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.