Update README file for cpp-package and provide README file for exampl…

…e directory.

cpp-package/README.md

@@ -1,21 +1,42 @@
 # MXNet C++ Package
 
-To build the C++ package, please refer to [this guide](<https://mxnet.incubator.apache.org/install/build_from_source#build-the-c-package>).
+The MXNet C++ Package provides C++ API bindings to the users of MXNet.  Currently, these bindings are not available as standalone package.
+The users of these bindings are required to build this package as mentioned below.
 
-A basic tutorial can be found at <https://mxnet.incubator.apache.org/tutorials/c++/basics.html>.
+## Building C++ Package
 
-The example directory contains examples for you to get started.
+The cpp-package directory contains the implementation of C++ API. As mentioned above, users are required to build this directory or package before using it.
+**The cpp-package is built while building the MXNet shared library, *libmxnet.so*.**
+
+###Steps to build the C++ package:
+1.  Building the MXNet C++ package requires building MXNet from source.
+2.  Clone the MXNet github repository **recursively** to ensure the code in submodules is available for building MXNet.
+3.  Install the [prerequisites](<https://mxnet.incubator.apache.org/install/build_from_source#prerequisites>), desired [BLAS libraries](<https://mxnet.incubator.apache.org/install/build_from_source#blas-library>) and optional [OpenCV, CUDA, and cuDNN](<https://mxnet.incubator.apache.org/install/build_from_source#optional>) for building MXNet from source.
+4.  There is a configuration file for make, [make/config.mk](<https://github.com/apache/incubator-mxnet/blob/master/make/config.mk>) that contains all the compilation options. You can edit this file and set the appropriate options prior to running the **make** command.
+5.  Please refer to  [platfrom specific build instructions](<https://mxnet.incubator.apache.org/install/build_from_source#build-instructions-by-operating-system>) and available [build configurations](https://mxnet.incubator.apache.org/install/build_from_source#build-configurations) for more details. 
+5.  For enabling the build of C++ Package, set the **USE__CPP__PACKAGE = 1** in [make/config.mk](<https://github.com/apache/incubator-mxnet/blob/master/make/config.mk>). Optionally, the compilation flag can also be specified on **make** command line as follows:
+	```
+	make -j USE_CPP_PACKAGE=1 
+	```
+
+## Usage
+
+In order to consume the C++ API please follow the steps below
 
-## Building C++ examples in examples folder
+1. Ensure that the MXNet shared library is built from source with the **USE__CPP__PACKAGE = 1**.
+2. Include the [MxNetCpp.h](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/include/mxnet-cpp/MxNetCpp.h>) in the program that is going to consume MXNet C++ API.
+	```
+	#include <mxnet-cpp/MxNetCpp.h>
+	```
+3. While building the program, ensure that the correct paths to the directories containing header files and MxNet shared library.
+4. The program links MxNet shared library dynamically. Hence the library needs to be accessible to the program during the runtime. This can be achieved by including the path to shared library to environment variable such as LD_LIBRARY_PATH.
 
-From cpp-package/examples directory
--  Build all examples in release mode: **make all**
--  Build all examples in debug mode : **make debug**
 
-By default, the examples are build to be run on GPU.
-To build examples to run on CPU:
-- Release: **make all MXNET_USE_CPU=1**  
-- Debug: **make debug MXNET_USE_CPU=1**  
+## Tutorial
 
+A basic tutorial can be found at <https://mxnet.incubator.apache.org/tutorials/c++/basics.html>.
+
+## Examples
+
+The example directory contains examples for you to get started.
 
-The makefile will also download the necessary data files and store in data folder. (The download will take couple of minutes, but will be done only once on a fresh installation.)

cpp-package/example/README.md

@@ -0,0 +1,112 @@
+# MXNet C++ Package Examples
+
+## Building C++ examples
+
+The examples are built while building the MXNet library and cpp-package from source . However, they can be built manually as follows
+
+From cpp-package/examples directory
+
+-  Build all examples in release mode: **make all**
+-  Build all examples in debug mode: **make debug**
+
+By default, the examples are build to be run on GPU. To build examples to run on CPU:
+
+-  Release: **make all MXNET\_USE\_CPU=1**
+-  Debug: **make debug MXNET\_USE\_CPU=1**
+
+The examples that are build to be run on GPU may not work on the non-GPU machines.
+The makefile will also download the necessary data files and store in data folder. (The download will take couple of minutes, but will be done only once on a fresh installation.)
+
+
+## Examples
+
+This directory contains following examples. In order to run the examples, ensure that the path to the MXNet shared library is added to the OS specific environment variable such as _LD\_LIBRARY\_PATH_ .
+
+### [alexnet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/alexnet.cpp>)
+
+The example implements C++ version of AlexNet. The networks trains the MNIST data. The number of epochs can be specified as command line arguement. For example:
+	```
+	./alexnet 10
+	```
+
+### [charRNN.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/chaRNN.cpp>)
+
+The code implements C++ version charRNN for mxnet\example\rnn\char-rnn.ipynb with MXNet.cpp API. The generated params file is compatiable with python version. The train() and predict() has been verified with original data samples.
+
+The example expects arguments as follows:
+
+```
+	./charRNN train [BuildIn\ [TImeMajor] {corpus file} { batch size} { max epoch} [{starting epoch}]
+	./charRNN predict [BuildIn\ [TImeMajor] {param file} { batch size} { max epoch} [{starting epoch}]
+```
+
+### [googlenet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/googlenet.cpp>)
+
+The code implements GoogLeNet/Inception network using C++ API. The example uses MNIST data to train the network. The number of epochs can be specified in the command line as follows. If not specified, the model trains for 100 epochs.
+
+```
+./googlenet 10
+```
+
+### [mlp.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/mlp.cpp>)
+
+The code implements multilayer perceptron from scratch. The example creates its own dummy data to train the model. The example does not require command line parameters. It trains the model for 20000 iterations.
+
+```
+./mlp
+```
+
+### [mlp_cpu.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/mlp_cpu.cpp>)
+
+The code implements multilayer perceptron to train the MNIST data. The code demonstrates the use of "SimpleBind"  C++ API and MNISTIter. The example is designed to work on CPU. The example does not require command line parameters.
+
+```
+./mlp_cpu
+```
+
+### [mlp_gpu.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/mlp_gpu.cpp>)
+The code implements multilayer perceptron to train the MNIST data. The code demonstrates the use of "SimpleBind"  C++ API and MNISTIter. The example is designed to work on GPU. The example does not require command line paratmeters.
+
+```
+./mlp_gpu
+```
+
+### [mlp_csv.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/mlp_csv.cpp>)
+The code implements multilayer perceptron to train the MNIST data. The code demonstrates the use of "SimpleBind"  C++ API and CSVIter. The CSVIter can iterate data that is in CSV format. The example can be run on CPU or GPU. The example usage is as follows:
+
+```
+mlp_csv --train mnist_training_set.csv --test mnist_test_set.csv --epochs 10 --batch_size 100 --hidden_units "128,64,64 [--gpu]"
+```
+
+### [resnet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/resnet.cpp>)
+
+The code implements resnet model using C++ API. The model is used to train MNIST data. The number of epochs for training the model can be specified on the command line. By default, model is trained for 100 epochs.
+
+```
+./resnet 10
+```
+
+### [lenet.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/lenet.cpp>)
+
+The code implements lenet model using C++ API. It uses MNIST training data in CSV format to train the network. The example does not use built-in CSVIter to read the data from CSV file. The number of epochs can be specified on the command line. By default, the mode is trained for 100000 epochs.
+
+```
+./lenet 10
+```
+### [lenet\_with\_mxdataiter.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/mlp_cpu.cpp>)
+
+The code implements lenet model using C++ API. It uses MNIST training data to train the network. The example uses built-in MNISTIter to read the data. The number of epochs can be specified on the command line. By default, the mode is trained for 100 epochs.
+
+```
+./lenet\_with\_mxdataiter 10
+```
+
+In addition, there is `run_lenet_with_mxdataiter.sh` that downloads the mnist data and run `lenet_with_mxdataiter` example.
+
+###[inception_bn.cpp](<https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/inception_bn.cpp>)
+
+The code implements Inception network using C++ API with batch normalization. The example uses MNIST data to train the network. The model trains for 100 epochs.
+
+```
+./inception_bn
+```