreads 1 --memory-limit 59.60GiB --nanny --death-timeout 60\n",
|
| 132 |
+
"\n"
|
| 133 |
+
]
|
| 134 |
+
},
|
| 135 |
+
{
|
| 136 |
+
"name": "stderr",
|
| 137 |
+
"output_type": "stream",
|
| 138 |
+
"text": [
|
| 139 |
+
"Exception in thread Profile:\n",
|
| 140 |
+
"Traceback (most recent call last):\n",
|
| 141 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/threading.py\", line 1045, in _bootstrap_inner\n",
|
| 142 |
+
" self.run()\n",
|
| 143 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/ipykernel/ipkernel.py\", line 766, in run_closure\n",
|
| 144 |
+
" _threading_Thread_run(self)\n",
|
| 145 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/threading.py\", line 982, in run\n",
|
| 146 |
+
" self._target(*self._args, **self._kwargs)\n",
|
| 147 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/profile.py\", line 366, in _watch\n",
|
| 148 |
+
" process(frame, None, recent, omit=omit)\n",
|
| 149 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/profile.py\", line 183, in process\n",
|
| 150 |
+
" if any(frame.f_code.co_filename.endswith(o) for o in omit):\n",
|
| 151 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 152 |
+
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/profile.py\", line 183, in <genexpr>\n",
|
| 153 |
+
" if any(frame.f_code.co_filename.endswith(o) for o in omit):\n",
|
| 154 |
+
" ^^^^^^^^^^^^^^^^^^^^^^^^\n",
|
| 155 |
+
"AttributeError: 'dict' object has no attribute 'co_filename'\n"
|
| 156 |
+
]
|
| 157 |
+
}
|
| 158 |
+
],
|
| 159 |
+
"source": [
|
| 160 |
+
"nodes_per_alloc = 1\n",
|
| 161 |
+
"gpus_per_alloc = 4\n",
|
| 162 |
+
"ntasks = 1\n",
|
| 163 |
+
"\n",
|
| 164 |
+
"cluster_kwargs = {\n",
|
| 165 |
+
" \"cores\": 1,\n",
|
| 166 |
+
" \"memory\": \"64 GB\",\n",
|
| 167 |
+
" \"shebang\": \"#!/bin/bash\",\n",
|
| 168 |
+
" \"account\": \"matgen\",\n",
|
| 169 |
+
" \"walltime\": \"00:30:00\",\n",
|
| 170 |
+
" \"job_mem\": \"0\",\n",
|
| 171 |
+
" \"job_script_prologue\": [\n",
|
| 172 |
+
" \"source ~/.bashrc\",\n",
|
| 173 |
+
" \"module load python\",\n",
|
| 174 |
+
" \"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\",\n",
|
| 175 |
+
" ],\n",
|
| 176 |
+
" \"job_directives_skip\": [\"-n\", \"--cpus-per-task\", \"-J\"],\n",
|
| 177 |
+
" \"job_extra_directives\": [f\"-N {nodes_per_alloc}\", f\"-G {gpus_per_alloc}\", \"-q debug\", \"-C gpu\", \"-J eos\"],\n",
|
| 178 |
+
"}\n",
|
| 179 |
+
"cluster = SLURMCluster(**cluster_kwargs)\n",
|
| 180 |
+
"\n",
|
| 181 |
+
"print(cluster.job_script())\n",
|
| 182 |
+
"cluster.adapt(minimum_jobs=2, maximum_jobs=2)\n",
|
| 183 |
+
"client = Client(cluster)\n"
|
| 184 |
+
]
|
| 185 |
+
},
|
| 186 |
+
{
|
| 187 |
+
"cell_type": "code",
|
| 188 |
+
"execution_count": 5,
|
| 189 |
+
"metadata": {
|
| 190 |
+
"tags": []
|
| 191 |
+
},
|
| 192 |
+
"outputs": [],
|
| 193 |
+
"source": [
|
| 194 |
+
"\n",
|
| 195 |
+
"\n",
|
| 196 |
+
"def postprocess(output, model: str, formula: str):\n",
|
| 197 |
+
" row = {\n",
|
| 198 |
+
" \"formula\": formula,\n",
|
| 199 |
+
" \"method\": model,\n",
|
| 200 |
+
" \"volumes\": output[\"eos\"][\"volumes\"],\n",
|
| 201 |
+
" \"energies\": output[\"eos\"][\"energies\"],\n",
|
| 202 |
+
" \"K\": output[\"K\"],\n",
|
| 203 |
+
" }\n",
|
| 204 |
+
"\n",
|
| 205 |
+
" fpath = Path(REGISTRY[model][\"family\"]) / f\"{model}.parquet\"\n",
|
| 206 |
+
"\n",
|
| 207 |
+
" if not fpath.exists():\n",
|
| 208 |
+
" fpath.parent.mkdir(parents=True, exist_ok=True)\n",
|
| 209 |
+
" df = pd.DataFrame([row]) # Convert the dictionary to a DataFrame with a list\n",
|
| 210 |
+
" else:\n",
|
| 211 |
+
" df = pd.read_parquet(fpath)\n",
|
| 212 |
+
" new_row = pd.DataFrame([row]) # Convert dictionary to DataFrame with a list\n",
|
| 213 |
+
" df = pd.concat([df, new_row], ignore_index=True)\n",
|
| 214 |
+
"\n",
|
| 215 |
+
" df.drop_duplicates(subset=[\"formula\", \"method\"], keep='last', inplace=True)\n",
|
| 216 |
+
" df.to_parquet(fpath)\n",
|
| 217 |
+
"\n",
|
| 218 |
+
"from prefect.runtime import flow_run, task_run\n",
|
| 219 |
+
"EOS = EOS.with_options(timeout_seconds=240, result_storage=None)\n",
|
| 220 |
+
"\n",
|
| 221 |
+
"def generate_task_run_name():\n",
|
| 222 |
+
" task_name = task_run.task_name\n",
|
| 223 |
+
"\n",
|
| 224 |
+
" parameters = task_run.parameters\n",
|
| 225 |
+
"\n",
|
| 226 |
+
" atoms = parameters[\"atoms\"]\n",
|
| 227 |
+
" \n",
|
| 228 |
+
" return f\"{task_name}: {atoms.get_chemical_formula()}\"\n",
|
| 229 |
+
"\n",
|
| 230 |
+
"\n",
|
| 231 |
+
"@task(task_run_name=generate_task_run_name, result_storage=None)\n",
|
| 232 |
+
"def fit_one(atoms: Atoms):\n",
|
| 233 |
+
" \n",
|
| 234 |
+
" outputs = []\n",
|
| 235 |
+
" for model in MLIPEnum:\n",
|
| 236 |
+
" try:\n",
|
| 237 |
+
" eos = EOS(\n",
|
| 238 |
+
" atoms=atoms,\n",
|
| 239 |
+
" calculator_name=model.name,\n",
|
| 240 |
+
" calculator_kwargs={},\n",
|
| 241 |
+
" device=None,\n",
|
| 242 |
+
" optimizer=\"QuasiNewton\",\n",
|
| 243 |
+
" optimizer_kwargs=None,\n",
|
| 244 |
+
" filter=\"FrechetCell\",\n",
|
| 245 |
+
" filter_kwargs=None,\n",
|
| 246 |
+
" criterion=dict(\n",
|
| 247 |
+
" fmax=0.1,\n",
|
| 248 |
+
" ),\n",
|
| 249 |
+
" max_abs_strain=0.1,\n",
|
| 250 |
+
" npoints=7,\n",
|
| 251 |
+
" )\n",
|
| 252 |
+
" if isinstance(eos, dict):\n",
|
| 253 |
+
" postprocess(output=eos, model=model.name, formula=atoms.get_chemical_formula())\n",
|
| 254 |
+
" eos[\"method\"] = model.name\n",
|
| 255 |
+
" outputs.append(eos)\n",
|
| 256 |
+
" except:\n",
|
| 257 |
+
" continue\n",
|
| 258 |
+
" \n",
|
| 259 |
+
" return outputs\n",
|
| 260 |
+
"\n",
|
| 261 |
+
"\n",
|
| 262 |
+
"@flow(task_runner=DaskTaskRunner(address=client.scheduler.address), log_prints=True, result_storage=None)\n",
|
| 263 |
+
"def fit_all(atoms_list: list[Atoms]):\n",
|
| 264 |
+
" \n",
|
| 265 |
+
" futures = []\n",
|
| 266 |
+
" for atoms in atoms_list:\n",
|
| 267 |
+
" future = fit_one.submit(atoms)\n",
|
| 268 |
+
" futures.append(future)\n",
|
| 269 |
+
" \n",
|
| 270 |
+
" wait(futures)\n",
|
| 271 |
+
" \n",
|
| 272 |
+
" return [f.result(raise_on_failure=False) for f in futures]"
|
| 273 |
+
]
|
| 274 |
+
},
|
| 275 |
+
{
|
| 276 |
+
"cell_type": "code",
|
| 277 |
+
"execution_count": 6,
|
| 278 |
+
"metadata": {
|
| 279 |
+
"tags": []
|
| 280 |
+
},
|
| 281 |
+
"outputs": [
|
| 282 |
+
{
|
| 283 |
+
"data": {
|
| 284 |
+
"text/html": [
|
| 285 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">00:51:45.507 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.engine - Created flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'thistle-pronghorn'</span> for flow<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> 'fit-all'</span>\n",
|
| 286 |
+
"</pre>\n"
|
| 287 |
+
],
|
| 288 |
+
"text/plain": [
|
| 289 |
+
"00:51:45.507 | \u001b[36mINFO\u001b[0m | prefect.engine - Created flow run\u001b[35m 'thistle-pronghorn'\u001b[0m for flow\u001b[1;35m 'fit-all'\u001b[0m\n"
|
| 290 |
+
]
|
| 291 |
+
},
|
| 292 |
+
"metadata": {},
|
| 293 |
+
"output_type": "display_data"
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"data": {
|
| 297 |
+
"text/html": [
|
| 298 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">00:51:45.509 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.engine - View at <span style=\"color: #0000ff; text-decoration-color: #0000ff\">https://app.prefect.cloud/account/f7d40474-9362-4bfa-8950-ee6a43ec00f3/workspace/d4bb0913-5f5e-49f7-bfc5-06509088baeb/runs/flow-run/9b293dae-4c2d-43b7-b8bb-9a4749eee74e</span>\n",
|
| 299 |
+
"</pre>\n"
|
| 300 |
+
],
|
| 301 |
+
"text/plain": [
|
| 302 |
+
"00:51:45.509 | \u001b[36mINFO\u001b[0m | prefect.engine - View at \u001b[94mhttps://app.prefect.cloud/account/f7d40474-9362-4bfa-8950-ee6a43ec00f3/workspace/d4bb0913-5f5e-49f7-bfc5-06509088baeb/runs/flow-run/9b293dae-4c2d-43b7-b8bb-9a4749eee74e\u001b[0m\n"
|
| 303 |
+
]
|
| 304 |
+
},
|
| 305 |
+
"metadata": {},
|
| 306 |
+
"output_type": "display_data"
|
| 307 |
+
},
|
| 308 |
+
{
|
| 309 |
+
"data": {
|
| 310 |
+
"text/html": [
|
| 311 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">00:51:45.818 | <span style=\"color: #008080; text-decoration-color: #008080\">INFO</span> | prefect.task_runner.dask - Connecting to existing Dask cluster SLURMCluster(5d2876ed, 'tcp://128.55.64.41:45323', workers=0, threads=0, memory=0 B)\n",
|
| 312 |
+
"</pre>\n"
|
| 313 |
+
],
|
| 314 |
+
"text/plain": [
|
| 315 |
+
"00:51:45.818 | \u001b[36mINFO\u001b[0m | prefect.task_runner.dask - Connecting to existing Dask cluster SLURMCluster(5d2876ed, 'tcp://128.55.64.41:45323', workers=0, threads=0, memory=0 B)\n"
|
| 316 |
+
]
|
| 317 |
+
},
|
| 318 |
+
"metadata": {},
|
| 319 |
+
"output_type": "display_data"
|
| 320 |
+
},
|
| 321 |
+
{
|
| 322 |
+
"data": {
|
| 323 |
+
"text/html": [
|
| 324 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">00:58:09.352 | <span style=\"color: #d70000; text-decoration-color: #d70000\">ERROR</span> | Flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'thistle-pronghorn'</span> - Crash detected! Execution was aborted by an interrupt signal.\n",
|
| 325 |
+
"</pre>\n"
|
| 326 |
+
],
|
| 327 |
+
"text/plain": [
|
| 328 |
+
"00:58:09.352 | \u001b[38;5;160mERROR\u001b[0m | Flow run\u001b[35m 'thistle-pronghorn'\u001b[0m - Crash detected! Execution was aborted by an interrupt signal.\n"
|
| 329 |
+
]
|
| 330 |
+
},
|
| 331 |
+
"metadata": {},
|
| 332 |
+
"output_type": "display_data"
|
| 333 |
+
},
|
| 334 |
+
{
|
| 335 |
+
"data": {
|
| 336 |
+
"text/html": [
|
| 337 |
+
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">00:58:09.642 | <span style=\"color: #d70000; text-decoration-color: #d70000\">ERROR</span> | Flow run<span style=\"color: #800080; text-decoration-color: #800080\"> 'thistle-pronghorn'</span> - Finished in state <span style=\"color: #ff0000; text-decoration-color: #ff0000\">Crashed</span>('Execution was aborted by an interrupt signal.')\n",
|
| 338 |
+
"</pre>\n"
|
| 339 |
+
],
|
| 340 |
+
"text/plain": [
|
| 341 |
+
"00:58:09.642 | \u001b[38;5;160mERROR\u001b[0m | Flow run\u001b[35m 'thistle-pronghorn'\u001b[0m - Finished in state \u001b[91mCrashed\u001b[0m('Execution was aborted by an interrupt signal.')\n"
|
| 342 |
+
]
|
| 343 |
+
},
|
| 344 |
+
"metadata": {},
|
| 345 |
+
"output_type": "display_data"
|
| 346 |
+
},
|
| 347 |
+
{
|
| 348 |
+
"ename": "KeyboardInterrupt",
|
| 349 |
+
"evalue": "",
|
| 350 |
+
"output_type": "error",
|
| 351 |
+
"traceback": [
|
| 352 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
| 353 |
+
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
| 354 |
+
"Cell \u001b[0;32mIn[6], line 21\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# import os\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m# import tempfile\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# import shutil\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 18\u001b[0m \n\u001b[1;32m 19\u001b[0m \u001b[38;5;66;03m# with twd():\u001b[39;00m\n\u001b[0;32m---> 21\u001b[0m \u001b[43mfit_all\u001b[49m\u001b[43m(\u001b[49m\u001b[43matoms_list\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 355 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flows.py:1345\u001b[0m, in \u001b[0;36mFlow.__call__\u001b[0;34m(self, return_state, wait_for, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1341\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m track_viz_task(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39misasync, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname, parameters)\n\u001b[1;32m 1343\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mprefect\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mflow_engine\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m run_flow\n\u001b[0;32m-> 1345\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun_flow\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1346\u001b[0m \u001b[43m \u001b[49m\u001b[43mflow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1347\u001b[0m \u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1348\u001b[0m \u001b[43m \u001b[49m\u001b[43mwait_for\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mwait_for\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1349\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreturn_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1350\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
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| 356 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:818\u001b[0m, in \u001b[0;36mrun_flow\u001b[0;34m(flow, flow_run, parameters, wait_for, return_type)\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m run_flow_async(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 817\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 818\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrun_flow_sync\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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| 357 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:696\u001b[0m, in \u001b[0;36mrun_flow_sync\u001b[0;34m(flow, flow_run, parameters, wait_for, return_type)\u001b[0m\n\u001b[1;32m 694\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mis_running():\n\u001b[1;32m 695\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mrun_context():\n\u001b[0;32m--> 696\u001b[0m \u001b[43mengine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_flow_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 698\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mstate \u001b[38;5;28;01mif\u001b[39;00m return_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mresult()\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py:675\u001b[0m, in \u001b[0;36mFlowRunEngine.call_flow_fn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 673\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _call_flow_fn()\n\u001b[1;32m 674\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 675\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mcall_with_parameters\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflow\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 676\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_success(result)\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py:206\u001b[0m, in \u001b[0;36mcall_with_parameters\u001b[0;34m(fn, parameters)\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;124;03mCall a function with parameters extracted with `get_call_parameters`\u001b[39;00m\n\u001b[1;32m 200\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 203\u001b[0m \u001b[38;5;124;03mthe args/kwargs using `parameters_to_positional_and_keyword` directly\u001b[39;00m\n\u001b[1;32m 204\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 205\u001b[0m args, kwargs \u001b[38;5;241m=\u001b[39m parameters_to_args_kwargs(fn, parameters)\n\u001b[0;32m--> 206\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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"Cell \u001b[0;32mIn[5], line 72\u001b[0m, in \u001b[0;36mfit_all\u001b[0;34m(atoms_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m futures \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 71\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m atoms \u001b[38;5;129;01min\u001b[39;00m atoms_list:\n\u001b[0;32m---> 72\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[43mfit_one\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\u001b[43matoms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m futures\u001b[38;5;241m.\u001b[39mappend(future)\n\u001b[1;32m 75\u001b[0m wait(futures)\n",
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| 361 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/tasks.py:1163\u001b[0m, in \u001b[0;36mTask.submit\u001b[0;34m(self, return_state, wait_for, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m VisualizationUnsupportedError(\n\u001b[1;32m 1159\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`task.submit()` is not currently supported by `flow.visualize()`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1160\u001b[0m )\n\u001b[1;32m 1162\u001b[0m task_runner \u001b[38;5;241m=\u001b[39m flow_run_context\u001b[38;5;241m.\u001b[39mtask_runner\n\u001b[0;32m-> 1163\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[43mtask_runner\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwait_for\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m return_state:\n\u001b[1;32m 1165\u001b[0m future\u001b[38;5;241m.\u001b[39mwait()\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py:353\u001b[0m, in \u001b[0;36mDaskTaskRunner.submit\u001b[0;34m(self, task, parameters, wait_for, dependencies)\u001b[0m\n\u001b[1;32m 349\u001b[0m \u001b[38;5;66;03m# unpack the upstream call in order to cast Prefect futures to Dask futures\u001b[39;00m\n\u001b[1;32m 350\u001b[0m \u001b[38;5;66;03m# where possible to optimize Dask task scheduling\u001b[39;00m\n\u001b[1;32m 351\u001b[0m parameters \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_optimize_futures(parameters)\n\u001b[0;32m--> 353\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 354\u001b[0m \u001b[43m \u001b[49m\u001b[43mtask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 355\u001b[0m \u001b[43m \u001b[49m\u001b[43mparameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 356\u001b[0m \u001b[43m \u001b[49m\u001b[43mwait_for\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mwait_for\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 357\u001b[0m \u001b[43m \u001b[49m\u001b[43mdependencies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdependencies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 358\u001b[0m \u001b[43m \u001b[49m\u001b[43mreturn_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstate\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 359\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 360\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m PrefectDaskFuture(wrapped_future\u001b[38;5;241m=\u001b[39mfuture, task_run_id\u001b[38;5;241m=\u001b[39mfuture\u001b[38;5;241m.\u001b[39mtask_run_id)\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/client.py:64\u001b[0m, in \u001b[0;36mPrefectDaskClient.submit\u001b[0;34m(self, func, key, workers, resources, retries, priority, fifo_timeout, allow_other_workers, actor, actors, pure, *args, **kwargs)\u001b[0m\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 62\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m run_task_sync(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m---> 64\u001b[0m future \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubmit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 65\u001b[0m \u001b[43m \u001b[49m\u001b[43mwrapper_func\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 66\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 67\u001b[0m \u001b[43m \u001b[49m\u001b[43mworkers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworkers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 68\u001b[0m \u001b[43m \u001b[49m\u001b[43mresources\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresources\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 69\u001b[0m \u001b[43m \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 70\u001b[0m \u001b[43m \u001b[49m\u001b[43mpriority\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpriority\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 71\u001b[0m \u001b[43m \u001b[49m\u001b[43mfifo_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfifo_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[43m \u001b[49m\u001b[43mallow_other_workers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_other_workers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[43m \u001b[49m\u001b[43mactor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mactor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[43m \u001b[49m\u001b[43mactors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mactors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 75\u001b[0m \u001b[43m \u001b[49m\u001b[43mpure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpure\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 76\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mrun_task_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 77\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 79\u001b[0m future\u001b[38;5;241m.\u001b[39mtask_run_id \u001b[38;5;241m=\u001b[39m run_task_kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtask_run_id\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 80\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m future\n",
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py:1931\u001b[0m, in \u001b[0;36mClient.submit\u001b[0;34m(self, func, key, workers, resources, retries, priority, fifo_timeout, allow_other_workers, actor, actors, pure, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1929\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m key \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1930\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m pure:\n\u001b[0;32m-> 1931\u001b[0m key \u001b[38;5;241m=\u001b[39m funcname(func) \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m-\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[43mtokenize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1932\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1933\u001b[0m key \u001b[38;5;241m=\u001b[39m funcname(func) \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m-\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mstr\u001b[39m(uuid\u001b[38;5;241m.\u001b[39muuid4())\n",
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| 365 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1033\u001b[0m, in \u001b[0;36mtokenize\u001b[0;34m(ensure_deterministic, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1015\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Deterministic token\u001b[39;00m\n\u001b[1;32m 1016\u001b[0m \n\u001b[1;32m 1017\u001b[0m \u001b[38;5;124;03m>>> tokenize([1, 2, '3'])\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1030\u001b[0m \u001b[38;5;124;03m Defaults to the `tokenize.ensure-deterministic` configuration parameter.\u001b[39;00m\n\u001b[1;32m 1031\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 1032\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _seen_ctx(reset\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m), _ensure_deterministic_ctx(ensure_deterministic):\n\u001b[0;32m-> 1033\u001b[0m token: \u001b[38;5;28mobject\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1034\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m kwargs:\n\u001b[1;32m 1035\u001b[0m token \u001b[38;5;241m=\u001b[39m token, _normalize_seq_func(\u001b[38;5;28msorted\u001b[39m(kwargs\u001b[38;5;241m.\u001b[39mitems()))\n",
|
| 366 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1159\u001b[0m, in \u001b[0;36m_normalize_seq_func\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1158\u001b[0m seen[\u001b[38;5;28mid\u001b[39m(item)] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(seen), item\n\u001b[0;32m-> 1159\u001b[0m item \u001b[38;5;241m=\u001b[39m \u001b[43mnormalize_token\u001b[49m\u001b[43m(\u001b[49m\u001b[43mitem\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1160\u001b[0m out\u001b[38;5;241m.\u001b[39mappend(item)\n\u001b[1;32m 1161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
|
| 367 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/utils.py:773\u001b[0m, in \u001b[0;36mDispatch.__call__\u001b[0;34m(self, arg, *args, **kwargs)\u001b[0m\n\u001b[1;32m 769\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 770\u001b[0m \u001b[38;5;124;03mCall the corresponding method based on type of argument.\u001b[39;00m\n\u001b[1;32m 771\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 772\u001b[0m meth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdispatch(\u001b[38;5;28mtype\u001b[39m(arg))\n\u001b[0;32m--> 773\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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| 368 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1129\u001b[0m, in \u001b[0;36mnormalize_dict\u001b[0;34m(d)\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((types\u001b[38;5;241m.\u001b[39mMappingProxyType, \u001b[38;5;28mdict\u001b[39m))\n\u001b[1;32m 1128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_dict\u001b[39m(d):\n\u001b[0;32m-> 1129\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdict\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43msorted\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43md\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkv\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkv\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
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| 369 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1159\u001b[0m, in \u001b[0;36m_normalize_seq_func\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1158\u001b[0m seen[\u001b[38;5;28mid\u001b[39m(item)] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(seen), item\n\u001b[0;32m-> 1159\u001b[0m item \u001b[38;5;241m=\u001b[39m \u001b[43mnormalize_token\u001b[49m\u001b[43m(\u001b[49m\u001b[43mitem\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1160\u001b[0m out\u001b[38;5;241m.\u001b[39mappend(item)\n\u001b[1;32m 1161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
|
| 370 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/utils.py:773\u001b[0m, in \u001b[0;36mDispatch.__call__\u001b[0;34m(self, arg, *args, **kwargs)\u001b[0m\n\u001b[1;32m 769\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 770\u001b[0m \u001b[38;5;124;03mCall the corresponding method based on type of argument.\u001b[39;00m\n\u001b[1;32m 771\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 772\u001b[0m meth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdispatch(\u001b[38;5;28mtype\u001b[39m(arg))\n\u001b[0;32m--> 773\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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| 371 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1166\u001b[0m, in \u001b[0;36mnormalize_seq\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((\u001b[38;5;28mtuple\u001b[39m, \u001b[38;5;28mlist\u001b[39m))\n\u001b[1;32m 1165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_seq\u001b[39m(seq):\n\u001b[0;32m-> 1166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(seq)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mseq\u001b[49m\u001b[43m)\u001b[49m\n",
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| 372 |
+
" \u001b[0;31m[... skipping similar frames: Dispatch.__call__ at line 773 (1 times), _normalize_seq_func at line 1159 (1 times)]\u001b[0m\n",
|
| 373 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1129\u001b[0m, in \u001b[0;36mnormalize_dict\u001b[0;34m(d)\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((types\u001b[38;5;241m.\u001b[39mMappingProxyType, \u001b[38;5;28mdict\u001b[39m))\n\u001b[1;32m 1128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_dict\u001b[39m(d):\n\u001b[0;32m-> 1129\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdict\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43msorted\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43md\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkv\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkv\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 374 |
+
" \u001b[0;31m[... skipping similar frames: Dispatch.__call__ at line 773 (1 times), _normalize_seq_func at line 1159 (1 times)]\u001b[0m\n",
|
| 375 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1166\u001b[0m, in \u001b[0;36mnormalize_seq\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((\u001b[38;5;28mtuple\u001b[39m, \u001b[38;5;28mlist\u001b[39m))\n\u001b[1;32m 1165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_seq\u001b[39m(seq):\n\u001b[0;32m-> 1166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(seq)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mseq\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 376 |
+
" \u001b[0;31m[... skipping similar frames: Dispatch.__call__ at line 773 (3 times), _normalize_seq_func at line 1159 (3 times), normalize_dict at line 1129 (1 times), normalize_seq at line 1166 (1 times)]\u001b[0m\n",
|
| 377 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1129\u001b[0m, in \u001b[0;36mnormalize_dict\u001b[0;34m(d)\u001b[0m\n\u001b[1;32m 1127\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((types\u001b[38;5;241m.\u001b[39mMappingProxyType, \u001b[38;5;28mdict\u001b[39m))\n\u001b[1;32m 1128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_dict\u001b[39m(d):\n\u001b[0;32m-> 1129\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdict\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43msorted\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43md\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkv\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkv\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 378 |
+
" \u001b[0;31m[... skipping similar frames: Dispatch.__call__ at line 773 (2 times), _normalize_seq_func at line 1159 (2 times), normalize_seq at line 1166 (1 times)]\u001b[0m\n",
|
| 379 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1166\u001b[0m, in \u001b[0;36mnormalize_seq\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;129m@normalize_token\u001b[39m\u001b[38;5;241m.\u001b[39mregister((\u001b[38;5;28mtuple\u001b[39m, \u001b[38;5;28mlist\u001b[39m))\n\u001b[1;32m 1165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mnormalize_seq\u001b[39m(seq):\n\u001b[0;32m-> 1166\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(seq)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[43m_normalize_seq_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mseq\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 380 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1159\u001b[0m, in \u001b[0;36m_normalize_seq_func\u001b[0;34m(seq)\u001b[0m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1158\u001b[0m seen[\u001b[38;5;28mid\u001b[39m(item)] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(seen), item\n\u001b[0;32m-> 1159\u001b[0m item \u001b[38;5;241m=\u001b[39m \u001b[43mnormalize_token\u001b[49m\u001b[43m(\u001b[49m\u001b[43mitem\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1160\u001b[0m out\u001b[38;5;241m.\u001b[39mappend(item)\n\u001b[1;32m 1161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
|
| 381 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/utils.py:773\u001b[0m, in \u001b[0;36mDispatch.__call__\u001b[0;34m(self, arg, *args, **kwargs)\u001b[0m\n\u001b[1;32m 769\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 770\u001b[0m \u001b[38;5;124;03mCall the corresponding method based on type of argument.\u001b[39;00m\n\u001b[1;32m 771\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 772\u001b[0m meth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdispatch(\u001b[38;5;28mtype\u001b[39m(arg))\n\u001b[0;32m--> 773\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 382 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1212\u001b[0m, in \u001b[0;36mnormalize_object\u001b[0;34m(o)\u001b[0m\n\u001b[1;32m 1209\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _normalize_dataclass(o)\n\u001b[1;32m 1211\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_normalize_pickle\u001b[49m\u001b[43m(\u001b[49m\u001b[43mo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m 1214\u001b[0m _maybe_raise_nondeterministic(\n\u001b[1;32m 1215\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mObject \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mo\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m cannot be deterministically hashed. See \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1216\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://docs.dask.org/en/latest/custom-collections.html#implementing-deterministic-hashing \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1217\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfor more information.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1218\u001b[0m )\n",
|
| 383 |
+
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/base.py:1250\u001b[0m, in \u001b[0;36m_normalize_pickle\u001b[0;34m(o)\u001b[0m\n\u001b[1;32m 1247\u001b[0m buffers\u001b[38;5;241m.\u001b[39mclear()\n\u001b[1;32m 1248\u001b[0m pik \u001b[38;5;241m=\u001b[39m cloudpickle\u001b[38;5;241m.\u001b[39mdumps(o, protocol\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5\u001b[39m, buffer_callback\u001b[38;5;241m=\u001b[39mbuffers\u001b[38;5;241m.\u001b[39mappend)\n\u001b[0;32m-> 1250\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhash_buffer_hex\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpik\u001b[49m\u001b[43m)\u001b[49m, [hash_buffer_hex(buf) \u001b[38;5;28;01mfor\u001b[39;00m buf \u001b[38;5;129;01min\u001b[39;00m buffers]\n",
|
| 384 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/hashing.py:98\u001b[0m, in \u001b[0;36mhash_buffer_hex\u001b[0;34m(buf, hasher)\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhash_buffer_hex\u001b[39m(buf, hasher\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 95\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 96\u001b[0m \u001b[38;5;124;03m Same as hash_buffer, but returns its result in hex-encoded form.\u001b[39;00m\n\u001b[1;32m 97\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 98\u001b[0m h \u001b[38;5;241m=\u001b[39m \u001b[43mhash_buffer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhasher\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 99\u001b[0m s \u001b[38;5;241m=\u001b[39m binascii\u001b[38;5;241m.\u001b[39mb2a_hex(h)\n\u001b[1;32m 100\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m s\u001b[38;5;241m.\u001b[39mdecode()\n",
|
| 385 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/hashing.py:88\u001b[0m, in \u001b[0;36mhash_buffer\u001b[0;34m(buf, hasher)\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m hasher \u001b[38;5;129;01min\u001b[39;00m hashers:\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 88\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhasher\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuf\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mOverflowError\u001b[39;00m):\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n",
|
| 386 |
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"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/dask/hashing.py:44\u001b[0m, in \u001b[0;36m_hash_xxhash\u001b[0;34m(buf)\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_hash_xxhash\u001b[39m(buf):\n\u001b[1;32m 41\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124;03m Produce a 8-bytes hash of *buf* using xxHash.\u001b[39;00m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mxxhash\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mxxh64\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuf\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mdigest()\n",
|
| 387 |
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"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
|
| 388 |
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]
|
| 389 |
+
}
|
| 390 |
+
],
|
| 391 |
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"source": [
|
| 392 |
+
"# import os\n",
|
| 393 |
+
"# import tempfile\n",
|
| 394 |
+
"# import shutil\n",
|
| 395 |
+
"# from contextlib import contextmanager\n",
|
| 396 |
+
"\n",
|
| 397 |
+
"# @contextmanager\n",
|
| 398 |
+
"# def twd():\n",
|
| 399 |
+
" \n",
|
| 400 |
+
"# pwd = os.getcwd()\n",
|
| 401 |
+
"# temp_dir = tempfile.mkdtemp()\n",
|
| 402 |
+
" \n",
|
| 403 |
+
"# try:\n",
|
| 404 |
+
"# os.chdir(temp_dir)\n",
|
| 405 |
+
"# yield\n",
|
| 406 |
+
"# finally:\n",
|
| 407 |
+
"# os.chdir(pwd)\n",
|
| 408 |
+
"# shutil.rmtree(temp_dir)\n",
|
| 409 |
+
"\n",
|
| 410 |
+
"# with twd():\n",
|
| 411 |
+
"\n",
|
| 412 |
+
"fit_all(atoms_list)"
|
| 413 |
+
]
|
| 414 |
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},
|
| 415 |
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{
|
| 416 |
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|
| 420 |
+
},
|
| 421 |
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"outputs": [],
|
| 422 |
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"source": [
|
| 423 |
+
"import pandas as pd\n",
|
| 424 |
+
"\n",
|
| 425 |
+
"df = pd.read_parquet('mace-mp/MACE-MP(M).parquet')"
|
| 426 |
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]
|
| 427 |
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},
|
| 428 |
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| 430 |
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| 431 |
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"metadata": {},
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"data": {
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|
| 452 |
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|
| 453 |
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" <th></th>\n",
|
| 454 |
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" <th>formula</th>\n",
|
| 455 |
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" <th>method</th>\n",
|
| 456 |
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" <th>volumes</th>\n",
|
| 457 |
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" <th>energies</th>\n",
|
| 458 |
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" <th>K</th>\n",
|
| 459 |
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" </tr>\n",
|
| 460 |
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|
| 461 |
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|
| 462 |
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|
| 463 |
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|
| 464 |
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" <td>Ac2O3</td>\n",
|
| 465 |
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" <td>MACE-MP(M)</td>\n",
|
| 466 |
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" <td>[82.36010147441682, 85.41047560309894, 88.4608...</td>\n",
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| 469 |
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|
| 470 |
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| 472 |
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| 473 |
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" <td>MACE-MP(M)</td>\n",
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| 474 |
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| 479 |
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" <th>3</th>\n",
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| 480 |
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" <td>Ac16S24</td>\n",
|
| 481 |
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" <td>MACE-MP(M)</td>\n",
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| 482 |
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" <td>[1006.5670668063424, 1043.84732853991, 1081.12...</td>\n",
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" formula method volumes \\\n",
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"0 Ac2O3 MACE-MP(M) [82.36010147441682, 85.41047560309894, 88.4608... \n",
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| 493 |
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| 494 |
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"3 Ac16S24 MACE-MP(M) [1006.5670668063424, 1043.84732853991, 1081.12... \n",
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| 495 |
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"\n",
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| 496 |
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" energies K \n",
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| 497 |
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"0 [-39.47665786743164, -39.65583419799805, -39.7... 95.869141 \n",
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| 498 |
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}
|
| 618 |
+
},
|
| 619 |
+
"cf1131b45bf04178ac93962259718700": {
|
| 620 |
+
"model_module": "@jupyter-widgets/controls",
|
| 621 |
+
"model_module_version": "2.0.0",
|
| 622 |
+
"model_name": "FloatProgressModel",
|
| 623 |
+
"state": {
|
| 624 |
+
"bar_style": "success",
|
| 625 |
+
"layout": "IPY_MODEL_b09359f88f954062aff30df3bf2ba46b",
|
| 626 |
+
"max": 5135,
|
| 627 |
+
"style": "IPY_MODEL_8d602e7a8e734c50b0fad54bf76cc7d5",
|
| 628 |
+
"value": 5135
|
| 629 |
+
}
|
| 630 |
+
},
|
| 631 |
+
"e03d78a760b8402cad0827279f4075c1": {
|
| 632 |
+
"model_module": "@jupyter-widgets/base",
|
| 633 |
+
"model_module_version": "2.0.0",
|
| 634 |
+
"model_name": "LayoutModel",
|
| 635 |
+
"state": {}
|
| 636 |
+
}
|
| 637 |
+
},
|
| 638 |
+
"version_major": 2,
|
| 639 |
+
"version_minor": 0
|
| 640 |
+
}
|
| 641 |
+
}
|
| 642 |
+
},
|
| 643 |
+
"nbformat": 4,
|
| 644 |
+
"nbformat_minor": 4
|
| 645 |
+
}
|
mlip_arena/tasks/eos/run.py
CHANGED
|
@@ -6,7 +6,6 @@ https://github.com/materialsvirtuallab/matcalc/blob/main/matcalc/eos.py
|
|
| 6 |
|
| 7 |
from __future__ import annotations
|
| 8 |
|
| 9 |
-
import asyncio
|
| 10 |
from typing import TYPE_CHECKING
|
| 11 |
|
| 12 |
import numpy as np
|
|
@@ -15,9 +14,9 @@ from ase.filters import * # type: ignore
|
|
| 15 |
from ase.optimize import * # type: ignore
|
| 16 |
from ase.optimize.optimize import Optimizer
|
| 17 |
from prefect import flow
|
| 18 |
-
from pymatgen.analysis.eos import BirchMurnaghan
|
| 19 |
-
|
| 20 |
from prefect.futures import wait
|
|
|
|
|
|
|
| 21 |
|
| 22 |
from mlip_arena.models.utils import MLIPEnum
|
| 23 |
from mlip_arena.tasks.optimize import run as OPT
|
|
@@ -26,13 +25,36 @@ if TYPE_CHECKING:
|
|
| 26 |
from ase.filters import Filter
|
| 27 |
|
| 28 |
|
| 29 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 30 |
def fit(
|
| 31 |
atoms: Atoms,
|
| 32 |
calculator_name: str | MLIPEnum,
|
| 33 |
calculator_kwargs: dict | None,
|
| 34 |
device: str | None = None,
|
| 35 |
-
optimizer: Optimizer | str = BFGSLineSearch,
|
| 36 |
optimizer_kwargs: dict | None = None,
|
| 37 |
filter: Filter | str | None = None,
|
| 38 |
filter_kwargs: dict | None = None,
|
|
@@ -59,7 +81,7 @@ def fit(
|
|
| 59 |
Returns:
|
| 60 |
A dictionary containing the EOS data and the bulk modulus.
|
| 61 |
"""
|
| 62 |
-
|
| 63 |
atoms=atoms,
|
| 64 |
calculator_name=calculator_name,
|
| 65 |
calculator_kwargs=calculator_kwargs,
|
|
@@ -71,7 +93,7 @@ def fit(
|
|
| 71 |
criterion=criterion,
|
| 72 |
)
|
| 73 |
|
| 74 |
-
relaxed =
|
| 75 |
|
| 76 |
# p0 = relaxed.get_positions()
|
| 77 |
c0 = relaxed.get_cell()
|
|
@@ -99,14 +121,20 @@ def fit(
|
|
| 99 |
|
| 100 |
wait(futures)
|
| 101 |
|
| 102 |
-
volumes = [f.result()["atoms"].get_volume() for f in futures]
|
| 103 |
-
energies = [f.result()["atoms"].get_potential_energy() for f in futures]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 104 |
|
| 105 |
bm = BirchMurnaghan(volumes=volumes, energies=energies)
|
| 106 |
bm.fit()
|
| 107 |
|
| 108 |
-
volumes, energies = map(list, zip(*sorted(zip(volumes, energies, strict=False), key=lambda i: i[0]), strict=False))
|
| 109 |
-
|
| 110 |
return {
|
| 111 |
"eos": {"volumes": volumes, "energies": energies},
|
| 112 |
"K": bm.b0_GPa,
|
|
|
|
| 6 |
|
| 7 |
from __future__ import annotations
|
| 8 |
|
|
|
|
| 9 |
from typing import TYPE_CHECKING
|
| 10 |
|
| 11 |
import numpy as np
|
|
|
|
| 14 |
from ase.optimize import * # type: ignore
|
| 15 |
from ase.optimize.optimize import Optimizer
|
| 16 |
from prefect import flow
|
|
|
|
|
|
|
| 17 |
from prefect.futures import wait
|
| 18 |
+
from prefect.runtime import flow_run, task_run
|
| 19 |
+
from pymatgen.analysis.eos import BirchMurnaghan
|
| 20 |
|
| 21 |
from mlip_arena.models.utils import MLIPEnum
|
| 22 |
from mlip_arena.tasks.optimize import run as OPT
|
|
|
|
| 25 |
from ase.filters import Filter
|
| 26 |
|
| 27 |
|
| 28 |
+
def generate_flow_run_name():
|
| 29 |
+
flow_name = flow_run.flow_name
|
| 30 |
+
|
| 31 |
+
parameters = flow_run.parameters
|
| 32 |
+
|
| 33 |
+
atoms = parameters["atoms"]
|
| 34 |
+
calculator_name = parameters["calculator_name"]
|
| 35 |
+
|
| 36 |
+
return f"{flow_name}: {atoms.get_chemical_formula()} - {calculator_name}"
|
| 37 |
+
|
| 38 |
+
|
| 39 |
+
def generate_task_run_name():
|
| 40 |
+
task_name = task_run.task_name
|
| 41 |
+
|
| 42 |
+
parameters = task_run.parameters
|
| 43 |
+
|
| 44 |
+
atoms = parameters["atoms"]
|
| 45 |
+
calculator_name = parameters["calculator_name"]
|
| 46 |
+
|
| 47 |
+
return f"{task_name}: {atoms.get_chemical_formula()} - {calculator_name}"
|
| 48 |
+
|
| 49 |
+
|
| 50 |
+
# @task(task_run_name=generate_task_run_name)
|
| 51 |
+
@flow(flow_run_name=generate_flow_run_name, validate_parameters=False)
|
| 52 |
def fit(
|
| 53 |
atoms: Atoms,
|
| 54 |
calculator_name: str | MLIPEnum,
|
| 55 |
calculator_kwargs: dict | None,
|
| 56 |
device: str | None = None,
|
| 57 |
+
optimizer: Optimizer | str = "BFGSLineSearch", # type: ignore
|
| 58 |
optimizer_kwargs: dict | None = None,
|
| 59 |
filter: Filter | str | None = None,
|
| 60 |
filter_kwargs: dict | None = None,
|
|
|
|
| 81 |
Returns:
|
| 82 |
A dictionary containing the EOS data and the bulk modulus.
|
| 83 |
"""
|
| 84 |
+
first_relax = OPT(
|
| 85 |
atoms=atoms,
|
| 86 |
calculator_name=calculator_name,
|
| 87 |
calculator_kwargs=calculator_kwargs,
|
|
|
|
| 93 |
criterion=criterion,
|
| 94 |
)
|
| 95 |
|
| 96 |
+
relaxed = first_relax["atoms"]
|
| 97 |
|
| 98 |
# p0 = relaxed.get_positions()
|
| 99 |
c0 = relaxed.get_cell()
|
|
|
|
| 121 |
|
| 122 |
wait(futures)
|
| 123 |
|
| 124 |
+
volumes = [f.result()["atoms"].get_volume() for f in futures if isinstance(f.result(), dict)]
|
| 125 |
+
energies = [f.result()["atoms"].get_potential_energy() for f in futures if isinstance(f.result(), dict)]
|
| 126 |
+
|
| 127 |
+
volumes, energies = map(
|
| 128 |
+
list,
|
| 129 |
+
zip(
|
| 130 |
+
*sorted(zip(volumes, energies, strict=True), key=lambda i: i[0]),
|
| 131 |
+
strict=True,
|
| 132 |
+
),
|
| 133 |
+
)
|
| 134 |
|
| 135 |
bm = BirchMurnaghan(volumes=volumes, energies=energies)
|
| 136 |
bm.fit()
|
| 137 |
|
|
|
|
|
|
|
| 138 |
return {
|
| 139 |
"eos": {"volumes": volumes, "energies": energies},
|
| 140 |
"K": bm.b0_GPa,
|
mlip_arena/tasks/optimize.py
CHANGED
|
@@ -41,7 +41,11 @@ _valid_optimizers: dict[str, Optimizer] = {
|
|
| 41 |
} # type: ignore
|
| 42 |
|
| 43 |
|
| 44 |
-
@task(
|
|
|
|
|
|
|
|
|
|
|
|
|
| 45 |
def run(
|
| 46 |
atoms: Atoms,
|
| 47 |
calculator_name: str | MLIPEnum,
|
|
|
|
| 41 |
} # type: ignore
|
| 42 |
|
| 43 |
|
| 44 |
+
# @task(
|
| 45 |
+
# cache_key_fn=task_input_hash,
|
| 46 |
+
# cache_expiration=timedelta(days=1),
|
| 47 |
+
# timeout_seconds=120)
|
| 48 |
+
@task(timeout_seconds=120, result_storage=None)
|
| 49 |
def run(
|
| 50 |
atoms: Atoms,
|
| 51 |
calculator_name: str | MLIPEnum,
|
tests/test_eos.py
CHANGED
|
@@ -12,7 +12,7 @@ atoms = bulk("Cu", "fcc", a=3.6)
|
|
| 12 |
|
| 13 |
@pytest.mark.parametrize("model", [MLIPEnum["MACE-MP(M)"]])
|
| 14 |
@pytest.mark.skipif(
|
| 15 |
-
sys.version_info != (3, 11), reason="requires Python 3.11 to use prefect"
|
| 16 |
)
|
| 17 |
def test_eos(model: MLIPEnum):
|
| 18 |
"""
|
|
|
|
| 12 |
|
| 13 |
@pytest.mark.parametrize("model", [MLIPEnum["MACE-MP(M)"]])
|
| 14 |
@pytest.mark.skipif(
|
| 15 |
+
tuple(sys.version_info)[:2] != (3, 11), reason="requires Python 3.11 to use prefect"
|
| 16 |
)
|
| 17 |
def test_eos(model: MLIPEnum):
|
| 18 |
"""
|