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Add support for Ray model evaluation and hosting #568

Merged
merged 2 commits into from
Jan 14, 2019
Merged

Add support for Ray model evaluation and hosting #568

merged 2 commits into from
Jan 14, 2019

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saurabh3949
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@saurabh3949 saurabh3949 commented Jan 14, 2019

Add the following capabilities:

  • Save ray checkpoints
  • Evaluate policies/model after training RL agents
  • Host the policy using Tensorflow Serving

Can help resolve aws/sagemaker-python-sdk#581

"source": [
"%%time\n",
" \n",
"estimator_eval = RLEstimator(entry_point=\"evaluate-ray.py\",\n",
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why not specify output_path here as well?

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the evaluation_job doesn't write anything to disk. the results are printed in the logs. I can save those results to disk if you suggest

@vrkhare vrkhare merged commit 2b9b871 into aws:master Jan 14, 2019
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Ray RLLib examples not saving model output
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