urartu 5.0.3

An open-source NLP framework that offers high-level wrappers designed for effortless launch, enhanced reproducibility, superior control, and unmatched flexibility for your experiments.

Urartu

Urartu is an ML workflow runner built around Pipelines (orchestrators) and Actions (reusable steps) with automatic caching and dependency injection.

Installation

pip install urartu

From source:

git clone [e-mail]:tamohannes/urartu.git
cd urartu
pip install -e .

Project layout (recommended)

Run the CLI from a project root that contains:

my_project/
├── __init__.py
├── actions/
│   ├── __init__.py
│   └── my_action.py
├── pipelines/
│   ├── __init__.py
│   └── my_pipeline.py
└── configs/
    └── pipeline/
        └── my_pipeline.yaml

Optional (per-user configs):

my_project/
└── configs_<username>/
    ├── aim/
    ├── machine/
    └── slurm/

Quickstart

Create a pipeline config:

# configs/pipeline/my_pipeline.yaml
pipeline_name: my_pipeline
debug: false

pipeline:
  experiment_name: "My pipeline"
  device: auto
  seed: 42

  # Pipeline-level cache policy (propagates to actions)
  cache_enabled: true
  force_rerun: false
  cache_max_age_days: 7

  actions:
    - action_name: my_action
      # Action-specific config (merged with pipeline-level common settings)
      some_param: 123

Create the pipeline file:

from aim import Run
from omegaconf import DictConfig
from urartu.common import Pipeline


class MyPipeline(Pipeline):
    pass


def main(cfg: DictConfig, aim_run: Run):
    MyPipeline(cfg, aim_run).main()

Create an action:

from omegaconf import DictConfig
from aim import Run
from urartu.common import Action


class MyAction(Action):
    def run(self):
        cache_dir = self.get_cache_entry_dir()
        run_dir = self.get_run_dir()
        # ... compute, write machine-readable artifacts to cache_dir ...
        # ... write plots/reports to run_dir ...

    def get_outputs(self):
        return {
            "cache_dir": str(self.get_cache_entry_dir()),
            "run_dir": str(self.get_run_dir()),
        }

Run it:

urartu my_pipeline

CLI overrides and config groups

• Overrides: pipeline.seed=123, pipeline.device=cuda, descr="my run".
• Config-group selectors (unquoted) load *.yaml files from:
  • configs_<username>/<group>/<selector>.yaml
  • configs/<group>/<selector>.yaml
  • built-in defaults in the Urartu package

Examples:

# Select config files (unquoted values)
urartu my_pipeline machine=local slurm=no_slurm aim=no_aim

# Set literal strings (quoted values)
urartu my_pipeline descr="experiment 001" machine="local"

Notes on outputs and caching

• Cached, machine-readable artifacts: write under self.get_cache_entry_dir(...) (shared across runs).
• Run artifacts (plots/reports/logs): write under self.get_run_dir(...) (unique per run).

Citation

If you find Urartu helpful in your research, please cite it:

@software{Tamoyan_Urartu_2023,
  author = {Hovhannes Tamoyan},
  license = {Apache-2.0},
  month = {8},
  title = {{Urartu}},
  url = {https://github.com/tamohannes/urartu},
  year = {2023}
}