RetryPolicyScenario
Economics scenarios · Implementation: mlsysim/engine/scenario_definitions/economics.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
A cheap attempt retried up to a cap, run as a batch, or one stronger attempt.
Notes
Equation: The result property delegates to the named solver documented below; it converts declared scenario units before passing the inputs.
Assumptions: Attempt successes are independent with fixed probability and fixed per-attempt charges.
Excludes: Correlated failure causes, changing retry quality, and latency scheduling.
References
Derivation: the scenario composes mlsysim.solvers.RetryPolicyModel. Their contracts supply the underlying equations; property equations show the remaining unit conversions and accounting.
Examples
>>> from mlsysim import Scenarios
>>> scenario = Scenarios.CheapRetryAgainstStrongCall
>>> value = scenario.result
>>> type(value).__name__
'RetryPolicyResult'Attributes
| Name | Description |
|---|---|
| attempt_cost | |
| max_attempts | |
| pass_probability | |
| result | Return the typed accounting result from RetryPolicyModel using this scenario’s |
| strong_attempt_cost | |
| strong_pass_probability |
pass_probability
Type: float.
Declared default: required.
attempt_cost
Type: Quantity.
Declared default: required.
max_attempts
Type: int.
Declared default: required.
strong_pass_probability
Type: float.
Declared default: required.
strong_attempt_cost
Type: Quantity.
Declared default: required.
result
engine.scenario_types.RetryPolicyScenario.result
Return the typed accounting result from RetryPolicyModel using this scenario’s declared inputs; units and exclusions follow that solver contract.
Equation: RetryPolicyModel().solve(pass_probability, attempt_cost, max_attempts, strong_pass_probability, strong_attempt_cost).