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# nnc
Neural Network Compiler
### DESCRIPTION
nnc is a neural network compiler that transforms neural networks of various formats into source or machine code.
> At this moment only two NN are supported (MobileNet and InceptionV3) in Tensorflow Lite or Caffe format.
### SYNOPSIS
nnc OPTIONS
### OPTIONS
--help, -h - print usage and exit
--caffe - treat input file as Caffe model
--tflite - treat input file as Tensor Flow Lite model
--target - select target language to emit for given architecture.
Valid values are 'x86-c++', 'interpreter'
--nnmodel, -m - specify input file with NN model
--output, -o - specify name for output files
--output-dir, -d - specify directory for output files
--input-model-data - interpreter option: specify file with neural network input data.
This file contains array of floats in binary form
--input-node - interpreter option: set input node in Computational Graph
--output-node - interpreter option: set output node in Computational Graph
### USAGE
Assuming that user has already installed nnc as follows:
```
$ cmake <path_to_nnc_sources> -DCMAKE_INSTALL_PREFIX=<path_to_install>
$ make all && make install
```
Also assuming that we have tflite model (for example inceptionv3.tflite)
**1. Running nnc in interpreter mode:**
```
<path_to_install>/bin/nnc \
--nnmodel inceptionv3.tflite \
--target interpreter \
--input-model-data data.file \
--input-node input --output-node output
```
**2. Running to generate C/C++ source code:**
```
<path_to_install>/bin/nnc \
--nnmodel inceptionv3.tflite \
--target x86-c++ \
--output inception \
--output-dir output_dir
```
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