Sacred templates for ISG Machine Learning and experimental algorithmics experiments.
Sacred website contains a Quickstart guide that you should read.
pip install sacred pymongo
scikit-sacred.py: Scikit-learn with Sacred and MongoDB observer example. This is the most complete example, with some Sacred features not included in the others.
keras-sacred.py: Keras with Sacred and MongoDB observer example.
notebook-keras-sacred.ipynb: Notebook with a Keras train model.
Command-line arguments.
python scikit-sacred.py with 'text="Adios"' 'gamma=0.9'
From Sacred documentation.
./example.py with 'my_list=[1, 2, 3]'
./example.py with 'nested_list=[["a", "b"], [2, 3], False]'
./example.py with 'my_dict={"a":1, "b":[-.2, "two"]}'
./example.py with 'alpha=-.3e-7'
./example.py with 'mask=0b111000'
./example.py with 'message="Hello Bob!"'
Configuration can also be stored in a file.
python scikit-sacred.py print_config with config.json
In case you need to debug your configuration
python scikit-sacred.py print_config
To execute Omniboard locally, you hust have docker in your machine, once this precondition is satisfied, install the container just one time:
docker run --name omniboard --net=<host> -e MONGO_URI=mongodb://<mongo-user>:<mongo-passwd>@<host>:27017/<mongo-db>?authMechanism=SCRAM-SHA-1 vivekratnavel/omniboard
There should be now an Omniboard instance running on localhost:9000.
Stop the container:
docker stop /omniboard
Each time you want to run Omniboard, you need to execute the container:
docker start /omniboard
or remove it:
docker container rm <container-id>
docker run -it --rm --name mongo-express --network host -e ME_CONFIG_BASICAUTH_USERNAME="" -e ME_CONFIG_MONGODB_SERVER="myServer" -e ME_CONFIG_MONGODB_AUTH_DATABASE="myDatabase" -e ME_CONFIG_MONGODB_AUTH_USERNAME="myUser" -e ME_CONFIG_MONGODB_AUTH_PASSWORD="myPassword" mongo-express
Mongo Expresss should be available on localhost:8081.