reference/generated/torchrl.modules.inference_server.RayTransport

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RayTransport

class torchrl.modules.inference_server.RayTransport(*, max_queue_size: int = 1000)

Transport using Ray queues for distributed inference.

Uses ray.util.queue.Queue for both request submission and response routing. Per-actor response queues ensure correct result routing without serialising Queue objects through other queues.

Ray is imported lazily at instantiation time; importing the class itself does not require Ray.

Keyword Arguments:

max_queue_size (int) – maximum size of the request queue. Default: 1000.

Example

>>> import ray
>>> ray.init()
>>> transport = RayTransport()
>>> client = transport.client()
>>> # pass *client* to a Ray actor for remote inference requests

client() → _QueueInferenceClient

Create an actor-side client with a dedicated Ray response queue.

Returns:

A _QueueInferenceClient that can be used inside any Ray actor or the driver process.