ObservationCarryScenario
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 raw tool output sized in windows, and its shaped view carried by later calls.
Notes
Equation: Result = mlsysim.solvers.ObservationCarryModel.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 ObservationCarryModel.solve; this class binds one reproducible configuration.
Excludes: Any behavior excluded by ObservationCarryModel.solve, and measurement or calibration of the supplied inputs.
References
Implementation reference: mlsysim.solvers.ObservationCarryModel.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.TwentyFourMegabyteLogObservation
>>> round((scenario.result.raw_tokens).to('token').magnitude, 6)
8000000.0Attributes
| Name | Description |
|---|---|
| bytes_per_token | |
| cached_fraction | |
| carry_calls | |
| input_price | |
| raw_bytes | |
| result | Return mlsysim.solvers.ObservationCarryModel.solve for this scenario; output fields retain the units and feasibility semantics specified by that solver. |
| shaped_tokens | |
| window |
raw_bytes
Type: Quantity.
Declared default: required.
bytes_per_token
Type: Quantity.
Declared default: required.
window
Type: int.
Declared default: required.
shaped_tokens
Type: int.
Declared default: required.
carry_calls
Type: int.
Declared default: required.
input_price
Type: Quantity.
Declared default: required.
cached_fraction
Type: float.
Declared default: required.
result
engine.scenario_types.ObservationCarryScenario.result
Return mlsysim.solvers.ObservationCarryModel.solve for this scenario; output fields retain the units and feasibility semantics specified by that solver.
Equation: mlsysim.solvers.ObservationCarryModel.solve (scenario fields).