SamplingScenario
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.
One fixed logit vector at a base and a sharpened temperature, then top-p at the base.
Notes
Equation: Compose mlsysim.solvers.SamplingModel.
Assumptions: The stated fields are inputs to mlsysim.solvers.SamplingModel; its documented validity regime, units, and modeling choices apply unchanged.
Excludes: This scenario adds no measurement, empirical calibration, or mechanisms beyond mlsysim.solvers.SamplingModel.
References
Derivation: this scenario binds its input fields to the referenced implementation contracts: mlsysim.solvers.SamplingModel. The methods below identify any additional arithmetic.
Examples
>>> from mlsysim import Scenarios
>>> case = Scenarios.TemperatureNucleusExample
>>> type(case.result).__name__
'SamplingResult'Attributes
| Name | Description |
|---|---|
| base_temperature | |
| logits | |
| result | Evaluate this scenario through mlsysim.solvers.SamplingModel.solve. Equation: pass |
| sharp_temperature | |
| top_p |
logits
Type: List[float].
Declared default: required.
base_temperature
Type: float.
Declared default: required.
sharp_temperature
Type: float.
Declared default: required.
top_p
Type: float.
Declared default: required.
result
engine.scenario_types.SamplingScenario.result
Evaluate this scenario through mlsysim.solvers.SamplingModel.solve. Equation: pass the stated fields to that implementation; its contract defines the calculation and feasibility tests. Units: each returned field follows the referenced result schema; no independent equation is evaluated by this wrapper.