Commit 91cbdbab authored by Matthieu Dorier's avatar Matthieu Dorier

added README

parent 298d55aa
# FlameStore
FlameStore is a storage system specifically designed to store
Keras models in the context of the CANDLE research workflows.
It is based on the [Mochi](https://www.mcs.anl.gov/research/projects/mochi/)
components developed at Argonne National Laboratory.
## Installing
FlameStore itself is purely written in Python. However It depends
on the Mochi components and their Python wrappers. It also depends
on Keras.
- [ ] _explain how to install the Mochi components_
- [ ] _explain how to install Keras_
To install FlameStore, use the following commands.
```
git clone https://xgitlab.cels.anl.gov/sds/flame-store.git
cd flame-store
python setup.py install
```
You can check that the installation worked by typping `import flamestore`
in a Python interpreter.
## Using FlameStore
The following example shows how to create a Workspace and store/load
Keras model to/from it. A more complete example can be found in the
_test_ directory of the source, which trains a 7-layer CNN model on
the MNIST dataset, stores the resuling model, reloads it, and checks
that the reloaded model performs the same way as the original one.
```python
from flamestore import Workspace
from keras.models import Sequential
from keras.layers import Dense
ws = Workspace("/tmp")
model = Sequential()
model.add(Dense(128, activation='relu'))
model.add(Dense(10, activation='softmax'))
ws.store("mymodel", model)
reloaded_model = ws.load("mymodel")
```
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