aitune.torch.task.profiling.measuring_strategy

Measuring strategies for profiling.

Module Contents

Classes

Name	Description
`MeasuringStrategy`	Strategy how do the measurement and create a ProfilingResultEvent(s).
`ModelExecutionTimeMeasuringStrategy`	Strategy to measure execution time.

API

class aitune.torch.task.profiling.measuring_strategy.MeasuringStrategy()

Abstract

Strategy how do the measurement and create a ProfilingResultEvent(s).

aitune.torch.task.profiling.measuring_strategy.MeasuringStrategy.do_measurement(
    batch_size: int,
    model: collections.abc.Callable,
    sample: tuple[list, dict],
    kwargs = {}
) -> list[aitune.torch.task.profiling.events.ProfilingResultEvent]

abstract

Do the measurement and create a ProfilingResultEvent(s).

Parameters:

batch_size

int

Batch size of the measurement.

model

Callable

Model to measure.

sample

tuple[list, dict]

Sample to measure.

**kwargs

Defaults to {}

Additional keyword arguments.

Returns: list[ProfilingResultEvent]

List of ProfilingResultEvent(s).

class aitune.torch.task.profiling.measuring_strategy.ModelExecutionTimeMeasuringStrategy()

Bases: MeasuringStrategy

Strategy to measure execution time.

counter

int = 0

aitune.torch.task.profiling.measuring_strategy.ModelExecutionTimeMeasuringStrategy.do_measurement(
    batch_size: int,
    model: collections.abc.Callable,
    sample: tuple[list, dict],
    measurement_kwargs = {}
) -> list[aitune.torch.task.profiling.events.ProfilingResultEvent]

Do the measurement and create a ProfilingResultEvent(s) for the model.