lstm2.py contains sequence to sequence mapping code. it creates a checkpoint and saves it after training.
preprocessing.py contains code for loading and normalizing and getting data in proper dimensions

testingfromckpt.py can be used to load trained model and use it for predictions.

lstm.py is incomplete sequence to sequence mapping code

clientAudioQoSAlgoData-20160815-181127.csv
	181127_80_22.csv	501-1509
	181127_22_83.csv	66324-67359

clientAudioQoSAlgoData-20160815-182409.csv
	182409_80_26		601-1721
	182409_26			1030-2206
	
qos_blake.csv
	blake_80_31					2900-4007
	
qos_blake2.csv
	blake2_80_35				1528-2704




seqtoseqmodel, seqtoseqmodel.meta, checkpoint and 
0.05_8/model.ckpt, 0.05_8/checkpoint, 0.05_8/model.ckpt.meta are files for storing the trained model


Trainign data is available at- //sw/pvt/rrewale/lstm/Data/