wehub-resource-sync
28 lines
706 B
Python
28 lines
706 B
Python
# flake8: noqa
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# fmt: off
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# __resource_allocation_1_begin__
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import ray
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from ray import tune
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# This workload will use spare cluster resources for execution.
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def objective(*args):
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ray.data.range(10).show()
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# Create a cluster with 4 CPU slots available.
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ray.init(num_cpus=4)
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# By setting `max_concurrent_trials=3`, this ensures the cluster will always
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# have a sparse CPU for Dataset. Try setting `max_concurrent_trials=4` here,
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# and notice that the experiment will appear to hang.
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tuner = tune.Tuner(
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tune.with_resources(objective, {"cpu": 1}),
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tune_config=tune.TuneConfig(
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num_samples=1,
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max_concurrent_trials=3
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)
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)
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tuner.fit()
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# __resource_allocation_1_end__
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# fmt: on
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