ContinuationForkCostScenario
Training scenarios · Implementation: mlsysim/engine/scenario_definitions/training.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
A trajectory whose value is sampled by forking continuations at chosen turns.
Notes
Equation: Composition of mlsysim.solvers.ContinuationForkCostModel.solve.
Assumptions: Inputs are routed to ContinuationForkCostModel.solve; their documented regimes and units apply to this configuration.
Excludes: Additional mechanisms beyond the linked solver contracts; the scenario does not collect measurements.
References
Derivation: This scenario binds named inputs to ContinuationForkCostModel. The linked solver contracts own equations, sources, and result-unit definitions.
Examples
Evaluate the named configuration and display a modeled result.
>>> from mlsysim import Scenarios
>>> case = Scenarios.ThirtyTurnForksAtEveryBoundary
>>> value = case.result.multiple
>>> print(f"{value:.3g}")
117Attributes
| Name | Description |
|---|---|
| boundaries | |
| branches | |
| result | Evaluate the stated continuation fork cost case through ContinuationForkCostModel.solve; returns its typed result and quantity units. |
| tokens_per_turn | |
| turns |
turns
Type: int.
Declared default: required.
tokens_per_turn
Type: int.
Declared default: required.
branches
Type: int.
Declared default: required.
boundaries
Type: Optional[List[int]].
Declared default: None.
result
engine.scenario_types.ContinuationForkCostScenario.result
Evaluate the stated continuation fork cost case through ContinuationForkCostModel.solve; returns its typed result and quantity units.
Calculation: mlsysim.solvers.ContinuationForkCostModel.solve.