The server side for MLStorage. MLStorage is an application for running machine learning experiments and storing results as well as generated files, all accessible with a dashboard.
The client side: MLStorage Client.
- Python: >= 3.5.3, or Docker (for server)
- MongoDB: for storing experiment documents.
- A shared network file system: currently the programs must run on a host where the server's storage directory is accessible in the same location, so as to store its generated files.
pip install git+https://github.com/haowen-xu/mlstorage-server.git
mlserver -h <ip> -p 8080 -w 4 -R /path/to/storage-dir \
-M mongodb://user:password@localhost/admin -D user -C experiments
The above command starts an MLStorage server at http://<ip>:8080
, with
4
workers to serve requests. The MongoDB connection string is set to
mongodb://user:password@localhost/admin
, with user
and password
as
the login credential. The user
database and the experiments
collection
is chosen to store the experiment documents. The root directory of experiment
storage directory (i.e., working directory) is set to /path/to/storage-dir
.
git clone git+https://github.com/haowen-xu/mlstorage-server.git
docker build \
--build-arg UBUNTU_MIRROR=archive.ubuntu.com \
--build-arg TZ=UTC \
-t mlstorage_server \
.
docker run \
--name mlserver -d \
-p 8080 \
-e MLSTORAGE_SERVER_HOST=0.0.0.0 \
-e MLSTORAGE_SERVER_PORT=8080 \
-e MLSTORAGE_SERVER_WORKERS=4 \
-e MLSTORAGE_EXPERIMENT_ROOT=/path/to/experiments \
-v /path/to/experiments:/path/to/experiments \
-e MLSTORAGE_MONGO_CONN=mongodb://localhost:27017 \
-e MLSTORAGE_MONGO_DB=test \
-e MLSTORAGE_MONGO_COLL=experiments \
mlstorage_server