def main(*argv):
sys.argv = argv[:]
# # def main(*argv):
# # sys.argv = argv[:]
args = sys.argv[1:]
# print(args)
# testCounter(*args)
justTest(*args)
from trainModel import kerasUtilities
kerasUtilities=kerasUtilities.KerasUtilities()
kerasUtilities.updateStatusOfTraining('./logs/UXEWJBAGBGDX/status.txt','Code Execution Completed')
from KerasModelSupport.views import ONNXExecution
def create_lockForModel():
global lockForModelLoad
lockForModelLoad = Lock()
# from SwaggerSchema.schemas import (loadModelSwagger,
# predictTestDataSwagger,
# unloadModelSwagger,
# )
from trainModel import kerasUtilities
from trainModel.mergeTrainingV2 import PMMLMODELSTORAGE
from trainModel.mergeTrainingV2 import NewModelOperations
kerasUtilities = kerasUtilities.KerasUtilities()
global PMMLMODELSTORAGE
class Scoring:
def getListOfModelinMemory():
global PMMLMODELSTORAGE
# print ('PMMLMODELSTORAGE',PMMLMODELSTORAGE)
moreDetails = []
for j in PMMLMODELSTORAGE:
temp_dict = {}
temp_dict['modelName'] = j
try:
temp_dict['inputShape'] = PMMLMODELSTORAGE[j]['inputShape']
except:
