ModelPollingScenario
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 model that checks a pending job at a fixed interval until it completes.
Notes
Equation: Result = mlsysim.solvers.ModelPollingModel.solve with the named scenario fields; no extra fitting or postprocessing is applied.
Assumptions: The supplied inputs use the units and validity regime documented by ModelPollingModel.solve; this class binds one reproducible configuration.
Excludes: Any behavior excluded by ModelPollingModel.solve, and measurement or calibration of the supplied inputs.
References
Implementation reference: mlsysim.solvers.ModelPollingModel.solve documents the composed equation and its sources.
Examples
The named registry scenario supplies the stated inputs; this is a modeled calculation, not a new measurement.
>>> from mlsysim import Scenarios
>>> scenario = Scenarios.ModelPollingEveryFiveSeconds
>>> scenario.result.polls
59Attributes
| Name | Description |
|---|---|
| cache_hit | |
| cached_fraction | |
| context_tokens | |
| input_price | |
| job_duration | |
| output_price | |
| output_tokens | |
| poll_interval | |
| result | Return mlsysim.solvers.ModelPollingModel.solve for this scenario; output fields retain the units and feasibility semantics specified by that solver. |
job_duration
Type: Quantity.
Declared default: required.
poll_interval
Type: Quantity.
Declared default: required.
context_tokens
Type: int.
Declared default: required.
output_tokens
Type: int.
Declared default: required.
cache_hit
Type: float.
Declared default: required.
input_price
Type: Quantity.
Declared default: required.
cached_fraction
Type: float.
Declared default: required.
output_price
Type: Quantity.
Declared default: required.
result
engine.scenario_types.ModelPollingScenario.result
Return mlsysim.solvers.ModelPollingModel.solve for this scenario; output fields retain the units and feasibility semantics specified by that solver.
Equation: mlsysim.solvers.ModelPollingModel.solve (scenario fields).