LengthNormalizationScenario
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.
Two rollouts with one group coefficient and different lengths, averaged per rollout.
Notes
Equation: Composition of mlsysim.solvers.LengthNormalizationModel.solve.
Assumptions: Inputs are routed to LengthNormalizationModel.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 LengthNormalizationModel. 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.ShortAndLongFailureLengths
>>> value = case.result.per_token_ratio
>>> print(f"{value:.3g}")
32Attributes
| Name | Description |
|---|---|
| long_tokens | |
| result | Evaluate the stated length normalization case through LengthNormalizationModel.solve; returns its typed result and quantity units. |
| short_tokens |
short_tokens
Type: int.
Declared default: required.
long_tokens
Type: int.
Declared default: required.
result
engine.scenario_types.LengthNormalizationScenario.result
Evaluate the stated length normalization case through LengthNormalizationModel.solve; returns its typed result and quantity units.
Calculation: mlsysim.solvers.LengthNormalizationModel.solve.