To install this, ensure that you have your favorite library installed. To install deckard along with tensorflow, for example, use
python -m pip install .[tensorflow]
Add the -e flag if you want to edit files:
python -m pip install -e .
Or try the rpi script:
bash rpi.sh
Now, check that deckard works
$ python
>>> import deckard
Then CTRL+D or quit() to quit.
Running dvc repro in that folder will reproduce the experiment outlined in the dvc.yaml. Running
python -m deckard
will parse the configuration folder, create a params.yaml, and then run dvc repro.
.
├── Dockerfile: Constructs a generic Docker image for running experiments
├── LICENSE
├── README.md: this file
├── deckard: Source code
├── examples: Directory containing all the examples
├── rpi.sh: For installation on Raspbian.
├── setup.py : for installation with pip
├── setup.sh : for installation using bash
└── test : test suite
After adding it to your path, you can then run it as a module:
cd examples/power
python -m deckard --config_name mnist.yaml