== Author of the README ==
    Wengong Jin,
    Shanghai Jiao Tong University
    email: acmgokun@gmail.com

    Hakan Erdogan
    MERL, Sabanci University
    email: haerdogan@sabanciuniv.edu

    Yu Zhang, Leo Liu
    CSAIL, Massachusetts Institute of Technology
    email: yzhang87@csail.mit.edu
    email: leoliu_cu@sbcglobal.net

== Preeliminaries ==
To build the cpu version, you have to install intel MKL blas library or ACML library first. Note that ACML is free, where MKL may not be.

for MKL:
1. Download from https://software.intel.com/en-us/intel-mkl
2. You can modify variable MKL_PATH in makefile.cpu to change your mkl path.
Then add ${MKL_PATH}/mkl/lib/intel64, ${MKL_PATH}/mkl/lib/mic, ${MKL_PATH}/compiler/lib/intel64. ${MKL_PATH}/compiler/lib/mic to your ${LD_LIBRARY_PATH} to make sure the program links the library correctly.

for ACML:
1. Download from http://developer.amd.com/tools-and-sdks/cpu-development/amd-core-math-library-acml/
2. Modify ACML_PATH in the makefile.cpu and makefile.gpu to provide your ACML library path.
You need to add ${ACML_PATH}/lib to your ${LD_LIBRARY_PATH}.

To build the gpu version, you have to install NIVIDIA CUDA first
You can modify the path CUDA_PATH in makefile.cpu to change your cuda path
We use cuda-7.0 as default.
Then add ${CUDA_PATH}/lib, ${CUDA_PATH}/lib64 to your ${LD_LIBRARY_PATH} to make sure the program links to the library correctly.

... TODO: add documentation on nvml lib

== Build ==
To build the cpu version, run
	make DEVICE=cpu 
To build the gpu version, run
	make
To clean the compile, just run
	make DEVICE=cpu clean
or
	make clean

For release version, just add BUILDTYPE=release to the make command line.

== Run ==
All executables are in bin/ directory:
	cn.exe: The main executable for CNTK
	*.so: shared library for corresponding reader, these readers will be linked and loaded dynamically at runtime.

To run the executable, make sure bin/ is in your ${LD_LIBRARY_PATH}, if not, running cn.exe will fail when cn.exe tries to link the corresponding reader. Once it's done, run in command line:
	./cn.exe configFile=${your config file}

== Kaldi Reader ==
This is a HTKMLF reader and kaldi writer (for decode)

To build the cpu/gpu version, run
    make -f Makefile_kaldi.cpu/gpu

The feature section is like:

writer=[
    writerType=KaldiReader
    readMethod=blockRandomize
    frameMode=false
    miniBatchMode=Partial
    randomize=Auto
    verbosity=1
    ScaledLogLikelihood=[
        dim=$labelDim$
        Kaldicmd="ark:-" # will pipe to the Kaldi decoder latgen-faster-mapped
        scpFile=$outputSCP$ # the file key of the features
    ]
]

== Kaldi2 Reader ==
This is a kaldi reader and kaldi writer (for decode)

To build the cpu/gpu version, run
    make -f Makefile_kaldi2.cpu/gpu


The features section is different:

features=[
    dim=
    rx=
    scpFile=
    featureTransform=
]

rx is a text file which contains:

    one Kaldi feature rxspecifier readable by RandomAccessBaseFloatMatrixReader.
    'ark:' specifiers don't work; only 'scp:' specifiers work.

scpFile is a text file generated by running:

    feat-to-len FEATURE_RXSPECIFIER_FROM_ABOVE ark,t:- > TEXT_FILE_NAME

    scpFile should contain one line per utterance.

    If you want to run with fewer utterances, just shorten this file.
    (It will load the feature rxspecifier but ignore utterances not present in scpFile).

featureTransform is the name of a Kaldi feature transform file:
    
    Kaldi feature transform files are used for stacking / applying transforms to features.

    An empty string (if permitted by the config file reader?) or the special string: NO_FEATURE_TRANSFORM
    says to ignore this option.

********** Labels **********

The labels section is also different.

labels=[
    mlfFile=
    labelDim=
    labelMappingFile=
]

Only difference is mlfFile. mlfFile is a different format now. It is a text file which contains:

    one Kaldi label rxspecifier readable by Kaldi's copy-post binary.