update_reward `async` ¶

update_reward(
    job_arn: JobArn,
    trajectory_id: TrajectoryId,
    rewards: DoubleList,
    *,
    config_overrides: Optional[AsyncSagemakerJobRuntimeClientConfig] = None,
    client_token: Optional[str] = None,
) -> UpdateRewardResponse

Updates the reward values for a trajectory and transitions it to reward-received status, signaling that it is eligible for processing. Call this operation after CompleteRollout to provide the computed reward scores.

Parameters:

job_arn (JobArn) –

The job ARN.
trajectory_id (TrajectoryId) –

The trajectory ID to update with reward values.
rewards (DoubleList) –

The list of reward values to assign to this trajectory. Provide one reward value per turn in the trajectory.
client_token (Optional[str], default: None ) –

A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

Raises:

AccessDeniedException –

You do not have permission to perform this operation.
ConflictException –

The request conflicts with the current state of the resource.
InternalServiceError –

An internal service error occurred. Retry the request.
ResourceNotFoundException –

The specified resource was not found.
ServiceQuotaExceededException –

You have exceeded a service quota.
ThrottlingException –

The request was throttled. Retry the request after a brief wait.
ValidationException –

The request is not valid. Check the request syntax and parameters
UnknownServiceError –

The service returned an error code this client does not model.

Examples:

Invoke UpdateReward Updates the reward values for a completed trajectory.

>>> await client.update_reward(job_arn='arn:aws:sagemaker:us-east-1:123456789012:job/AgentRFT/my-training-job', trajectory_id='trajectory-001', rewards=[0.85, 0.92, 0.78])

Source code in docs_src/capo_sagemakerjobruntime/_services/async_sagemaker_job_runtime.py

async def update_reward(
    self,
    job_arn: "capo_sagemakerjobruntime.types.job_arn.JobArn",
    trajectory_id: "capo_sagemakerjobruntime.types.trajectory_id.TrajectoryId",
    rewards: "capo_sagemakerjobruntime.types.double_list.DoubleList",
    *,
    config_overrides: Optional[AsyncSagemakerJobRuntimeClientConfig] = None,
    client_token: Optional[str] = None,
) -> "capo_sagemakerjobruntime.types.update_reward_response.UpdateRewardResponse":
    """Updates the reward values for a trajectory and transitions it to reward-received status, signaling that it is eligible for processing. Call this operation after CompleteRollout to provide the computed reward scores.

    Args:
        job_arn: The job ARN.
        trajectory_id: The trajectory ID to update with reward values.
        rewards: The list of reward values to assign to this trajectory. Provide one reward value per turn in the trajectory.
        client_token: A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

    Raises:
        capo_sagemakerjobruntime.errors.access_denied_exception.AccessDeniedException: You do not have permission to perform this operation.
        capo_sagemakerjobruntime.errors.conflict_exception.ConflictException: The request conflicts with the current state of the resource.
        capo_sagemakerjobruntime.errors.internal_service_error.InternalServiceError: An internal service error occurred. Retry the request.
        capo_sagemakerjobruntime.errors.resource_not_found_exception.ResourceNotFoundException: The specified resource was not found.
        capo_sagemakerjobruntime.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: You have exceeded a service quota.
        capo_sagemakerjobruntime.errors.throttling_exception.ThrottlingException: The request was throttled. Retry the request after a brief wait.
        capo_sagemakerjobruntime.errors.validation_exception.ValidationException: The request is not valid. Check the request syntax and parameters
        capo_sagemakerjobruntime.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        Invoke UpdateReward
        Updates the reward values for a completed trajectory.

        >>> await client.update_reward(job_arn='arn:aws:sagemaker:us-east-1:123456789012:job/AgentRFT/my-training-job', trajectory_id='trajectory-001', rewards=[0.85, 0.92, 0.78])
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_sagemakerjobruntime.types.update_reward_request.UpdateRewardRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemakerjobruntime.types.update_reward_response.UpdateRewardResponse"
    ]:
        import capo_sagemakerjobruntime._operations.agentic_rft_runtime_service.update_reward

        (
            output,
            http_response,
        ) = await capo_sagemakerjobruntime._operations.agentic_rft_runtime_service.update_reward.async_update_reward(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateReward")
    )
    input_: capo_sagemakerjobruntime.types.update_reward_request.UpdateRewardRequest = {
        "job_arn": job_arn,
        "trajectory_id": trajectory_id,
        "rewards": rewards,
    }
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output

update_reward async ¶

update_reward `async` ¶