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](
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
cd flame-store
python 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.
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'))"mymodel", model)
reloaded_model = ws.load("mymodel")
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