get_services

class torchrl.services.get_services(backend: str = 'ray', **init_kwargs)

Get a distributed service registry.

This function creates or retrieves a service registry for managing distributed actors across workers. Services registered by one worker are immediately visible to all other workers in the cluster.

Parameters:

• backend – Service backend to use. Currently only “ray” is supported.

• **init_kwargs –

  Backend-specific initialization arguments. For Ray:

  • ray_init_config (dict, optional): Arguments to pass to ray.init()

  • namespace (str, optional): Ray namespace for service isolation.

    Defaults to “torchrl_services”.

Returns:

A service registry instance.

Return type:

ServiceBase

Raises:

• ValueError – If an unsupported backend is specified.

• ImportError – If the required backend library is not installed.

Examples

>>> # Basic usage - register and access services
>>> services = get_services()
>>> services.register("tokenizer", TokenizerClass, num_cpus=1)
>>> tokenizer = services["tokenizer"]
>>>
>>> # With custom Ray initialization
>>> services = get_services(
...     backend="ray",
...     ray_init_config={"address": "auto"},
...     namespace="my_experiment"
... )
>>>
>>> # Check if service exists
>>> if "tokenizer" in services:
...     tokenizer = services["tokenizer"]
>>>
>>> # List all registered services
>>> service_names = services.list()