Configuration Files

Valohai generates two configuration files during Distributed Task executions: /valohai/config/distributed.json and /valohai/config/distributed.yaml.

Both files contain identical information in different formats. These files are only present in executions that are part of a Distributed Task.

Reading configuration files

The valohai-utils Python package includes helpers under valohai.distributed to read and use these configuration files.

You can also parse the files manually if you're not using Python or prefer direct access.

Configuration structure

Top-level fields

Field	Type	Description
config	Object	Task-level configuration (group name, member ID, worker count)
members	Array	List of all workers in the Distributed Task
self	Object	Details about the current worker (duplicate of this worker's entry in members)

config object

Field	Type	Description
group_name	String	Distributed group identifier, typically derived from the Task ID
member_id	String	Unique identifier for the worker reading this configuration file
required_count	Integer	Total number of workers expected in this Distributed Task

members array

Each object in members represents one worker in the Distributed Task.

Field	Type	Description
announce_time	String	ISO 8601 timestamp when the worker joined the group
identity	String	Machine identifier (depends on infrastructure)
job_id	String	Execution identifier for this worker
member_id	String	Unique member identifier (typically a number as a string: "0", "1", "2")
network	Object	Network connection details (see below)

network object

Field	Type	Description
exposed_ports	Object	Map of host port to container port (e.g., {"1234": "1234"}). Empty if all ports are exposed via VH_DOCKER_NETWORK=host.
local_ips	Array	List of local IP addresses to reach this worker
public_ips	Array	List of public IP addresses to reach this worker (if available)

self object

The self object is a convenience field that duplicates the current worker's entry from the members array. It has the same structure as a members object.

Example configuration file

{
  "config": {
    "group_name": "task-0180f5a9-9ffe-4e09-d5a7-9a0a507019d4",
    "member_id": "0",
    "required_count": 3
  },
  "members": [
    {
      "announce_time": "2022-05-24T10:42:57",
      "identity": "happy-yjaqaqlx",
      "job_id": "exec-0180f5a9-a002-45a0-f0e6-8e98720eeaad",
      "member_id": "0",
      "network": {
        "exposed_ports": {
          "1234": "1234"
        },
        "local_ips": [
          "10.0.16.61"
        ],
        "public_ips": [
          "34.121.32.110"
        ]
      }
    },
    {
      "announce_time": "2022-05-24T10:42:58",
      "identity": "happy-kwfncqxe",
      "job_id": "exec-0180f5a9-a007-633b-8af3-e11593482653",
      "member_id": "2",
      "network": {
        "exposed_ports": {
          "1234": "1234"
        },
        "local_ips": [
          "10.0.16.60"
        ],
        "public_ips": [
          "34.134.18.149"
        ]
      }
    },
    {
      "announce_time": "2022-05-24T10:42:57",
      "identity": "happy-tcuaezxm",
      "job_id": "exec-0180f5a9-a005-f2ef-693a-3b4c4c115ed8",
      "member_id": "1",
      "network": {
        "exposed_ports": {
          "1234": "1234"
        },
        "local_ips": [
          "10.0.16.59"
        ],
        "public_ips": [
          "35.194.55.255"
        ]
      }
    }
  ],
  "self": {
    "announce_time": "2022-05-24T10:42:57",
    "identity": "happy-yjaqaqlx",
    "job_id": "exec-0180f5a9-a002-45a0-f0e6-8e98720eeaad",
    "member_id": "0",
    "network": {
      "exposed_ports": {
        "1234": "1234"
      },
      "local_ips": [
        "10.0.16.61"
      ],
      "public_ips": [
        "34.121.32.110"
      ]
    }
  }
}

Using configuration in Python

The valohai-utils package provides helpers to read this configuration:

import valohai

# Get all workers
members = valohai.distributed.members()
for member in members:
    print(member.primary_local_ip)

# Get the master worker (first to announce)
master = valohai.distributed.master()
master_url = f"tcp://{master.primary_local_ip}:1234"

# Get current worker details
me = valohai.distributed.me()
rank = valohai.distributed.rank
size = valohai.distributed.required_count

Using configuration manually

Read the JSON or YAML file directly:

import json

with open('/valohai/config/distributed.json') as f:
    config = json.load(f)

# Get current worker's member_id
my_member_id = config['config']['member_id']

# Get all worker IPs
worker_ips = [m['network']['local_ips'][0] for m in config['members']]

# Get master worker (member_id "0")
master = next(m for m in config['members'] if m['member_id'] == "0")
master_ip = master['network']['local_ips'][0]

Next steps

• Running Distributed Tasks

• Distributed Examples Repository

• Distributed Training Concepts