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# Getting Started
## Environments
Currently, Ubuntu 16.04 is officially supported as development environment.
Other environments may be available but not confirmed.
## How to compile your own model
### What should we preapare
- Tensorflow model file (`.pb` file)
- TensorFlow model file should be frozen. [[How to freeze?]](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py)
- Only inference operations are supported. Training operations are not supported yet.
- Quantization is not yet supported.
- `device` attribute should not have `GPU` value.
- Model information file (`.info` file)
- `.info` file should include 4 things.
- Specification of input or output
- name of input/output node
- type of input/output node
- shape of input/output node
- Example format is written below.
```
# input/output, node_name, node_type, node_shape
input, input:0, TF_FLOAT, [1, 299, 299, 3]
output, InceptionV3/Predictions/Reshape_1:0, TF_FLOAT, [1, 1001]
```
### How to compile
1. Generate `nnpkg` using `.pb` file and `.info` file.
```sh
tf2nnpkg --graphdef <model.pb> --info <model.info> -o <path/to/generate>
```
1. Check if all files are generated correctly.
- Directory name of `nnpkg` is prefix of `.pb` file.
- For example, if there is `model.pb` file, directory name will be `model`.
```
path/to/generate
└ model
├ model.circle
└ metadata
└ MANIFEST
```
1. Check if `MANIFEST` contents are correct.
```sh
$ cat path/to/generate/model/metadata/MANIFEST
{
"major-version" : "1",
"minor-version" : "0",
"patch-version" : "0",
"models" : [ "model.circle" ],
"model-types" : [ "circle" ]
}
```
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