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: