saealib.EvaluationPlanStage#

class saealib.EvaluationPlanStage(planner=None, n_eval=None)[source]#

Bases: Stage

Create an owned request and pending record.

Increments state.decision_count by exactly one whenever a genuinely new plan is confirmed (the branch that calls the planner and builds pending_evaluations), never on a continuation of an already-pending multi-request plan. One decision covers the whole confirmed EvaluationPlan, however many candidates its requests evaluate. decision_count counts a genuinely new evaluation plan confirmed by the runtime regardless of execution mode: this method increments it for synchronous execution; AsyncEvaluationSubmitStage (which execute_async() delegates to) increments it the same way for async/steady-state execution.

Parameters:: planner (EvaluationPlanner | None)

Methods

`__init__`	Initialize base Stage attributes.
`contract`	Return this stage's structural and direct state-access contract.
`execute`	Execute this stage and return the updated state.
`execute_async`	Submit through the public async execution seam.
`has_async_work`
`to_pseudocode`	Render this stage as a LaTeX algorithmic line.
`to_text`	Render this stage as a plain-text algorithmic line.

Method Details

EvaluationPlanStage.__init__(planner=None, n_eval=None)[source]#

Initialize base Stage attributes.

Parameters:

name (str, optional) – Override the class-level name.
label (str, optional) – Override the class-level label.
notation (str, optional) – Override the class-level notation.
planner (EvaluationPlanner | None)

Return type:

None

EvaluationPlanStage.contract()[source]#

Return this stage’s structural and direct state-access contract.

Return type:: ComponentContract

EvaluationPlanStage.execute(state)[source]#

Execute this stage and return the updated state.

Parameters:: state (OptimizationState) – Current optimization state.
Returns:: Updated state.
Return type:: OptimizationState

EvaluationPlanStage.execute_async(state, *, scheduler, feedback_builder=None, algorithm=None, callback_manager=None, prefix=None, strategy=None)[source]#

Submit through the public async execution seam.

Runtime supplies lifecycle services and a prefix callback; planning and refill decisions remain owned by this stage.

Parameters:

state (OptimizationState)
scheduler (Any)
feedback_builder (FeedbackBuilder | None)
algorithm (Any)
callback_manager (Any)
strategy (Any)

Return type:

OptimizationState

EvaluationPlanStage.has_async_work(state)[source]#

Parameters:: state (OptimizationState)
Return type:: bool

EvaluationPlanStage.to_pseudocode(*, expand=False, indent=0)#

Render this stage as a LaTeX algorithmic line.

Parameters:

expand (bool) – If True and this stage has sub-stages, recursively expand them.
indent (int) – Current indentation level (number of \State indent steps).

Returns:

LaTeX algorithmic fragment.

Return type:

str

EvaluationPlanStage.to_text(*, expand=False, indent=0)#

Render this stage as a plain-text algorithmic line.

Parameters:

expand (bool)
indent (int)

Return type:

str