Bump Ray Version from 2.0.0.dev0 to 3.0.0.dev0 (ray-project#24894)

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-2.0.0.dev0-cp36-cp36m-manylinux2014_x86_64.whl
+ - pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.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.
 

doc/source/ray-contribute/development.rst

@@ -25,7 +25,8 @@ RLlib, Tune, Autoscaler, and most Python files do not require you to build and c
 
 .. code-block:: shell
 
- pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
+ # 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
 
 2. Fork and clone the project to your machine. Connect your repository to the upstream (main project) ray repository.
 
@@ -74,7 +75,7 @@ For RHELv8 (Redhat EL 8.0-64 Minimal), run the following commands:
  sudo yum groupinstall 'Development Tools'
  sudo yum install psmisc
 
-Install bazel manually from link: https://docs.bazel.build/versions/main/install-redhat.html 
+Install bazel manually from link: https://docs.bazel.build/versions/main/install-redhat.html
 
 
 For MacOS, run the following commands:

doc/source/ray-core/handling-dependencies.rst

@@ -635,7 +635,7 @@ 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]: 2.0.0.dev0 /Users/user/ray/python/ray
+ (pid=runtime_env) 2022-02-28 14:12:35,118 INFO utils.py:97 -- Output of cmd[2]: 3.0.0.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']
@@ -646,7 +646,7 @@ 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]: 2.0.0.dev0 /Users/user/ray/python/ray
+ (pid=runtime_env) 2022-02-28 14:12:38,804 INFO utils.py:97 -- Output of cmd[4]: 3.0.0.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.

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="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
+ 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
  # 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="2.0.0.dev0",actor_name="my_actor"} -15.0
+ ray_curr_count{Component="core_worker",Version="3.0.0.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="2.0.0.dev0",actor_name="my_actor"} 2.0
+ ray_num_requests_total{Component="core_worker",Version="3.0.0.dev0",actor_name="my_actor"} 2.0
 
 Please see :ref:`ray.util.metrics <custom-metric-api-ref>` for more details.

doc/source/ray-overview/installation.rst

@@ -56,20 +56,20 @@ 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-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
+.. _`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
 
-.. _`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
+.. _`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
 
-.. _`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
+.. _`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
 
 
 Installing from a specific commit
@@ -81,11 +81,11 @@ 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 2.0.0.dev0 wheels for Python 3.7, MacOS for commit ``ba6cebe30fab6925e5b2d9e859ad064d53015246``:
+For example, here are the Ray 3.0.0.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-2.0.0.dev0-cp37-cp37m-macosx_10_15_intel.whl
+ 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
 
 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:

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: "2.0.0.dev0"
+ `ray --version`. Examples: "3.0.0.dev0"
  py_version (str):
  The major and minor Python versions concatenated. Examples: "36",
  "37", "38", "39"
  Returns:
  The wheel file name. Examples:
- ray-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
+ ray-3.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
  """
  assert py_version in ["36", "37", "38", "39"], py_version
 

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-2.0.0.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-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands:

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-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: []

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-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: []

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-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"
+ # - 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"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands:

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-2.0.0.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-3.0.0.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

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-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.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

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-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.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

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-2.0.0.dev0-cp38-cp38-manylinux2014_x86_64.whl"
+# - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.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

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-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
+ - which ray || pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
 
 
 # Custom commands that will be run on the head node after common setup.

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-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
+ # - pip install -U "ray[default] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 
 # Custom commands that will be run on the head node after common setup.

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-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"
+ # - 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"
 
 # Custom commands that will be run on the head node after common setup.
 head_setup_commands: