def get_prediction(request, pk1, pk2, pk3):
models = []
jobs = []
pk1 = int(pk1)
pk2 = int(pk2)
pk3 = int(pk3)
log = Log.objects.get(pk=pk1)
split, created = Split.objects.get_or_create(type='single',
original_log=log)
try:
if pk2 > 0:
model = PredModels.objects.get(pk=pk2)
models.append(model)
if pk3 > 0:
model = PredModels.objects.get(pk=pk3)
models.append(model)
except PredModels.DoesNotExist:
return Response({'error': 'not in database'},
status=status.HTTP_404_NOT_FOUND)
for model in models:
job = generate_run(pk1, model, model.id, split)
# django_rq.enqueue(training, jobrun, predictive_model)
django_rq.enqueue(runtime_task, job, model)
# os.system('python3 manage.py rqworker --burst')
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=201)
def create_multiple(request):
"""No request validation"""
payload = json.loads(request.body.decode('utf-8'))
try:
split = Split.objects.get(pk=payload['split_id'])
except Split.DoesNotExist:
return Response({'error': 'not in database'},
status=status.HTTP_404_NOT_FOUND)
# detect either or not a predictive_model to update has been specified otherwise train a new one.
if 'incremental_train' in payload['config'] and payload['config'][
'incremental_train']['base_model'] is not None:
jobs = update(split, payload)
elif payload['type'] in [e.value for e in PredictiveModels]:
jobs = generate(split, payload)
elif payload['type'] == JobTypes.LABELLING.value:
jobs = generate_labelling(split, payload)
else:
return Response(
{'error': 'type not supported'.format(payload['type'])},
status=status.HTTP_422_UNPROCESSABLE_ENTITY)
for job in jobs:
django_rq.enqueue(tasks.prediction_task, job.id)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=201)
def post_replay(request):
""" Post request to start a demo of a log arriving to server
:param request: json
:return: Response
"""
jobs = []
data = request.data
split_id = int(data['splitId'])
job_id = int(data['jobId'])
split = Split.objects.get(pk=split_id)
try:
training_initial_job = Job.objects.get(pk=job_id)
new_job = duplicate_orm_row(training_initial_job)
new_job.type = JobTypes.REPLAY.value
new_job.status = JobStatuses.CREATED.value
new_job.split = split
new_job.save()
except Job.DoesNotExist:
return Response({'error': 'Job ' + str(job_id) + ' not in database'},
status=status.HTTP_404_NOT_FOUND)
django_rq.enqueue(replay_task, new_job, training_initial_job)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=status.HTTP_201_CREATED)
def post_replay_prediction(request):
""" Post request to have a single prediction during the replay of a log
:param request: json
:return: Response
"""
jobs = []
job_id = int(request.query_params['jobId'])
training_initial_job_id = int(request.query_params['training_job'])
logger.info("Creating replay_prediction task")
try:
training_initial_job = Job.objects.get(pk=training_initial_job_id)
replay_job = Job.objects.filter(pk=job_id)[0]
replay_prediction_job = duplicate_orm_row(replay_job)
replay_prediction_job.parent_job = Job.objects.filter(pk=job_id)[0]
replay_prediction_job.type = JobTypes.REPLAY_PREDICT.value
replay_prediction_job.status = JobStatuses.CREATED.value
replay_prediction_job.save()
except Job.DoesNotExist:
return Response({'error': 'Job ' + str(job_id) + ' not in database'},
status=status.HTTP_404_NOT_FOUND)
logger.info("Enqueuing replay_prediction task ID {}".format(
replay_prediction_job.id))
log = import_log_from_string(request.data.decode('utf-8'))
django_rq.enqueue(replay_prediction_task, replay_prediction_job,
training_initial_job, log)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=status.HTTP_201_CREATED)
def post_prediction(request):
""" Post request to have a single static prediction
:param request: json
:return: Response
"""
jobs = []
data = request.data
job_id = int(data['jobId'])
split_id = int(data['splitId'])
split = Split.objects.get(pk=split_id)
try:
job = Job.objects.get(pk=job_id)
new_job = duplicate_orm_row(job)
new_job.type = JobTypes.RUNTIME.value
new_job.status = JobStatuses.CREATED.value
new_job.split = split
new_job.save()
except Job.DoesNotExist:
return Response({'error': 'Job ' + str(job_id) + ' not in database'},
status=status.HTTP_404_NOT_FOUND)
django_rq.enqueue(runtime_task, new_job)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=status.HTTP_201_CREATED)
def _serializer(object):
"""Assumed to be Django models"""
name = object.__class__.__name__
if name == 'Log':
data = LogSerializer(object).data
elif name == 'Job':
data = JobSerializer(object).data
elif name == 'XTrace':
data = TraceSerializer(object).data
else:
raise NotImplementedError("Websocket not implemented for class ".format(name))
return JSONRenderer().render({'type': name, 'data': data})
def post_replay_prediction(request):
""" Post request to have a single prediction during the replay of a log
:param request: json
:return: Response
"""
jobs = []
job_id = int(request.query_params['jobId'])
training_initial_job_id = int(request.query_params['training_job'])
logger.info("Creating replay_prediction task")
try:
training_initial_job = Job.objects.get(pk=training_initial_job_id)
replay_job = Job.objects.filter(pk=job_id)[0]
# replay_prediction_job = duplicate_orm_row(replay_job) #todo: replace with simple CREATE
replay_prediction_job = Job.objects.create(
created_date=replay_job.created_date,
modified_date=replay_job.modified_date,
error=replay_job.error,
status=replay_job.status,
type=replay_job.type,
create_models=replay_job.create_models,
case_id=replay_job.case_id,
event_number=replay_job.event_number,
gold_value=replay_job.gold_value,
results=replay_job.results,
parent_job=replay_job.parent_job,
split=replay_job.split,
encoding=replay_job.encoding,
labelling=replay_job.labelling,
clustering=replay_job.clustering,
predictive_model=replay_job.predictive_model,
evaluation=replay_job.evaluation,
hyperparameter_optimizer=replay_job.hyperparameter_optimizer,
incremental_train=replay_job.incremental_train)
replay_prediction_job.parent_job = Job.objects.filter(pk=job_id)[0]
replay_prediction_job.type = JobTypes.REPLAY_PREDICT.value
replay_prediction_job.status = JobStatuses.CREATED.value
replay_prediction_job.save()
except Job.DoesNotExist:
return Response({'error': 'Job ' + str(job_id) + ' not in database'},
status=status.HTTP_404_NOT_FOUND)
logger.info("Enqueuing replay_prediction task ID {}".format(
replay_prediction_job.id))
log = import_log_from_string(request.data.decode('utf-8'))
django_rq.enqueue(replay_prediction_task, replay_prediction_job,
training_initial_job, log)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=status.HTTP_201_CREATED)
def post_replay(request):
""" Post request to start a demo of a log arriving to server
:param request: json
:return: Response
"""
jobs = []
data = request.data
split_id = int(data['splitId'])
job_id = int(data['jobId'])
split = Split.objects.get(pk=split_id)
try:
training_initial_job = Job.objects.get(pk=job_id)
# new_job = duplicate_orm_row(training_initial_job) #todo: replace with simple CREATE
new_job = Job.objects.create(
created_date=training_initial_job.created_date,
modified_date=training_initial_job.modified_date,
error=training_initial_job.error,
status=training_initial_job.status,
type=training_initial_job.type,
create_models=training_initial_job.create_models,
case_id=training_initial_job.case_id,
event_number=training_initial_job.event_number,
gold_value=training_initial_job.gold_value,
results=training_initial_job.results,
parent_job=training_initial_job.parent_job,
split=training_initial_job.split,
encoding=training_initial_job.encoding,
labelling=training_initial_job.labelling,
clustering=training_initial_job.clustering,
predictive_model=training_initial_job.predictive_model,
evaluation=training_initial_job.evaluation,
hyperparameter_optimizer=training_initial_job.
hyperparameter_optimizer,
incremental_train=training_initial_job.incremental_train)
new_job.type = JobTypes.REPLAY.value
new_job.status = JobStatuses.CREATED.value
new_job.split = split
new_job.save()
except Job.DoesNotExist:
return Response({'error': 'Job ' + str(job_id) + ' not in database'},
status=status.HTTP_404_NOT_FOUND)
django_rq.enqueue(replay_task, new_job, training_initial_job)
serializer = JobSerializer(jobs, many=True)
return Response(serializer.data, status=status.HTTP_201_CREATED)
def modelList(request):
completed_jobs = Job.objects.filter(status=JobStatuses.COMPLETED.value,
type=JobTypes.PREDICTION.value,
create_models=True)
serializer = JobSerializer(completed_jobs, many=True)
return Response(serializer.data, status=200)
def post(request):
serializer = JobSerializer(data=request.data)
if serializer.is_valid():
serializer.save()
return Response(serializer.data, status=201)
return Response(serializer.errors, status=400)
