data-maker/pipeline.py

#!/usr/bin/env python3
	@staticmethod

		data.maker.train(**_args)
			_args['batch_size'] = int(args['batch_size'])
		# 	df = pd.DataFrame(df[ int (partition) ],columns = columns)
		# We need to post the generate the data in order to :
	print ("..::: ",PIPELINE[index]['context'])