How severe does this issue affect your experience of using Ray?
- High: It blocks me to complete my task.
This is my cluster yaml file
cluster_name: ray-minimal
max_workers: 2
upscaling_speed: 1.0
docker:
image: "rayproject/ray:latest-py310-cpu"
container_name: "ray_container"
pull_before_run: True
run_options: # Extra options to pass into "docker run"
- --ulimit nofile=65536:65536
idle_timeout_minutes: 3
provider:
type: aws
region: us-east-1
cache_stopped_nodes: True
auth:
ssh_user: ubuntu
available_node_types:
ray.head.default:
# resources: {"CPU": 1, "GPU": 1, "custom": 5}
resources: {}
node_config:
InstanceType: t2.large
ImageId: ami-0c47a507d2c485dff
BlockDeviceMappings:
- DeviceName: /dev/sda1
Ebs:
VolumeSize: 150
VolumeType: gp3
ray.worker.default:
min_workers: 1
max_workers: 2
resources: {}
node_config:
InstanceType: t2.large
ImageId: ami-0c47a507d2c485dff
BlockDeviceMappings:
- DeviceName: /dev/sda1
Ebs:
VolumeSize: 150
VolumeType: gp3
head_node_type: ray.head.default
file_mounts: {
"~/": "~/scale/"
}
cluster_synced_files: []
file_mounts_sync_continuously: False
rsync_exclude:
- "**/.git"
- "**/.git/**"
rsync_filter:
- ".gitignore"
initialization_commands: []
setup_commands: []
head_setup_commands:
- pwd && ls -lShrt
- ls ~/
- ~/anaconda3/bin/conda env list
- ~/anaconda3/bin/pip install -r src/requirements.txt
worker_setup_commands:
- pwd && ls -lShrt
- ls ~/
- ~/anaconda3/bin/conda env list
- ~/anaconda3/bin/pip install -r src/requirements.txt
head_start_ray_commands:
- ray stop
- ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --dashboard-host=0.0.0.0
worker_start_ray_commands:
- ray stop
- ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076
when I do an Ray Attach
and the do a python --version,
It does not recognises python
When I load the container in my local machine it seems to have anaconda and corresponding python
It fails to setup head node as it does not have anaconda folder ? While when I pull the image in local it has the anaconda folder
Not sure what is changing when I am doing it on a cluster
Any help is appreciated