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https://github.com/vale981/ray
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b0fa9d6766
After #24459, this PR will add similar support for model artifact saving and an example for experiment tracking with Ray AIR for Comet ML.
51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
"""
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This script is used to clean up state after running test scripts, including
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on external services. For instance, this script can be used to remove the runs
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from WandB that have been saved during unit testing or when running examples.
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"""
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import sys
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def clear_wandb_project():
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import wandb
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# This is hardcoded in the `ray/ml/examples/upload_to_wandb.py` example
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wandb_project = "ray_air_example"
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api = wandb.Api()
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for run in api.runs(wandb_project):
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run.delete()
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def clear_comet_ml_project():
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import comet_ml
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# This is hardcoded in the `ray/ml/examples/upload_to_comet_ml.py` example
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comet_ml_project = "ray-air-example"
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api = comet_ml.API()
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workspace = api.get_default_workspace()
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experiments = api.get_experiments(
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workspace=workspace, project_name=comet_ml_project
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)
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api.delete_experiments([experiment.key for experiment in experiments])
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SERVICES = {"wandb": clear_wandb_project, "comet_ml": clear_comet_ml_project}
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print(f"Usage: python {sys.argv[0]} <service1> [service2] ...")
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sys.exit(0)
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services = sys.argv[1:]
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if any(service not in SERVICES for service in services):
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raise RuntimeError(
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f"All services must be included in {list(SERVICES.keys())}. "
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f"Got: {services}"
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)
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for service in services:
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SERVICES[service]()
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