Stephanie Wang da06b4db82 Warn the user when a nondeterministic task is detected. (#339)
* WARN instead of FATAL for object hash mismatches, push error to driver

* Document the callback signature for object_table_add/remove

* Error table

* Wait for all errors in python test

* Fix doc

* Fix state test
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Ray

Build Status Documentation Status

Ray is an experimental distributed execution engine. It is under development and not ready to be used.

The goal of Ray is to make it easy to write machine learning applications that run on a cluster while providing the development and debugging experience of working on a single machine.

View the documentation.

S
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Readme Multiple Licenses 111 MiB
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