rlmesh.torch.RemoteVectorEnv

classExperimentalfrom rlmesh.torch import RemoteVectorEnv[source]

Experimental Torch-backed remote client for vectorized environments.

RemoteVectorEnv(
    address: str | None = None,
    *,
    host: str | None = None,
    port: int | None = None,
    path: str | None = None,
    transport: Transport | None = None,
    connect_timeout_seconds: float | None = None,
    request_timeout_seconds: float | None = None,
    workflow_edition: str | None = None,
) -> None

A vector client connects one model process to an endpoint that owns multiple environment instances. Batched observations, rewards, terminations, and truncations decode into Torch values.

Parameters

Name	Type	Description
`address`	`str \| None`	Endpoint address such as `"tcp://127.0.0.1:5555"`.
`host`	`str \| None`	TCP host helper used when `address` is omitted.
`port`	`int \| None`	TCP port helper used when `address` is omitted.
`path`	`str \| None`	Unix socket path helper used when `address` is omitted.
`transport`	`Transport \| None`	Explicit transport selector.
`connect_timeout_seconds`	`float \| None`	Optional dial timeout in seconds; `None` uses the native default.
`request_timeout_seconds`	`float \| None`	Optional per-request (reset/step/render) timeout in seconds; `None` waits indefinitely.

Examples

>>> from rlmesh.torch import RemoteVectorEnv
>>> envs = RemoteVectorEnv("127.0.0.1:5555")
>>> observations, infos = envs.reset(seed=42)
>>> actions = [
...     envs.single_action_space.sample() for _ in range(envs.num_envs)
... ]
>>> observations, rewards, terminations, truncations, infos = envs.step(
...     actions
... )
>>> envs.close()

Attributes

num_envsNumber of environment instances served by the endpoint.
single_observation_spaceObservation space for one environment in the vector.
single_action_spaceAction space for one environment in the vector.
observation_spaceAlias for single_observation_space.
action_spaceAlias for single_action_space.
addressEndpoint address this client is connected to.
env_idThis connection's container id (UUIDv7).
selected_workflow_editionThe workflow edition this connection negotiated with the env.
env_contractEnvironment contract returned by the endpoint handshake.
render_modeConfigured render mode reported by the endpoint.
metadataEndpoint metadata reported by the environment contract.
observation_space_specNative observation space spec reported by the endpoint.
action_space_specNative action space spec reported by the endpoint.

Methods

reset()Reset all remote environments and decode the observations.
step()Step all remote environments with a batch of actions.
render()Render a frame from the remote environment.
close()Detach this client from the remote endpoint.
shutdown()Request owner-level shutdown of the remote environment endpoint.

num_envs

property[source]

property num_envs: int

Number of environment instances served by the endpoint.

single_observation_space

property[source]

property single_observation_space: Space[ValueT]

Observation space for one environment in the vector.

single_action_space

property[source]

property single_action_space: Space[ActionT]

Action space for one environment in the vector.

reset

function[source]

reset(
    *,
    seed: int | list[int] | None = None,
    options: dict[str, object] | None = None,
) -> tuple[ValueT, ResetInfo]

Reset all remote environments and decode the observations.

Parameters

Name	Type	Description
`seed`	`int \| list[int] \| None`	Optional seed or per-environment seed list.
`options`	`dict[str, object] \| None`	Optional reset options forwarded to the vector environment.

Returns

Type	Description
`tuple[ValueT, ResetInfo]`	Batched decoded observations and reset info dictionary.

step

function[source]

step(
    actions: ActionT,
) -> tuple[ValueT, ValueT, ValueT, ValueT, StepInfo]

Step all remote environments with a batch of actions.

Parameters

Name	Type	Description
`actions`	`ActionT`	Batched actions accepted by the vector endpoint.

Returns

Type	Description
`tuple[ValueT, ValueT, ValueT, ValueT, StepInfo]`	Batched observations, rewards, terminations, truncations, and info.

address

property[source]

property address: str

Endpoint address this client is connected to.

env_id

property[source]

property env_id: str

This connection’s container id (UUIDv7).

A stable correlation identity, distinct from the human env name (env_contract.id).

selected_workflow_edition

property[source]

property selected_workflow_edition: str

The workflow edition this connection negotiated with the env.

The highest edition both sides can drive, at or below whatever either declared, in the exact spelling they agreed on – so a prerelease build reports its cohort, not the bare sealed base. Named apart from the workflow_edition declaration surfaces on purpose: this is what was agreed, not what this side asked for.

env_contract

property[source]

property env_contract: EnvContract

Environment contract returned by the endpoint handshake.

render_mode

property[source]

property render_mode: str | None

Configured render mode reported by the endpoint.

metadata

property[source]

property metadata: Metadata

Endpoint metadata reported by the environment contract.

observation_space_spec

property[source]

property observation_space_spec: SpaceSpec

Native observation space spec reported by the endpoint.

action_space_spec

property[source]

property action_space_spec: SpaceSpec

Native action space spec reported by the endpoint.

render

function[source]

render(*, env_index: int = 0) -> ValueT | None

Render a frame from the remote environment.

Parameters

Name	Type	Description
`env_index`	`int`	Environment index to render. Single environments use `0`.

Returns

Type	Description
`ValueT \| None`	A decoded render frame, or `None` when the environment has no frame.

close

function[source]

close() -> None

Detach this client from the remote endpoint.

shutdown

function[source]

shutdown(reason: str = 'owner shutdown') -> bool

Request owner-level shutdown of the remote environment endpoint.