ScopedRevisionScenario
Agents scenarios · Implementation: mlsysim/engine/scenario_definitions/agents.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
A candidate plan of equal nodes, replaced_nodes of which a refuted premise invalidates.
Notes
Equation: result = ScopedRevisionModel.solve(…) with the declared total_nodes, replaced_nodes, tokens_per_node inputs.
Assumptions: The inputs instantiate the assumptions documented by mlsysim.solvers.ScopedRevisionModel.solve; accessing result evaluates that solver again.
Excludes: Any extra mechanism beyond ScopedRevisionModel; this record supplies configuration and does not collect performance measurements.
References
Derivation: This configuration forwards its stored inputs to mlsysim.solvers.ScopedRevisionModel.solve. The solver contract records the equations and their provenance.
Examples
The named scenario supplies illustrative inputs; the output is calculated.
>>> from mlsysim import Scenarios
>>> case = Scenarios.ScopedPlanRevision
>>> round(float(case.result.full_output), 3)
1800.0Attributes
| Name | Description |
|---|---|
| replaced_nodes | |
| result | Modeled result from mlsysim.solvers.ScopedRevisionModel.solve using this |
| tokens_per_node | |
| total_nodes |
total_nodes
Type: int.
Declared default: required.
replaced_nodes
Type: int.
Declared default: required.
tokens_per_node
Type: int.
Declared default: required.
result
engine.scenario_types.ScopedRevisionScenario.result
Modeled result from mlsysim.solvers.ScopedRevisionModel.solve using this scenario’s declared inputs; see that method for units, limits, and feasibility.
Equation: Delegates the declared fields to mlsysim.solvers.ScopedRevisionModel.solve; returned quantities and feasibility follow that contract.