将 Ubuntu 18.04 与 Ray 一起使用。尝试使用以下命令启动本地群集(当前为 1 台服务器，但计划添加更多服务器((从本地服务器上的终端运行(：
ray up my_cluster.yaml
使用以下 yaml 文件：
# An unique identifier for the head node and workers of this cluster.
cluster_name: my_cluster
## NOTE: Typically for local clusters, min_workers == initial_workers == max_workers.
# The minimum number of workers nodes to launch in addition to the head
# node. This number should be >= 0.
# Typically, min_workers == initial_workers == max_workers.
min_workers: 0
# The initial number of worker nodes to launch in addition to the head node.
# Typically, min_workers == initial_workers == max_workers.
initial_workers: 0
# The maximum number of workers nodes to launch in addition to the head node.
# This takes precedence over min_workers.
# Typically, min_workers == initial_workers == max_workers.
max_workers: 0
# Autoscaling parameters.
# Ignore this if min_workers == initial_workers == max_workers.
autoscaling_mode: default
target_utilization_fraction: 0.8
idle_timeout_minutes: 5
# This executes all commands on all nodes in the docker container,
# and opens all the necessary ports to support the Ray cluster.
# Empty string means disabled. Assumes Docker is installed.
docker:
image: "" # e.g., tensorflow/tensorflow:1.5.0-py3
container_name: "" # e.g. ray_docker
# If true, pulls latest version of image. Otherwise, `docker run` will only pull the image
# if no cached version is present.
pull_before_run: True
run_options: [] # Extra options to pass into "docker run"
# Local specific configuration.
provider:
type: local
head_ip: 192.168.10.3
worker_ips: []
# How Ray will authenticate with newly launched nodes.
auth:
ssh_user: user
ssh_private_key: ~/.ssh/id_rsa
# Leave this empty.
head_node: {}
# Leave this empty.
worker_nodes: {}
# Files or directories to copy to the head and worker nodes. The format is a
# dictionary from REMOTE_PATH: LOCAL_PATH, e.g.
file_mounts: {
# "/path1/on/remote/machine": "/path1/on/local/machine",
# "/path2/on/remote/machine": "/path2/on/local/machine",
}
# List of commands that will be run before `setup_commands`. If docker is
# enabled, these commands will run outside the container and before docker
# is setup.
initialization_commands: []
# List of shell commands to run to set up each nodes.
setup_commands:
- source /home/user/.virtualenvs/tune/bin/activate
- pip install ray torch torchvision tabulate tensorboard
# Custom commands that will be run on the head node after common setup.
head_setup_commands: []
# Custom commands that will be run on worker nodes after common setup.
worker_setup_commands: []
# Command to start ray on the head node. You don't need to change this.
head_start_ray_commands:
- source /home/user/.virtualenvs/tune/bin/activate
- ray stop
- ulimit -c unlimited && ray start --head --redis-port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
# Command to start ray on worker nodes. You don't need to change this.
worker_start_ray_commands:
- source /home/user/.virtualenvs/tune/bin/activate
- ray stop
- ray start --redis-address=$RAY_HEAD_IP:6379
运行命令后，我收到很多错误，例如：
bash: cannot set terminal process group (-1): Inappropriate ioctl for device
bash: no job control in this shell
我在这里做错了什么？ 感谢您的帮助。
bash：无法设置终端进程组 (-1(：不合适的 ioctl 设备 bash：此外壳中没有作业控制
通常，这些是无害的错误。