def set_model_name(job: Job) -> None:
if job.create_models:
if job.predictive_model.model_path != '':
job.predictive_model = duplicate_orm_row(PredictiveModel.objects.filter(pk=job.predictive_model.pk)[0])
job.predictive_model.save()
job.save()
if job.clustering.clustering_method != ClusteringMethods.NO_CLUSTER.value:
job.clustering.model_path = 'cache/model_cache/job_{}-split_{}-clusterer-{}-v0.sav'.format(
job.id,
job.split.id,
job.type)
job.clustering.save()
if job.type == JobTypes.UPDATE.value:
job.type = JobTypes.PREDICTION.value #TODO: Y am I doing this?
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v{}.sav'.format(
job.id,
job.split.id,
job.type,
str(time.time()))
else:
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v0.sav'.format(
job.id,
job.split.id,
job.type)
job.predictive_model.model_path = predictive_model_filename
job.predictive_model.save()
job.save()
def set_model_name(job: Job) -> None:
if job.create_models:
if job.predictive_model.model_path != '':
# job.predictive_model = duplicate_orm_row(PredictiveModel.objects.filter(pk=job.predictive_model.pk)[0]) #todo: replace with simple CREATE
job.predictive_model = PredictiveModel.init(
job.predictive_model.get_full_dict(
) #todo: doublecheck me, are you sure get_full_dict is returning everything needed?
) #todo: futurebug if object changes
job.predictive_model.save()
job.save()
if job.clustering.clustering_method != ClusteringMethods.NO_CLUSTER.value:
job.clustering.model_path = 'cache/model_cache/job_{}-split_{}-clusterer-{}-v0.sav'.format(
job.id, job.split.id, job.type)
job.clustering.save()
if job.type == JobTypes.UPDATE.value:
job.type = JobTypes.PREDICTION.value #TODO: Y am I doing this?
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v{}.sav'.format(
job.id, job.split.id, job.type, str(time.time()))
else:
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v0.sav'.format(
job.id, job.split.id, job.type)
job.predictive_model.model_path = predictive_model_filename
job.predictive_model.save()
job.save()
def save_models(models: dict, job: Job):
logger.info("\tStart saving models of JOB {}".format(job.id))
if job.clustering.clustering_method != ClusteringMethods.NO_CLUSTER.value:
clusterer_filename = 'cache/model_cache/job_{}-split_{}-clusterer-{}-v0.sav'.format(
job.id, job.split.id, job.type)
joblib.dump(models[ModelType.CLUSTERER.value], clusterer_filename)
job.clustering.model_path = clusterer_filename
job.clustering.save()
job.save()
if job.type == JobTypes.UPDATE.value:
job.type = JobTypes.PREDICTION.value #TODO: Y am I doing this?
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v{}.sav'.format(
job.id, job.split.id, job.type, str(time.time()))
else:
predictive_model_filename = 'cache/model_cache/job_{}-split_{}-predictive_model-{}-v0.sav'.format(
job.id, job.split.id, job.type)
joblib.dump(models[job.predictive_model.predictive_model],
predictive_model_filename)
job.predictive_model.model_path = predictive_model_filename
job.predictive_model.save()
job.save()
