1. formatting data files: cd ./data/dnn_ordered_traces/ make # now only formatting is deleting the first column # you can check ./data/dnn_ordered_traces/*.num to confirm # maps for instructions and data are stored in ./data/dnn_ordered_traces/*.num.instr_map and ./data/dnn_ordered_traces/*.num.data_map, respectively. # But the maps were already taken care of. ( for now only instr_map is used ) 2. train: (e.g. dataset is gcc) make gcc.train # model files will be stored in ./gcc/ 3. test with test file: make gcc.test # prediction will be stored in ./gcc.pred 4. test each sample: check main.py, a demo is written in lines 122-190: pseudo code: 0) read LSTM model by saver.restore(...) 1) read batches of samples from test_reader (created from test file "./data/dnn_ordered_traces/gcc.num.test", then translated by instruction map ) 2) at each step, feed one sample into LSTM model by model.predict(...) 3) do initialization by model.init() You can modify this part of code.