[Autoscaler][Docker] Mention nightly images in addition to nightly wheels (#14871)

python/ray/autoscaler/aws/example-full-legacy.yaml

@@ -128,7 +128,8 @@ setup_commands: []
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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[full] @ 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.

python/ray/autoscaler/aws/example-full.yaml

@@ -152,7 +152,8 @@ setup_commands: []
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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[full] @ 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.

python/ray/autoscaler/azure/example-full-legacy.yaml

@@ -126,7 +126,8 @@ setup_commands:
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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:
     - echo 'eval "$(conda shell.bash hook)"' >> ~/.bashrc
     - echo 'conda activate py37_tensorflow' >> ~/.bashrc
     - pip install -U "ray[full] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"

python/ray/autoscaler/azure/example-full.yaml

@@ -147,7 +147,8 @@ setup_commands:
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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:
     - echo 'eval "$(conda shell.bash hook)"' >> ~/.bashrc
     - echo 'conda activate py37_tensorflow' >> ~/.bashrc
     - pip install -U "ray[full] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"

python/ray/autoscaler/gcp/example-full-legacy.yaml

@@ -136,7 +136,8 @@ setup_commands: []
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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[full] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 

python/ray/autoscaler/gcp/example-full.yaml

@@ -160,7 +160,8 @@ setup_commands: []
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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[full] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
 
 

python/ray/autoscaler/local/example-full.yaml

@@ -93,7 +93,8 @@ setup_commands: []
     # Note: if you're developing Ray, you probably want to create a Docker image that
     # has your Ray repo pre-cloned. Then, you can replace the pip installs
     # below with a git checkout <your_sha> (and possibly a recompile).
-    # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest)
+    # 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[full] @ 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.