Revert "Bump Ray Version from 2.0.0.dev0 to 3.0.0.dev0 (#24894)"

This reverts commit c3ac6fc.
ray-project · May 18, 2022 · 3f70e60 · 3f70e60
1 parent 3ffcb81
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diff --git a/build-docker.sh b/build-docker.sh
@@ -7,7 +7,7 @@ set -x
 
 GPU=""
 BASE_IMAGE="ubuntu:focal"
-WHEEL_URL="https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+WHEEL_URL="https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 PYTHON_VERSION="3.7.7"
 
 

diff --git a/doc/source/cluster/config.rst b/doc/source/cluster/config.rst
@@ -471,7 +471,7 @@ A list of commands to run to set up nodes. These commands will always run on the
  # Default setup_commands:
  setup_commands:
  - echo 'export PATH="$HOME/anaconda3/envs/tensorflow_p36/bin:$PATH"' >> ~/.bashrc
- - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
+ - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
 
 - Setup commands should ideally be *idempotent* (i.e., can be run multiple times without changing the result); this allows Ray to safely update nodes after they have been created. You can usually make commands idempotent with small modifications, e.g. ``git clone foo`` can be rewritten as ``test -e foo || git clone foo`` which checks if the repo is already cloned first.
 

diff --git a/doc/source/ray-contribute/development.rst b/doc/source/ray-contribute/development.rst
@@ -115,7 +115,7 @@ RLlib, Tune, Autoscaler, and most Python files do not require you to build and c
 .. code-block:: shell
 
  # For example, for Python 3.8:
- pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
+ pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
 
 4. Replace Python files in the installed package with your local editable copy. We provide a simple script to help you do this: ``python python/ray/setup-dev.py``. Running the script will remove the ``ray/tune``, ``ray/rllib``, ``ray/autoscaler`` dir (among other directories) bundled with the ``ray`` pip package, and replace them with links to your local code. This way, changing files in your git clone will directly affect the behavior of your installed Ray.
 

diff --git a/doc/source/ray-core/handling-dependencies.rst b/doc/source/ray-core/handling-dependencies.rst
@@ -671,7 +671,7 @@ Example log output:
  (pid=runtime_env) activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator
  (pid=runtime_env)
  (pid=runtime_env) 2022-02-28 14:12:34,268 INFO utils.py:76 -- Run cmd[2] ['/tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/virtualenv/bin/python', '-c', 'import ray; print(ray.__version__, ray.__path__[0])']
- (pid=runtime_env) 2022-02-28 14:12:35,118 INFO utils.py:97 -- Output of cmd[2]: 3.0.0.dev0 /Users/user/ray/python/ray
+ (pid=runtime_env) 2022-02-28 14:12:35,118 INFO utils.py:97 -- Output of cmd[2]: 2.0.0.dev0 /Users/user/ray/python/ray
  (pid=runtime_env)
  (pid=runtime_env) 2022-02-28 14:12:35,120 INFO pip.py:236 -- Installing python requirements to /tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/virtualenv
  (pid=runtime_env) 2022-02-28 14:12:35,122 INFO utils.py:76 -- Run cmd[3] ['/tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/virtualenv/bin/python', '-m', 'pip', 'install', '--disable-pip-version-check', '--no-cache-dir', '-r', '/tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/requirements.txt']
@@ -682,7 +682,7 @@ Example log output:
  (pid=runtime_env) Requirement already satisfied: charset-normalizer~=2.0.0 in /Users/user/anaconda3/envs/ray-py38/lib/python3.8/site-packages (from requests->-r /tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/requirements.txt (line 1)) (2.0.6)
  (pid=runtime_env)
  (pid=runtime_env) 2022-02-28 14:12:38,001 INFO utils.py:76 -- Run cmd[4] ['/tmp/ray/session_2022-02-28_14-12-29_909064_87908/runtime_resources/pip/0cc818a054853c3841171109300436cad4dcf594/virtualenv/bin/python', '-c', 'import ray; print(ray.__version__, ray.__path__[0])']
- (pid=runtime_env) 2022-02-28 14:12:38,804 INFO utils.py:97 -- Output of cmd[4]: 3.0.0.dev0 /Users/user/ray/python/ray
+ (pid=runtime_env) 2022-02-28 14:12:38,804 INFO utils.py:97 -- Output of cmd[4]: 2.0.0.dev0 /Users/user/ray/python/ray
 
 Regardless of the value of ``RAY_RUNTIME_ENV_LOG_TO_DRIVER_ENABLED``, these logs can always be found in the file ``runtime_env_setup-[job_id].log`` for per-actor, per-task and per-job environments, or in
 ``runtime_env_setup-ray_client_server_[port].log`` for per-job environments when using Ray Client.

diff --git a/doc/source/ray-observability/ray-metrics.rst b/doc/source/ray-observability/ray-metrics.rst
@@ -183,16 +183,16 @@ If you open this in the browser, you should see the following output:
 
  # HELP ray_request_latency Latencies of requests in ms.
  # TYPE ray_request_latency histogram
- ray_request_latency_bucket{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor",le="0.1"} 2.0
- ray_request_latency_bucket{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor",le="1.0"} 2.0
- ray_request_latency_bucket{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor",le="+Inf"} 2.0
- ray_request_latency_count{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor"} 2.0
- ray_request_latency_sum{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor"} 0.11992454528808594
+ ray_request_latency_bucket{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor",le="0.1"} 2.0
+ ray_request_latency_bucket{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor",le="1.0"} 2.0
+ ray_request_latency_bucket{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor",le="+Inf"} 2.0
+ ray_request_latency_count{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor"} 2.0
+ ray_request_latency_sum{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor"} 0.11992454528808594
  # HELP ray_curr_count Current count held by the actor. Goes up and down.
  # TYPE ray_curr_count gauge
- ray_curr_count{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor"} -15.0
+ ray_curr_count{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor"} -15.0
  # HELP ray_num_requests_total Number of requests processed by the actor.
  # TYPE ray_num_requests_total counter
- ray_num_requests_total{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor"} 2.0
+ ray_num_requests_total{Component="core_worker",Version="2.0.0.dev0",actor_name="my_actor"} 2.0
 
 Please see :ref:`ray.util.metrics <custom-metric-api-ref>` for more details.
diff --git a/doc/source/ray-overview/installation.rst b/doc/source/ray-overview/installation.rst
@@ -57,20 +57,20 @@ You can install the nightly Ray wheels via the following links. These daily rele
  On Windows, support for multi-node Ray clusters is currently experimental and untested.
  If you run into issues please file a report at https://github.com/ray-project/ray/issues.
 
-.. _`Linux Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl
-.. _`Linux Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
-.. _`Linux Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
-.. _`Linux Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
+.. _`Linux Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp39-cp39-manylinux2014_x86_64.whl
+.. _`Linux Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
+.. _`Linux Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
+.. _`Linux Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
 
-.. _`MacOS Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp39-cp39-macosx_10_15_x86_64.whl
-.. _`MacOS Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-macosx_10_15_x86_64.whl
-.. _`MacOS Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-macosx_10_15_intel.whl
-.. _`MacOS Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-macosx_10_15_intel.whl
+.. _`MacOS Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp39-cp39-macosx_10_15_x86_64.whl
+.. _`MacOS Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-macosx_10_15_x86_64.whl
+.. _`MacOS Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-macosx_10_15_intel.whl
+.. _`MacOS Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-macosx_10_15_intel.whl
 
-.. _`Windows Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp39-cp39-win_amd64.whl
-.. _`Windows Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-win_amd64.whl
-.. _`Windows Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-win_amd64.whl
-.. _`Windows Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-win_amd64.whl
+.. _`Windows Python 3.9`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp39-cp39-win_amd64.whl
+.. _`Windows Python 3.8`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-win_amd64.whl
+.. _`Windows Python 3.7`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-win_amd64.whl
+.. _`Windows Python 3.6`: https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-win_amd64.whl
 
 
 Installing from a specific commit
@@ -82,11 +82,11 @@ You can install the Ray wheels of any particular commit on ``master`` with the f
 
  pip install https://s3-us-west-2.amazonaws.com/ray-wheels/master/{COMMIT_HASH}/ray-{RAY_VERSION}-{PYTHON_VERSION}-{PYTHON_VERSION}m-{OS_VERSION}.whl
 
-For example, here are the Ray 3.0.0.dev0 wheels for Python 3.7, MacOS for commit ``ba6cebe30fab6925e5b2d9e859ad064d53015246``:
+For example, here are the Ray 2.0.0.dev0 wheels for Python 3.7, MacOS for commit ``ba6cebe30fab6925e5b2d9e859ad064d53015246``:
 
 .. code-block:: bash
 
- pip install https://s3-us-west-2.amazonaws.com/ray-wheels/master/ba6cebe30fab6925e5b2d9e859ad064d53015246/ray-3.0.0.dev0-cp37-cp37m-macosx_10_15_intel.whl
+ pip install https://s3-us-west-2.amazonaws.com/ray-wheels/master/ba6cebe30fab6925e5b2d9e859ad064d53015246/ray-2.0.0.dev0-cp37-cp37m-macosx_10_15_intel.whl
 
 There are minor variations to the format of the wheel filename; it's best to match against the format in the URLs listed in the :ref:`Nightlies section <install-nightlies>`.
 Here's a summary of the variations:

diff --git a/python/ray/__init__.py b/python/ray/__init__.py
@@ -110,7 +110,7 @@ def _configure_system():
 
 # Replaced with the current commit when building the wheels.
 __commit__ = "{{RAY_COMMIT_SHA}}"
-__version__ = "3.0.0.dev0"
+__version__ = "2.0.0.dev0"
 
 import ray._raylet # noqa: E402
 

diff --git a/python/ray/_private/utils.py b/python/ray/_private/utils.py
@@ -1081,13 +1081,13 @@ def get_wheel_filename(
  sys_platform (str): The platform as returned by sys.platform. Examples:
  "darwin", "linux", "win32"
  ray_version (str): The Ray version as returned by ray.__version__ or
- `ray --version`. Examples: "3.0.0.dev0"
+ `ray --version`. Examples: "2.0.0.dev0"
  py_version (str):
  The major and minor Python versions concatenated. Examples: "36",
  "37", "38", "39"
  Returns:
  The wheel file name. Examples:
- ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
+ ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
  """
  assert py_version in ["36", "37", "38", "39"], py_version
 

diff --git a/python/ray/autoscaler/aws/defaults.yaml b/python/ray/autoscaler/aws/defaults.yaml
@@ -124,7 +124,7 @@ setup_commands:
  - >-
  (stat $HOME/anaconda3/envs/tensorflow2_latest_p37/ &> /dev/null &&
  echo 'export PATH="$HOME/anaconda3/envs/tensorflow2_latest_p37/bin:$PATH"' >> ~/.bashrc) || true
- - which ray || pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ - which ray || pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands:

diff --git a/python/ray/autoscaler/aws/example-full-legacy.yaml b/python/ray/autoscaler/aws/example-full-legacy.yaml
@@ -130,7 +130,7 @@ setup_commands: []
  # below with a git checkout <your_sha> (and possibly a recompile).
  # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image
  # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line:
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: []

diff --git a/python/ray/autoscaler/aws/example-full.yaml b/python/ray/autoscaler/aws/example-full.yaml
@@ -152,7 +152,7 @@ setup_commands: []
  # below with a git checkout <your_sha> (and possibly a recompile).
  # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image
  # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line:
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: []

diff --git a/python/ray/autoscaler/aws/example-gpu-docker.yaml b/python/ray/autoscaler/aws/example-gpu-docker.yaml
@@ -113,8 +113,8 @@ file_mounts: {
 # List of shell commands to run to set up nodes.
 # NOTE: rayproject/ray:latest has ray latest bundled
 setup_commands: []
- # - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands:

diff --git a/python/ray/autoscaler/azure/defaults.yaml b/python/ray/autoscaler/azure/defaults.yaml
@@ -123,7 +123,7 @@ setup_commands:
  - (which conda && echo 'eval "$(conda shell.bash hook)"' >> ~/.bashrc) || true
  # - (conda activate py38_pytorch &> /dev/null && echo 'conda activate py38_pytorch' >> ~/.bashrc) || true
  - (conda activate py38_tensorflow &> /dev/null && echo 'conda activate py38_tensorflow' >> ~/.bashrc) || true
- - which ray || pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+ - which ray || pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
  # Consider uncommenting these if you also want to run apt-get commands during setup
  # - sudo pkill -9 apt-get || true
  # - sudo pkill -9 dpkg || true

diff --git a/python/ray/autoscaler/azure/example-full-legacy.yaml b/python/ray/autoscaler/azure/example-full-legacy.yaml
@@ -132,7 +132,7 @@ setup_commands: []
  # below with a git checkout <your_sha> (and possibly a recompile).
  # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image
  # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line:
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 # NOTE: rayproject/ray-ml:latest has azure packages bundled

diff --git a/python/ray/autoscaler/azure/example-full.yaml b/python/ray/autoscaler/azure/example-full.yaml
@@ -148,7 +148,7 @@ setup_commands: []
  # below with a git checkout <your_sha> (and possibly a recompile).
  # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image
  # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line:
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 # NOTE: rayproject/ray-ml:latest has azure packages bundled

diff --git a/python/ray/autoscaler/azure/example-gpu-docker.yaml b/python/ray/autoscaler/azure/example-gpu-docker.yaml
@@ -109,7 +109,7 @@ initialization_commands:
 # List of shell commands to run to set up nodes.
 # NOTE: rayproject/ray-ml:latest has ray latest bundled
 setup_commands: []
-# - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+# - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 # NOTE: rayproject/ray-ml:latest has azure packages bundled

diff --git a/python/ray/autoscaler/gcp/defaults.yaml b/python/ray/autoscaler/gcp/defaults.yaml
@@ -139,7 +139,7 @@ setup_commands:
  - >-
  (stat /opt/conda/bin/ &> /dev/null &&
  echo 'export PATH="/opt/conda/bin:$PATH"' >> ~/.bashrc) || true
- - which ray || pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
+ - which ray || pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
 
 
 # Custom commands that will be run on the head node after common setup.

diff --git a/python/ray/autoscaler/gcp/example-full.yaml b/python/ray/autoscaler/gcp/example-full.yaml
@@ -162,7 +162,7 @@ setup_commands: []
  # below with a git checkout <your_sha> (and possibly a recompile).
  # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image
  # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line:
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 
 # Custom commands that will be run on the head node after common setup.

diff --git a/python/ray/autoscaler/gcp/example-gpu-docker.yaml b/python/ray/autoscaler/gcp/example-gpu-docker.yaml
@@ -135,8 +135,8 @@ initialization_commands:
 # List of shell commands to run to set up nodes.
 # NOTE: rayproject/ray-ml:latest has ray latest bundled
 setup_commands: []
- # - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
- # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: