Clean up top level Ray dir (#5404)

ci/travis/install-cython-examples.sh

@@ -7,7 +7,7 @@ ROOT_DIR=$(cd "$(dirname "${BASH_SOURCE:-$0}")"; pwd)
 
 echo "PYTHON is $PYTHON"
 
-cython_examples="$ROOT_DIR/../../examples/cython"
+cython_examples="$ROOT_DIR/../../doc/examples/cython"
 
 if [[ "$PYTHON" == "2.7" ]]; then
 

doc/source/example-lbfgs.rst

@@ -11,13 +11,13 @@ application, first install these dependencies.
 
 You can view the `code for this example`_.
 
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/lbfgs
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/lbfgs
 
 Then you can run the example as follows.
 
 .. code-block:: bash
 
-  python ray/examples/lbfgs/driver.py
+  python ray/doc/examples/lbfgs/driver.py
 
 
 Optimization is at the heart of many machine learning algorithms. Much of

doc/source/example-newsreader.rst

@@ -15,15 +15,15 @@ To run this example, you will need to install NPM and a few python dependencies.
 
 To use this example you need to
 
-* In the ``ray/examples/newsreader`` directory, start the server with
+* In the ``ray/doc/examples/newsreader`` directory, start the server with
   ``python server.py``.
 * Clone the client code with ``git clone https://github.com/ray-project/qreader``
 * Start the client with ``cd qreader;  npm install; npm run dev``
 * You can now add a channel by clicking "Add channel" and for example pasting
   ``http://news.ycombinator.com/rss`` into the field.
 * Star some of the articles and dump the database by running
-  ``sqlite3 newsreader.db`` in a terminal in the ``ray/examples/newsreader``
+  ``sqlite3 newsreader.db`` in a terminal in the ``ray/doc/examples/newsreader``
   directory and entering ``SELECT * FROM news;``.
 
 .. _`frontend`: https://github.com/saqueib/qreader
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/newsreader
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/newsreader

doc/source/example-parameter-server.rst

@@ -11,17 +11,17 @@ dependencies.
 
 You can view the `code for this example`_.
 
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/parameter_server
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/parameter_server
 
 The examples can be run as follows.
 
 .. code-block:: bash
 
   # Run the asynchronous parameter server.
-  python ray/examples/parameter_server/async_parameter_server.py --num-workers=4
+  python ray/doc/examples/parameter_server/async_parameter_server.py --num-workers=4
 
   # Run the synchronous parameter server.
-  python ray/examples/parameter_server/sync_parameter_server.py --num-workers=4
+  python ray/doc/examples/parameter_server/sync_parameter_server.py --num-workers=4
 
 Note that this examples uses distributed actor handles, which are still
 considered experimental.

doc/source/example-resnet.rst

@@ -24,7 +24,7 @@ Then run the training script that matches the dataset you downloaded.
 .. code-block:: bash
 
   # Train Resnet on CIFAR-10.
-  python ray/examples/resnet/resnet_main.py \
+  python ray/doc/examples/resnet/resnet_main.py \
       --eval_dir=/tmp/resnet-model/eval \
       --train_data_path=cifar-10-batches-bin/data_batch* \
       --eval_data_path=cifar-10-batches-bin/test_batch.bin \
@@ -32,7 +32,7 @@ Then run the training script that matches the dataset you downloaded.
       --num_gpus=1
 
   # Train Resnet on CIFAR-100.
-  python ray/examples/resnet/resnet_main.py \
+  python ray/doc/examples/resnet/resnet_main.py \
       --eval_dir=/tmp/resnet-model/eval \
       --train_data_path=cifar-100-binary/train.bin \
       --eval_data_path=cifar-100-binary/test.bin \
@@ -101,4 +101,4 @@ object store.
 
 .. _`TensorFlow ResNet example`: https://github.com/tensorflow/models/tree/master/resnet
 .. _`TensorFlow`: https://www.tensorflow.org/install/
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/resnet
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/resnet

doc/source/example-rl-pong.rst

@@ -17,7 +17,7 @@ Then you can run the example as follows.
 
 .. code-block:: bash
 
-  python ray/examples/rl_pong/driver.py --batch-size=10
+  python ray/doc/examples/rl_pong/driver.py --batch-size=10
 
 To run the example on a cluster, simply pass in the flag
 ``--redis-address=<redis-address>``.
@@ -32,7 +32,7 @@ an issue`_.
 
 .. _`code`: https://gist.github.com/karpathy/a4166c7fe253700972fcbc77e4ea32c5
 .. _`blog post`: http://karpathy.github.io/2016/05/31/rl/
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/rl_pong
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/rl_pong
 .. _`submitting an issue`: https://github.com/ray-project/ray/issues
 
 **Note** that these times depend on how long the rollouts take, which in turn

doc/source/example-streaming.rst

@@ -7,7 +7,7 @@ computes word counts on wikipedia articles.
 
 You can view the `code for this example`_.
 
-.. _`code for this example`: https://github.com/ray-project/ray/tree/master/examples/streaming
+.. _`code for this example`: https://github.com/ray-project/ray/tree/master/doc/examples/streaming
 
 To run the example, you need to install the dependencies
 
@@ -20,7 +20,7 @@ and then execute the script as follows:
 
 .. code-block:: bash
 
-  python ray/examples/streaming/streaming.py
+  python ray/doc/examples/streaming/streaming.py
 
 For each round of articles read, the script will output
 the top 10 words in these articles together with their word count:

setup_hooks.sh

@@ -1,2 +1,2 @@
 #!/bin/bash
-ln -s $PWD/hooks/pre-push $PWD/.git/hooks/pre-push
+ln -s $PWD/scripts/pre-push $PWD/.git/hooks/pre-push