data-maker/pipeline.py

#!/usr/bin/env python3
	@staticmethod
		df = pd.read_gbq(SQL,credentials=credentials,dialect='standard')
		else :

	def generate(self,args):
				dtype = str
		#
							# for name in args['ignore']['columns'] :
		# for name in cols :
		# 	_args['data'][name] = _dc[name]
	# if 'file' in args :
		# 		args['partition'] = index
		# 		args['data'] = DATA[index]
		# 		if int(args['num_gpu']) > 1 :
		# 			args['gpu'] = index
		# 		else:
		# 			args['gpu']=0
		#
		# trainer.train(**args)