EncoderRateScenario
Robotics scenarios · Implementation: mlsysim/engine/scenario_definitions/robotics/estimation.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
An encoder of flop_per_frame on every site.machine navigation frame, against the host SoC’s dense FP16 peak.
Notes
Equation: result evaluates the configured solver; its contract owns the governing equations.
Assumptions: Every camera frame incurs the supplied encoder FLOPs at the registered dense FP16 peak.
Excludes: Memory limits, effective kernel efficiency, and keyframe-rate fields in this result.
References
Derivation: The scenario binds declared inputs to EncoderRateModel. Those implementations document their derivations and sources.
Examples
Execute the registered worked inputs; this is a modeled calculation.
>>> from mlsysim import Scenarios
>>> case = Scenarios.WarehouseFoundationEncoderAtCameraRate
>>> value = case.result
>>> print(f"{value.required:.3f~P}")
180.000 TFLOPs/sAttributes
| Name | Description |
|---|---|
| flop_per_frame | |
| keyframe_rate_high | |
| keyframe_rate_low | |
| result | Evaluate the configured inputs with mlsysim.solvers.EncoderRateModel.solve. |
| site |
site
Type: Any.
Declared default: required.
flop_per_frame
Type: Quantity.
Declared default: required.
keyframe_rate_low
Type: Optional[Quantity].
Declared default: None.
keyframe_rate_high
Type: Optional[Quantity].
Declared default: None.
result
engine.scenario_types.EncoderRateScenario.result
Evaluate the configured inputs with mlsysim.solvers.EncoderRateModel.solve.
The returned typed result retains the solver’s documented units, assumptions, and feasibility semantics; this property adds no measurement or safety claim. Equation: result = EncoderRateModel().solve(...) using the fields shown below.