列出本地集群错误 - 无法设置终端进程组

Question

使用 Ubuntu 18.04 和 Ray。尝试使用以下命令（来自本地服务器上的终端的运行）启动本地集群（当前有 1 个服务器，但计划添加更多）：

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

在运行命令之后我收到很多错误，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。

Answer 1

bash: cannot set terminal process group (-1): Inappropriate ioctl for device bash: no job control in this shell

一般来说，这些都是无害的错误。

列出本地集群错误 - 无法设置终端进程组

ray up local cluster errors - cannot set terminal process group

ray