Replace all instances of ray.readthedocs.io with ray.io (#7994)

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Robert Nishihara 2020-04-13 16:17:05 -07:00 committed by GitHub
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35 changed files with 69 additions and 69 deletions

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@ -19,4 +19,4 @@ Please provide a script that can be run to reproduce the issue. The script shoul
If we cannot run your script, we cannot fix your issue.
- [ ] I have verified my script runs in a clean environment and reproduces the issue.
- [ ] I have verified the issue also occurs with the [latest wheels](https://ray.readthedocs.io/en/latest/installation.html).
- [ ] I have verified the issue also occurs with the [latest wheels](https://docs.ray.io/en/latest/installation.html).

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@ -11,7 +11,7 @@
## Checks
- [ ] I've run `scripts/format.sh` to lint the changes in this PR.
- [ ] I've included any doc changes needed for https://ray.readthedocs.io/en/latest/.
- [ ] I've included any doc changes needed for https://docs.ray.io/en/latest/.
- [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failure rates at https://ray-travis-tracker.herokuapp.com/.
- Testing Strategy
- [ ] Unit tests

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@ -4,7 +4,7 @@
:target: https://travis-ci.com/ray-project/ray
.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
:target: http://ray.readthedocs.io/en/latest/?badge=latest
:target: http://docs.ray.io/en/latest/?badge=latest
|
@ -15,10 +15,10 @@ Ray is packaged with the following libraries for accelerating machine learning w
- `Tune`_: Scalable Hyperparameter Tuning
- `RLlib`_: Scalable Reinforcement Learning
- `RaySGD <https://ray.readthedocs.io/en/latest/raysgd/raysgd.html>`__: Distributed Training Wrappers
- `RaySGD <https://docs.ray.io/en/latest/raysgd/raysgd.html>`__: Distributed Training Wrappers
Install Ray with: ``pip install ray``. For nightly wheels, see the
`Installation page <https://ray.readthedocs.io/en/latest/installation.html>`__.
`Installation page <https://docs.ray.io/en/latest/installation.html>`__.
**NOTE:** `We are deprecating Python 2 support soon.`_
@ -70,7 +70,7 @@ Ray programs can run on a single machine, and can also seamlessly scale to large
``ray submit [CLUSTER.YAML] example.py --start``
Read more about `launching clusters <https://ray.readthedocs.io/en/latest/autoscaling.html>`_.
Read more about `launching clusters <https://docs.ray.io/en/latest/autoscaling.html>`_.
Tune Quick Start
----------------
@ -127,10 +127,10 @@ If TensorBoard is installed, automatically visualize all trial results:
tensorboard --logdir ~/ray_results
.. _`Tune`: https://ray.readthedocs.io/en/latest/tune.html
.. _`Population Based Training (PBT)`: https://ray.readthedocs.io/en/latest/tune-schedulers.html#population-based-training-pbt
.. _`Vizier's Median Stopping Rule`: https://ray.readthedocs.io/en/latest/tune-schedulers.html#median-stopping-rule
.. _`HyperBand/ASHA`: https://ray.readthedocs.io/en/latest/tune-schedulers.html#asynchronous-hyperband
.. _`Tune`: https://docs.ray.io/en/latest/tune.html
.. _`Population Based Training (PBT)`: https://docs.ray.io/en/latest/tune-schedulers.html#population-based-training-pbt
.. _`Vizier's Median Stopping Rule`: https://docs.ray.io/en/latest/tune-schedulers.html#median-stopping-rule
.. _`HyperBand/ASHA`: https://docs.ray.io/en/latest/tune-schedulers.html#asynchronous-hyperband
RLlib Quick Start
-----------------
@ -176,7 +176,7 @@ RLlib Quick Start
"num_workers": 4,
"env_config": {"corridor_length": 5}})
.. _`RLlib`: https://ray.readthedocs.io/en/latest/rllib.html
.. _`RLlib`: https://docs.ray.io/en/latest/rllib.html
More Information
@ -190,7 +190,7 @@ More Information
- `RLlib paper`_
- `Tune paper`_
.. _`Documentation`: http://ray.readthedocs.io/en/latest/index.html
.. _`Documentation`: http://docs.ray.io/en/latest/index.html
.. _`Tutorial`: https://github.com/ray-project/tutorial
.. _`Blog`: https://ray-project.github.io/
.. _`Ray paper`: https://arxiv.org/abs/1712.05889

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@ -1,6 +1,6 @@
# Ray Kubernetes Operator (experimental)
NOTE: The operator is still under active development and not yet recommended for production deployments. Please see [the documentation](https://ray.readthedocs.io/en/latest/deploy-on-kubernetes.html#deploying-on-kubernetes) for current best practices.
NOTE: The operator is still under active development and not yet recommended for production deployments. Please see [the documentation](https://docs.ray.io/en/latest/deploy-on-kubernetes.html#deploying-on-kubernetes) for current best practices.
This directory contains the source code for a Ray operator for Kubernetes.
@ -19,14 +19,14 @@ Some of the main features of the operator are:
> │ ├── groupversion_info.go // contains common metadata about the group-version
> │ ├── raycluster_types.go // RayCluster field definitions, user should focus
> │ └── zz_generated.deepcopy.go // contains the autogenerated implementation of the aforementioned runtime.Object interface, which marks all of our root types as representing Kinds.
> │
> │
> │── config // contains Kustomize YAML definitions required to launch our controller on a cluster,hold our CustomResourceDefinitions, RBAC configuration, and WebhookConfigurations.
> │ ├── certmanager
> │ ├── certmanager
> │ │ ├── certificate.yaml // The following manifests contain a self-signed issuer CR and a certificate CR.
> │ │ ├── kustomization.yaml
> │ │ └── kustomizeconfig.yaml
> │ │
> │ ├── crd
> │ ├── crd
> │ │ └── bases
> │ │ │ └── ray.io_rayclusters.yaml // RayCluster CRD yaml file
> │ │ └── patches
@ -45,7 +45,7 @@ Some of the main features of the operator are:
> │ │ ├── kustomization.yaml
> │ │ └── manager.yaml // manager yaml to create controller deployment, user should focus
> │ │
> │ ├── prometheus
> │ ├── prometheus
> │ │ ├── kustomization.yaml
> │ │ └── monitor.yaml // Prometheus Monitor Service, user should focus
> │ │
@ -103,7 +103,7 @@ go test ./...
You can also build the operator using Bazel:
```generate BUILD.bazel
```generate BUILD.bazel
bazel run //:gazelle
```
@ -160,7 +160,7 @@ $ kubectl delete deployment ray-operator-controller-manager -n ray-operator-syst
### Running an example cluster
There are three example config files to deploy RayClusters included here:
There are three example config files to deploy RayClusters included here:
Sample | Description
------------- | -------------

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@ -4,7 +4,7 @@ name: ray-example-cython
description: "Example of how to use Cython with ray"
tags: ["ray-example", "cython"]
documentation: https://ray.readthedocs.io/en/latest/advanced.html#cython-code-in-ray
documentation: https://docs.ray.io/en/latest/advanced.html#cython-code-in-ray
cluster:
config: ray-project/cluster.yaml

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@ -4,7 +4,7 @@ name: ray-example-lbfgs
description: "Parallelizing the L-BFGS algorithm in ray"
tags: ["ray-example", "optimization", "lbfgs"]
documentation: https://ray.readthedocs.io/en/latest/auto_examples/plot_lbfgs.html
documentation: https://docs.ray.io/en/latest/auto_examples/plot_lbfgs.html
cluster:
config: ray-project/cluster.yaml

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@ -4,7 +4,7 @@ name: ray-example-newsreader
description: "A simple news reader example that uses ray actors to serve requests"
tags: ["ray-example", "flask", "rss", "newsreader"]
documentation: https://ray.readthedocs.io/en/latest/auto_examples/plot_newsreader.html
documentation: https://docs.ray.io/en/latest/auto_examples/plot_newsreader.html
cluster:
config: ray-project/cluster.yaml

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@ -13,7 +13,7 @@ View the `code for this example`_.
.. note::
For an overview of Ray's reinforcement learning library, see `RLlib <http://ray.readthedocs.io/en/latest/rllib.html>`__.
For an overview of Ray's reinforcement learning library, see `RLlib <http://docs.ray.io/en/latest/rllib.html>`__.
To run the application, first install **ray** and then some dependencies:

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@ -16,7 +16,7 @@ their results to be ready.
hyperparameter tuning, use `Tune`_, a scalable hyperparameter
tuning library built using Ray's Actor API.
.. _`Tune`: https://ray.readthedocs.io/en/latest/tune.html
.. _`Tune`: https://docs.ray.io/en/latest/tune.html
Setup: Dependencies
-------------------

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@ -87,7 +87,7 @@ the top 10 words in these articles together with their word count:
Note that this examples uses `distributed actor handles`_, which are still
considered experimental.
.. _`distributed actor handles`: http://ray.readthedocs.io/en/latest/actors.html
.. _`distributed actor handles`: http://docs.ray.io/en/latest/actors.html
There is a ``Mapper`` actor, which has a method ``get_range`` used to retrieve
word counts for words in a certain range:

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@ -8,7 +8,7 @@ date: 2017-05-20 14:00:00
This post announces Ray, a framework for efficiently running Python code on
clusters and large multi-core machines. The project is open source.
You can check out [the code](https://github.com/ray-project/ray) and
[the documentation](http://ray.readthedocs.io/en/latest/?badge=latest).
[the documentation](http://docs.ray.io/en/latest/?badge=latest).
Many AI algorithms are computationally intensive and exhibit complex
communication patterns. As a result, many researchers spend most of their

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@ -134,12 +134,12 @@ state of the actor. We are working on improving the speed of recovery by
enabling actor state to be restored from checkpoints. See [an overview of fault
tolerance in Ray][4].
[1]: http://ray.readthedocs.io/en/latest/plasma-object-store.html
[2]: http://ray.readthedocs.io/en/latest/webui.html
[3]: http://ray.readthedocs.io/en/latest/rllib.html
[4]: http://ray.readthedocs.io/en/latest/fault-tolerance.html
[1]: http://docs.ray.io/en/latest/plasma-object-store.html
[2]: http://docs.ray.io/en/latest/webui.html
[3]: http://docs.ray.io/en/latest/rllib.html
[4]: http://docs.ray.io/en/latest/fault-tolerance.html
[5]: https://github.com/apache/arrow
[6]: http://ray.readthedocs.io/en/latest/example-a3c.html
[6]: http://docs.ray.io/en/latest/example-a3c.html
[7]: https://github.com/openai/baselines
[8]: https://github.com/ray-project/ray/blob/b020e6bf1fb00d0745371d8674146d4a5b75d9f0/python/ray/rllib/test/tuned_examples.sh#L11
[9]: https://arrow.apache.org/docs/python/ipc.html#arbitrary-object-serialization

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@ -271,7 +271,7 @@ for i in range(len(test_objects)):
plot(*benchmark_object(test_objects[i]), titles[i], i)
```
[1]: http://ray.readthedocs.io/en/latest/index.html
[1]: http://docs.ray.io/en/latest/index.html
[2]: https://arrow.apache.org/
[3]: https://en.wikipedia.org/wiki/Serialization
[4]: https://github.com/cloudpipe/cloudpickle/

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@ -134,14 +134,14 @@ This feature is still considered experimental, but we've already found
distributed actor handles useful for implementing [**parameter server**][10] and
[**streaming MapReduce**][11] applications.
[1]: http://ray.readthedocs.io/en/latest/actors.html#passing-around-actor-handles-experimental
[2]: http://ray.readthedocs.io/en/latest/tune.html
[3]: http://ray.readthedocs.io/en/latest/rllib.html
[1]: http://docs.ray.io/en/latest/actors.html#passing-around-actor-handles-experimental
[2]: http://docs.ray.io/en/latest/tune.html
[3]: http://docs.ray.io/en/latest/rllib.html
[4]: https://research.google.com/pubs/pub46180.html
[5]: https://arxiv.org/abs/1603.06560
[6]: https://www.tensorflow.org/get_started/summaries_and_tensorboard
[7]: https://media.readthedocs.org/pdf/rllab/latest/rllab.pdf
[8]: https://en.wikipedia.org/wiki/Parallel_coordinates
[9]: https://github.com/ray-project/ray/tree/master/python/ray/tune
[10]: http://ray.readthedocs.io/en/latest/example-parameter-server.html
[11]: http://ray.readthedocs.io/en/latest/example-streaming.html
[10]: http://docs.ray.io/en/latest/example-parameter-server.html
[11]: http://docs.ray.io/en/latest/example-streaming.html

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@ -78,10 +78,10 @@ Training][9].
[1]: https://github.com/ray-project/ray
[2]: https://rise.cs.berkeley.edu/blog/pandas-on-ray/
[3]: http://ray.readthedocs.io/en/latest/rllib.html
[4]: http://ray.readthedocs.io/en/latest/tune.html
[3]: http://docs.ray.io/en/latest/rllib.html
[4]: http://docs.ray.io/en/latest/tune.html
[5]: https://rise.cs.berkeley.edu/blog/distributed-policy-optimizers-for-scalable-and-reproducible-deep-rl/
[6]: http://ray.readthedocs.io/en/latest/resources.html
[6]: http://docs.ray.io/en/latest/resources.html
[7]: https://pandas.pydata.org/
[8]: https://arxiv.org/abs/1803.00933
[9]: http://ray.readthedocs.io/en/latest/pbt.html
[9]: http://docs.ray.io/en/latest/pbt.html

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@ -76,8 +76,8 @@ Ray now supports Java thanks to contributions from [Ant Financial][4]:
[1]: https://github.com/ray-project/ray
[2]: http://ray.readthedocs.io/en/latest/rllib.html
[3]: http://ray.readthedocs.io/en/latest/tune.html
[2]: http://docs.ray.io/en/latest/rllib.html
[3]: http://docs.ray.io/en/latest/tune.html
[4]: https://www.antfin.com/
[5]: https://github.com/modin-project/modin
[6]: http://ray.readthedocs.io/en/latest/autoscaling.html
[6]: http://docs.ray.io/en/latest/autoscaling.html

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@ -321,12 +321,12 @@ Questions should be directed to *ray-dev@googlegroups.com*.
[1]: https://github.com/ray-project/ray
[2]: http://ray.readthedocs.io/en/latest/resources.html
[2]: http://docs.ray.io/en/latest/resources.html
[3]: http://www.sysml.cc/doc/206.pdf
[4]: http://ray.readthedocs.io/en/latest/rllib.html
[5]: http://ray.readthedocs.io/en/latest/tune.html
[6]: http://ray.readthedocs.io/en/latest
[7]: http://ray.readthedocs.io/en/latest/api.html
[4]: http://docs.ray.io/en/latest/rllib.html
[5]: http://docs.ray.io/en/latest/tune.html
[6]: http://docs.ray.io/en/latest
[7]: http://docs.ray.io/en/latest/api.html
[8]: https://github.com/modin-project/modin
[9]: https://ray-project.github.io/2017/10/15/fast-python-serialization-with-ray-and-arrow.html
[10]: https://ray-project.github.io/2017/08/08/plasma-in-memory-object-store.html

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@ -25,7 +25,7 @@ layout: default
</p>
<ul>
<li>Ray Project <a href="https://ray.io">web site</a></li>
<li><a href="https://ray.readthedocs.io/en/latest/">Documentation</a></li>
<li><a href="https://docs.ray.io/en/latest/">Documentation</a></li>
<li><a href="https://github.com/ray-project/">GitHub project</a></li>
<li><a href="https://github.com/ray-project/tutorial">Tutorials</a></li>
</ul>

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@ -33,6 +33,6 @@ layout: default
</ul>
<p>
To get started, visit the Ray Project <a href="https://ray.io">web site</a>, <a href="https://ray.readthedocs.io/en/latest/">documentation</a>, <a href="https://github.com/ray-project/">GitHub project</a>, or <a href="https://github.com/ray-project/tutorial">Tutorials</a>.
To get started, visit the Ray Project <a href="https://ray.io">web site</a>, <a href="https://docs.ray.io/en/latest/">documentation</a>, <a href="https://github.com/ray-project/">GitHub project</a>, or <a href="https://github.com/ray-project/tutorial">Tutorials</a>.
</p>
</div>

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@ -329,6 +329,6 @@ components like the following:
.. _`issues`: https://github.com/ray-project/ray/issues
.. _`Temporary Files`: http://ray.readthedocs.io/en/latest/tempfile.html
.. _`Temporary Files`: http://docs.ray.io/en/latest/tempfile.html
.. _`PR template`: https://github.com/ray-project/ray/blob/master/.github/PULL_REQUEST_TEMPLATE.md
.. _`Travis CI`: https://github.com/ray-project/ray/tree/master/ci/travis

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@ -4,7 +4,7 @@ Contributing to RLlib
Development Install
-------------------
You can develop RLlib locally without needing to compile Ray by using the `setup-dev.py <https://github.com/ray-project/ray/blob/master/python/ray/setup-dev.py>`__ script. This sets up links between the ``rllib`` dir in your git repo and the one bundled with the ``ray`` package. However if you have installed ray from source using [these instructions](https://ray.readthedocs.io/en/latest/installation.html) then do not this as these steps should have already created this symlink. When using this script, make sure that your git branch is in sync with the installed Ray binaries (i.e., you are up-to-date on `master <https://github.com/ray-project/ray>`__ and have the latest `wheel <https://ray.readthedocs.io/en/latest/installation.html>`__ installed.)
You can develop RLlib locally without needing to compile Ray by using the `setup-dev.py <https://github.com/ray-project/ray/blob/master/python/ray/setup-dev.py>`__ script. This sets up links between the ``rllib`` dir in your git repo and the one bundled with the ``ray`` package. However if you have installed ray from source using [these instructions](https://docs.ray.io/en/latest/installation.html) then do not this as these steps should have already created this symlink. When using this script, make sure that your git branch is in sync with the installed Ray binaries (i.e., you are up-to-date on `master <https://github.com/ray-project/ray>`__ and have the latest `wheel <https://docs.ray.io/en/latest/installation.html>`__ installed.)
API Stability
-------------

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@ -105,7 +105,7 @@ on what Ray functionalities we use, let us see what cProfile's output might look
like if our example involved Actors (for an introduction to Ray actors, see our
`Actor documentation here`_).
.. _`Actor documentation here`: http://ray.readthedocs.io/en/latest/actors.html
.. _`Actor documentation here`: http://docs.ray.io/en/latest/actors.html
Now, instead of looping over five calls to a remote function like in ``ex1``,
let's create a new example and loop over five calls to a remote function

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@ -19,7 +19,7 @@ This section assumes that you have a cluster running and that the nodes in the
cluster can communicate with each other. It also assumes that Ray is installed
on each machine. To install Ray, follow the `installation instructions`_.
.. _`installation instructions`: http://ray.readthedocs.io/en/latest/installation.html
.. _`installation instructions`: http://docs.ray.io/en/latest/installation.html
Starting Ray on each machine
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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@ -7,7 +7,7 @@
"project": "ray",
// The project's homepage
"project_url": "http://ray.readthedocs.io/en/latest/index.html",
"project_url": "http://docs.ray.io/en/latest/index.html",
// The URL or local path of the source code repository for the
// project being benchmarked

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@ -142,7 +142,7 @@ class ObjectStoreFullError(RayError):
"You can also try setting an option to fallback to LRU eviction "
"when the object store is full by calling "
"ray.init(lru_evict=True). See also: "
"https://ray.readthedocs.io/en/latest/memory-management.html.")
"https://docs.ray.io/en/latest/memory-management.html.")
class UnreconstructableError(RayError):
@ -167,7 +167,7 @@ class UnreconstructableError(RayError):
"or setting object store limits with "
"ray.remote(object_store_memory=<bytes>). See also: {}".format(
self.object_id.hex(),
"https://ray.readthedocs.io/en/latest/memory-management.html"))
"https://docs.ray.io/en/latest/memory-management.html"))
class RayTimeoutError(RayError):

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@ -52,7 +52,7 @@ if __name__ == "__main__":
print("Created links.\n\nIf you run into issues initializing Ray, please "
"ensure that your local repo and the installed Ray are in sync "
"(pip install -U the latest wheels at "
"https://ray.readthedocs.io/en/latest/installation.html, "
"https://docs.ray.io/en/latest/installation.html, "
"and ensure you are up-to-date on the master branch on git).\n\n"
"Note that you may need to delete the package symlinks when pip "
"installing new Ray versions to prevent pip from overwriting files "

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@ -3,7 +3,7 @@ Tune: Scalable Hyperparameter Tuning
Tune is a scalable framework for hyperparameter search with a focus on deep learning and deep reinforcement learning.
User documentation can be `found here <http://ray.readthedocs.io/en/latest/tune.html>`__.
User documentation can be `found here <http://docs.ray.io/en/latest/tune.html>`__.
Tutorial

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@ -40,7 +40,7 @@
<a class="nav-link" href="https://github.com/ray-project/ray">Github <span class="sr-only">(current)</span></a>
</li>
<li class="nav-item">
<a class="nav-link" href="http://ray.readthedocs.io/">Document</a>
<a class="nav-link" href="http://docs.ray.io/">Document</a>
</li>
</ul>
</div>

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@ -40,7 +40,7 @@
<a class="nav-link" href="https://github.com/ray-project/ray">Github</a>
</li>
<li class="nav-item">
<a class="nav-link" href="http://ray.readthedocs.io/">Document</a>
<a class="nav-link" href="http://docs.ray.io/">Document</a>
</li>
</ul>
</div>

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@ -40,7 +40,7 @@
<a class="nav-link" href="https://github.com/ray-project/ray">Github</a>
</li>
<li class="nav-item">
<a class="nav-link" href="http://ray.readthedocs.io/">Document</a>
<a class="nav-link" href="http://docs.ray.io/">Document</a>
</li>
</ul>
</div>

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@ -9,7 +9,7 @@ def register_ray():
except ImportError:
msg = ("To use the ray backend you must install ray."
"Try running 'pip install ray'."
"See https://ray.readthedocs.io/en/latest/installation.html"
"See https://docs.ray.io/en/latest/installation.html"
"for more information.")
raise ImportError(msg)

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@ -12,7 +12,7 @@ logger = logging.getLogger(__name__)
class RayBackend(MultiprocessingBackend):
"""Ray backend uses ray, a system for scalable distributed computing.
More info about Ray is available here: https://ray.readthedocs.io.
More info about Ray is available here: https://docs.ray.io.
"""
def configure(self,

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@ -3,7 +3,7 @@ Running benchmarks
RaySGD provides comparable or better performance than other existing solutions for parallel or distributed training.
You can run ``ray/python/ray/util/sgd/torch/examples/benchmarks/benchmark.py`` for benchmarking the RaySGD TorchTrainer implementation. To benchmark training on a multi-node multi-gpu cluster, you can use the `Ray Autoscaler <https://ray.readthedocs.io/en/latest/autoscaling.html#aws>`_.
You can run ``ray/python/ray/util/sgd/torch/examples/benchmarks/benchmark.py`` for benchmarking the RaySGD TorchTrainer implementation. To benchmark training on a multi-node multi-gpu cluster, you can use the `Ray Autoscaler <https://docs.ray.io/en/latest/autoscaling.html#aws>`_.
DISCLAIMER: RaySGD does not provide any custom communication primitives. If you see any performance issues, you may need to file them on the PyTorch github repository.

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@ -3,7 +3,7 @@ RLlib: Scalable Reinforcement Learning
RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
For an overview of RLlib, see the [documentation](http://ray.readthedocs.io/en/latest/rllib.html).
For an overview of RLlib, see the [documentation](http://docs.ray.io/en/latest/rllib.html).
If you've found RLlib useful for your research, you can cite the [paper](https://arxiv.org/abs/1712.09381) as follows:
@ -27,4 +27,4 @@ If you've found RLlib useful for your research, you can cite the [paper](https:/
Development Install
-------------------
You can develop RLlib locally without needing to compile Ray by using the [setup-dev.py](https://github.com/ray-project/ray/blob/master/python/ray/setup-dev.py) script. This sets up links between the ``rllib`` dir in your git repo and the one bundled with the ``ray`` package. When using this script, make sure that your git branch is in sync with the installed Ray binaries (i.e., you are up-to-date on [master](https://github.com/ray-project/ray) and have the latest [wheel](https://ray.readthedocs.io/en/latest/installation.html) installed.)
You can develop RLlib locally without needing to compile Ray by using the [setup-dev.py](https://github.com/ray-project/ray/blob/master/python/ray/setup-dev.py) script. This sets up links between the ``rllib`` dir in your git repo and the one bundled with the ``ray`` package. When using this script, make sure that your git branch is in sync with the installed Ray binaries (i.e., you are up-to-date on [master](https://github.com/ray-project/ray) and have the latest [wheel](https://docs.ray.io/en/latest/installation.html) installed.)

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Contributed algorithms, which can be run via ``rllib train --run=contrib/<alg_name>``
See https://ray.readthedocs.io/en/latest/rllib-dev.html for guidelines.
See https://docs.ray.io/en/latest/rllib-dev.html for guidelines.