def __findBestModel(self, model: str) -> str:
pred = Predictor()
pdHandler = PrometheusDataHandler(model)
data = pdHandler.get_data()
results = {}
count = 0.0
logging.debug("Running findBestModel in SimpleLoadBalance")
#data = { ip, vals }
for ip in data:
# data_values = [ (name,value) ]
values = data[ip]
data_values = pred.accuracy(values)
for r in data_values:
# print(r)
try:
results[r[1]] += r[0]
#some times it is better to ask for forgiveness than permission :)
except KeyError as e:
results[r[1]] = r[0]
count += 1.0
##
#Here we take the average between all of the nodes
##
for k in results.keys():
val = results[k]
results[k] = val / count
order_acc = sorted(results.items(), key=operator.itemgetter(1))
return order_acc[0][0]
def process(self, request): model = request['model'] pdHandler = PrometheusDataHandler(model) data = pdHandler.get_data() pred = Predictor() for ip in data: values = data[ip] self.data_[ip] = pred.accuracy(values)
