def DumpDataset(unicodedatasetindex = None):
if unicodedatasetindex != None:
# try:
datasetindex = int(unicodedatasetindex)
filepath = 'dataset/' + random_file_name(None, 'txt')
# DB
oldsinfo = OnlineDataset.objects.get(id = datasetindex)
dsinfo = Dataset()
dsinfo.name = oldsinfo.name
dsinfo.path = filepath
dsinfo.filetype = 'TXT'
dsinfo.head = oldsinfo.head
dsinfo.hashead = oldsinfo.hashead
dsinfo.attr_delim = ','
dsinfo.record_delim = '\n'
dsinfo.save()
#file
output = open(settings.MEDIA_ROOT + filepath, 'w')
oldataset = OnlineDataset.ViewDataset(datasetindex)
if oldataset == None:
return 'false'
output.write(','.join(map(str, oldataset.head)) + '\n')
for line in oldataset.items:
output.write(','.join(map(str, line)) + '\n')
output.close()
return 'true'
# except:
# return 'false'
return 'false'
def CreateTrain(unicodemodelindex = None):
'''
mdinfo: MLModel
traintask: TrainingTask
mdruntask: ModelRunTask
'''
if unicodemodelindex != None:
modelindex = int(unicodemodelindex)
mdinfo = MLModel.objects.get(id = modelindex)
if mdinfo != None:
# New Task in DB model
traintask = TrainingTask()
traintask.name = ''
traintask.modelprototype = mdinfo.modeltype
traintask.modelindex = modelindex
traintask.save()
# Modify Model Record
mdinfo.modelstatus = 'TRAINING'
mdinfo.save()
# Open dataset on db
if mdinfo.datasetprototype == 'LOCAL':
dsinfo = Dataset.GetDataset(mdinfo.datasetindex)
else:
dsinfo = OnlineDataset.GetDataset(mdinfo.datasetindex)
# Create Machine Learning Instance
# Get TrainingTask id
mdruntask = ModelRunTask(TrainingTask.objects.all()[len(TrainingTask.objects.all())-1].id, mdinfo, dsinfo)
mdruntask.Start()
# now Training is over
mdinfo.modelstatus = 'TRAINED'
# save training result
mdinfo.model_path = 'cache/models/'+random_file_name(None,'trd')
mdruntask.Save(mdinfo.model_path)
mdinfo.save()
traintask.delete()
return 'true'
return 'false'
def get_model_upload_to(instance, filename):
return settings.MEDIA_ROOT + 'upload/models/' + random_file_name(filename)
def get_upload_to(instance, filename):
# paths = { 'I':'images/', 'V':'videos/', 'A':'audio/', 'D':'documents'/ }
# return settings.MEDIA_ROOT + 'content/' + paths[instance.content_type] + filename
return 'dataset/' + random_file_name(filename)
