From 5d763b3f497eea50767e946bcd5d0a623610535c Mon Sep 17 00:00:00 2001 From: Ian Rodney Date: Tue, 23 Mar 2021 17:13:36 -0700 Subject: [PATCH] [Autoscaler][Docker] Mention nightly images in addition to nightly wheels (#14871) --- python/ray/autoscaler/aws/example-full-legacy.yaml | 3 ++- python/ray/autoscaler/aws/example-full.yaml | 3 ++- python/ray/autoscaler/azure/example-full-legacy.yaml | 3 ++- python/ray/autoscaler/azure/example-full.yaml | 3 ++- python/ray/autoscaler/gcp/example-full-legacy.yaml | 3 ++- python/ray/autoscaler/gcp/example-full.yaml | 3 ++- python/ray/autoscaler/local/example-full.yaml | 3 ++- 7 files changed, 14 insertions(+), 7 deletions(-) diff --git a/python/ray/autoscaler/aws/example-full-legacy.yaml b/python/ray/autoscaler/aws/example-full-legacy.yaml index 2bef855e0..b7de9695d 100644 --- a/python/ray/autoscaler/aws/example-full-legacy.yaml +++ b/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 (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. diff --git a/python/ray/autoscaler/aws/example-full.yaml b/python/ray/autoscaler/aws/example-full.yaml index 88c9fec50..1e2edb749 100644 --- a/python/ray/autoscaler/aws/example-full.yaml +++ b/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 (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. diff --git a/python/ray/autoscaler/azure/example-full-legacy.yaml b/python/ray/autoscaler/azure/example-full-legacy.yaml index 702a61868..e817e181b 100644 --- a/python/ray/autoscaler/azure/example-full-legacy.yaml +++ b/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 (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 "$(conda shell.bash hook)"' >> ~/.bashrc - echo 'conda activate py37_tensorflow' >> ~/.bashrc - pip install -U "ray[full] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-2.0.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl" diff --git a/python/ray/autoscaler/azure/example-full.yaml b/python/ray/autoscaler/azure/example-full.yaml index 01ef5d0ef..28b53eb94 100644 --- a/python/ray/autoscaler/azure/example-full.yaml +++ b/python/ray/autoscaler/azure/example-full.yaml @@ -147,7 +147,8 @@ setup_commands: # Note: if you're developing Ray, you probably want to create a Docker image that # has your Ray repo pre-cloned. Then, you can replace the pip installs # below with a git checkout (and possibly a recompile). - # Uncomment the following line if you want to run the nightly version of ray (as opposed to the latest) + # To run the nightly version of ray (as opposed to the latest), either use a rayproject docker image + # that has the "nightly" (e.g. "rayproject/ray-ml:nightly-gpu") or uncomment the following line: - echo 'eval "$(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" diff --git a/python/ray/autoscaler/gcp/example-full-legacy.yaml b/python/ray/autoscaler/gcp/example-full-legacy.yaml index 16848bb19..56a62c0b7 100644 --- a/python/ray/autoscaler/gcp/example-full-legacy.yaml +++ b/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 (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" diff --git a/python/ray/autoscaler/gcp/example-full.yaml b/python/ray/autoscaler/gcp/example-full.yaml index 1cd34f794..5b300d8c2 100644 --- a/python/ray/autoscaler/gcp/example-full.yaml +++ b/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 (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" diff --git a/python/ray/autoscaler/local/example-full.yaml b/python/ray/autoscaler/local/example-full.yaml index cf84aaa44..3d0b9828a 100644 --- a/python/ray/autoscaler/local/example-full.yaml +++ b/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 (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.