Added scheduler support to Ray Tune hyperopt and fixed GPU usage #1088
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tgaddair
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I think we may want to encode the configs in tune.report here using json.dumps() rather than str(config). I am having a hard time parsing the returned training_stats, config, and parameters using json.loads() and other decoding methods. |
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Ray will set
CUDA_VISIBLE_DEVICESfor each trial automatically, so we do not need to manually restrict GPUs in Ludwig.See the Ray Tune documentation for details.
cc @ANarayan.