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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from pathlib import Path\n",
"\n",
"from ase import units, Atoms\n",
"from ase.build import molecule\n",
"from ase.io import read, write\n",
"from dask.distributed import Client\n",
"from dask_jobqueue import SLURMCluster\n",
"from prefect import flow\n",
"from prefect_dask import DaskTaskRunner\n",
"from pymatgen.core import Molecule\n",
"from pymatgen.io.packmol import PackmolBoxGen\n",
"\n",
"from mlip_arena.models.utils import REGISTRY, MLIPEnum\n",
"from mlip_arena.tasks.md import run as MD"
]
},
{
"cell_type": "markdown",
"metadata": {
"jp-MarkdownHeadingCollapsed": true,
"tags": []
},
"source": [
"## Create initial configuration"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"h2 = molecule(\"H2\")\n",
"o2 = molecule(\"O2\")\n",
"h2o = molecule(\"H2O\")\n",
"\n",
"write(\"h2.xyz\", h2)\n",
"write(\"o2.xyz\", o2)\n",
"write(\"h2o.xyz\", h2o)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"h2 = Molecule.from_file(\"h2.xyz\")\n",
"o2 = Molecule.from_file(\"o2.xyz\")\n",
"h2o = Molecule.from_file(\"h2o.xyz\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"molecules = []\n",
"\n",
"for m, number in zip([h2, o2], [128, 64]):\n",
" molecules.append(\n",
" {\n",
" \"name\": m.composition.to_pretty_string(),\n",
" \"number\": number,\n",
" \"coords\": m,\n",
" }\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Atoms(symbols='H256O128', pbc=True, cell=[30.0, 30.0, 30.0])\n"
]
}
],
"source": [
"tolerance = 2.0\n",
"input_gen = PackmolBoxGen(\n",
" tolerance=tolerance,\n",
" seed=1,\n",
")\n",
"margin = 0.5 * tolerance\n",
"\n",
"a = 30\n",
"\n",
"packmol_set = input_gen.get_input_set(\n",
" molecules=molecules,\n",
" box=[margin, margin, margin, a - margin, a - margin, a - margin],\n",
")\n",
"packmol_set.write_input(\".\")\n",
"packmol_set.run(\".\")\n",
"\n",
"atoms = read(\"packmol_out.xyz\")\n",
"atoms.cell = [a, a, a]\n",
"atoms.pbc = True\n",
"\n",
"print(atoms)\n",
"\n",
"write(f'{atoms.get_chemical_formula()}.extxyz', atoms)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run workflow"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Atoms(symbols='H256O128', pbc=True, cell=[30.0, 30.0, 30.0])\n"
]
}
],
"source": [
"atoms = read(\"H256O128.extxyz\")\n",
"print(atoms)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"#!/bin/bash\n",
"\n",
"#SBATCH -A matgen\n",
"#SBATCH --mem=0\n",
"#SBATCH -t 00:30:00\n",
"#SBATCH -N 1\n",
"#SBATCH -q debug\n",
"#SBATCH -C gpu\n",
"#SBATCH -J combustion-water\n",
"source ~/.bashrc\n",
"module load python\n",
"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\n",
"/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",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n",
"Perhaps you already have a cluster running?\n",
"Hosting the HTTP server on port 38693 instead\n",
" warnings.warn(\n",
"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",
"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"
]
}
],
"source": [
"nodes_per_alloc = 1\n",
"gpus_per_alloc = 4\n",
"ntasks = 1\n",
"\n",
"# cluster_kwargs = dict(\n",
"# cores=1,\n",
"# memory=\"64 GB\",\n",
"# shebang=\"#!/bin/bash\",\n",
"# account=\"matgen\",\n",
"# walltime=\"02:00:00\",\n",
"# job_mem=\"0\",\n",
"# job_script_prologue=[\n",
"# \"source ~/.bashrc\",\n",
"# \"module load python\",\n",
"# \"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\",\n",
"# ],\n",
"# job_directives_skip=[\"-n\", \"--cpus-per-task\", \"-J\"],\n",
"# job_extra_directives=[\n",
"# \"-J combustion-water\",\n",
"# \"-q regular\",\n",
"# f\"-N {nodes_per_alloc}\",\n",
"# \"-C gpu\",\n",
"# f\"-G {gpus_per_alloc}\",\n",
"# f\"--exclusive\",\n",
"# # \"--time-min=00:30:00\",\n",
"# # \"--comment=1-00:00:00\",\n",
"# # \"--signal=B:USR1@60\",\n",
"# # \"--requeue\",\n",
"# # \"--open-mode=append\"\n",
"# ],\n",
"# death_timeout=86400\n",
"# )\n",
"\n",
"# cluster = SLURMCluster(**cluster_kwargs)\n",
"\n",
"cluster_kwargs = {\n",
" \"cores\": 1,\n",
" \"memory\": \"64 GB\",\n",
" \"shebang\": \"#!/bin/bash\",\n",
" \"account\": \"matgen\",\n",
" \"walltime\": \"00:30:00\",\n",
" \"job_mem\": \"0\",\n",
" \"job_script_prologue\": [\n",
" \"source ~/.bashrc\",\n",
" \"module load python\",\n",
" \"source activate /pscratch/sd/c/cyrusyc/.conda/mlip-arena\",\n",
" ],\n",
" \"job_directives_skip\": [\"-n\", \"--cpus-per-task\", \"-J\"],\n",
" \"job_extra_directives\": [f\"-N {nodes_per_alloc}\", \"-q debug\", \"-C gpu\", \"-J combustion-water\"],\n",
"}\n",
"cluster = SLURMCluster(**cluster_kwargs)\n",
"\n",
"print(cluster.job_script())\n",
"cluster.adapt(minimum_jobs=2, maximum_jobs=2)\n",
"client = Client(cluster)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"@flow(task_runner=DaskTaskRunner(address=client.scheduler.address), log_prints=True)\n",
"def combustion(atoms: Atoms):\n",
" futures = []\n",
"\n",
" for model in MLIPEnum:\n",
" future = MD.submit(\n",
" atoms=atoms,\n",
" calculator_name=model,\n",
" calculator_kwargs=None,\n",
" ensemble=\"nvt\",\n",
" dynamics=\"nose-hoover\",\n",
" time_step=None,\n",
" ase_md_kwargs=dict(ttime=25 * units.fs, pfactor=None),\n",
" total_time=1000_000,\n",
" temperature=[300, 3000, 3000, 300],\n",
" pressure=None,\n",
" md_velocity_seed=0,\n",
" traj_file=Path(REGISTRY[model.name][\"family\"])\n",
" / f\"{model.name}_{atoms.get_chemical_formula()}.traj\",\n",
" traj_interval=1000,\n",
" restart=True,\n",
" )\n",
"\n",
" futures.append(future)\n",
" \n",
" return [future.result() for future in futures]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<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",
"</pre>\n"
],
"text/plain": [
"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"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<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",
"</pre>\n"
],
"text/plain": [
"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"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<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",
"</pre>\n"
],
"text/plain": [
"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"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<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",
"Traceback (most recent call last):\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 652, in run_context\n",
" yield self\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 696, in run_flow_sync\n",
" engine.call_flow_fn()\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 675, in call_flow_fn\n",
" result = call_with_parameters(self.flow.fn, self.parameters)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 206, in call_with_parameters\n",
" return fn(*args, **kwargs)\n",
" ^^^^^^^^^^^^^^^^^^^\n",
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in combustion\n",
" return [future.result() for future in futures]\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in <listcomp>\n",
" return [future.result() for future in futures]\n",
" ^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py\", line 132, in result\n",
" future_result = self._wrapped_future.result(timeout=timeout)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 328, in result\n",
" return self.client.sync(self._result, callback_timeout=timeout)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 336, in _result\n",
" raise exc.with_traceback(tb)\n",
"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",
"</pre>\n"
],
"text/plain": [
"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",
"Traceback (most recent call last):\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 652, in run_context\n",
" yield self\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 696, in run_flow_sync\n",
" engine.call_flow_fn()\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/flow_engine.py\", line 675, in call_flow_fn\n",
" result = call_with_parameters(self.flow.fn, self.parameters)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect/utilities/callables.py\", line 206, in call_with_parameters\n",
" return fn(*args, **kwargs)\n",
" ^^^^^^^^^^^^^^^^^^^\n",
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in combustion\n",
" return [future.result() for future in futures]\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/tmp/ipykernel_892374/2043615938.py\", line 26, in <listcomp>\n",
" return [future.result() for future in futures]\n",
" ^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/prefect_dask/task_runners.py\", line 132, in result\n",
" future_result = self._wrapped_future.result(timeout=timeout)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 328, in result\n",
" return self.client.sync(self._result, callback_timeout=timeout)\n",
" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
" File \"/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/distributed/client.py\", line 336, in _result\n",
" raise exc.with_traceback(tb)\n",
"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"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<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",
"</pre>\n"
],
"text/plain": [
"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"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "KilledWorker",
"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.",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKilledWorker\u001b[0m Traceback (most recent call last)",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"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",
"\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."
]
}
],
"source": [
"results = combustion(atoms)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "mlip-arena",
"language": "python",
"name": "mlip-arena"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}
|