def _create_snapshot(self):
reals = {}
for real in self.get_active_reals():
reals[str(real.get_iens())] = Realization(
active=True,
status=state.REALIZATION_STATE_WAITING,
)
for step in real.get_steps():
reals[str(real.get_iens())].steps[str(step.get_id())] = Step(
status=state.STEP_STATE_UNKNOWN
)
for job in step.get_jobs():
reals[str(real.get_iens())].steps[str(step.get_id())].jobs[
str(job.get_id())
] = Job(
status=state.JOB_STATE_START,
data={},
name=job.get_name(),
)
top = SnapshotDict(
reals=reals,
status=state.ENSEMBLE_STATE_UNKNOWN,
metadata=self.get_metadata(),
)
return Snapshot(top.dict())
def full_snapshot() -> Snapshot:
real = Realization(
status=REALIZATION_STATE_UNKNOWN,
active=True,
steps={
"0":
Step(
status="",
jobs={
"0":
Job(
start_time=dt.now(),
end_time=dt.now(),
name="poly_eval",
status=JOB_STATE_START,
error="error",
stdout="std_out_file",
stderr="std_err_file",
data={
CURRENT_MEMORY_USAGE: "123",
MAX_MEMORY_USAGE: "312",
},
),
"1":
Job(
start_time=dt.now(),
end_time=dt.now(),
name="poly_postval",
status=JOB_STATE_START,
error="error",
stdout="std_out_file",
stderr="std_err_file",
data={
CURRENT_MEMORY_USAGE: "123",
MAX_MEMORY_USAGE: "312",
},
),
},
)
},
)
snapshot = SnapshotDict(
status=ENSEMBLE_STATE_STARTED,
reals={},
)
for i in range(0, 100):
snapshot.reals[str(i)] = copy.deepcopy(real)
return Snapshot(snapshot.dict())
pytest.param(
[
CloudEvent(
{"source": "/", "type": ids.EVTYPE_EE_SNAPSHOT},
data={
**(build_snapshot(["0", "1"]).to_dict()),
"iter": 0,
},
),
CloudEvent(
{"source": "/", "type": ids.EVTYPE_EE_SNAPSHOT_UPDATE},
data={
**(
build_partial(["0", "1"])
.update_step(
"0", "0", Step(status=state.STEP_STATE_SUCCESS)
)
.to_dict()
),
"iter": 0,
},
),
],
[("_phase_count", 1)],
0.5,
id="ensemble_experiment_50",
),
pytest.param(
[
CloudEvent(
{"source": "/", "type": ids.EVTYPE_EE_SNAPSHOT},
def _create_snapshot_dict(
self,
run_context: ErtRunContext,
detailed_progress: typing.Tuple[typing.Dict, int],
iter_: int,
) -> typing.Optional[SnapshotDict]:
"""create a snapshot of a run_context and detailed_progress.
detailed_progress is expected to be a tuple of a realization_progress
dict and iteration number. iter_ represents the current assimilation
cycle."""
self._set_iter_queue(iter_, self._model._job_queue)
snapshot = SnapshotDict(
status=ENSEMBLE_STATE_STARTED,
reals={},
metadata={"iter": iter_},
)
forward_model = self._model.get_forward_model()
iter_to_progress, progress_iter = detailed_progress
if progress_iter != iter_:
logger.debug(
f"run_context iter ({iter_}) and detailed_progress ({progress_iter} iter differed"
)
if iter_ in self._iter_queue and self._iter_queue[iter_] is not None:
queue_snapshot = self._iter_queue[iter_].snapshot()
else:
queue_snapshot = None
enumerated = 0
for iens, run_arg in _enumerate_run_context(run_context):
real_id = str(iens)
enumerated += 1
if not _is_iens_active(iens, run_context):
continue
status = JobStatusType.JOB_QUEUE_UNKNOWN
if queue_snapshot is not None and iens in queue_snapshot:
status = JobStatusType.from_string(queue_snapshot[iens])
snapshot.reals[real_id] = Realization(
status=queue_status_to_real_state(status),
active=True,
steps={})
step = Step(status="", jobs={})
snapshot.reals[real_id].steps["0"] = step
for index in range(0, len(forward_model)):
ext_job = forward_model.iget_job(index)
step.jobs[str(index)] = Job(name=ext_job.name(),
status=JOB_STATE_START,
data={})
progress = iter_to_progress[iter_].get(iens, None)
if not progress:
continue
jobs = progress[0]
for idx, fm in enumerate(jobs):
job = step.jobs[str(idx)]
job.start_time = fm.start_time
job.end_time = fm.end_time
job.name = fm.name
job.status = _map_job_state(fm.status)
job.error = fm.error
job.stdout = fm.std_out_file
job.stderr = fm.std_err_file
job.data = {
CURRENT_MEMORY_USAGE: fm.current_memory_usage,
MAX_MEMORY_USAGE: fm.max_memory_usage,
}
if enumerated == 0:
logger.debug("enumerated 0 items from run_context, it is gone")
return None
return snapshot
"source": "/",
"type": ids.EVTYPE_EE_SNAPSHOT
},
data={
**(build_snapshot(["0", "1"]).to_dict()),
"iter": 0,
},
),
CloudEvent(
{
"source": "/",
"type": ids.EVTYPE_EE_SNAPSHOT_UPDATE
},
data={
**(build_partial(["0", "1"]).update_step(
"0", "0", Step(status=state.STEP_STATE_SUCCESS)).to_dict(
)),
"iter":
0,
},
),
],
[("_phase_count", 1)],
0.5,
id="ensemble_experiment_50",
),
pytest.param(
[
CloudEvent(
{
"source": "/",