Source code for simplebench.stats.operation_timings
# -*- coding: utf-8 -*-
"""Containers for benchmark statistics"""
from __future__ import annotations
from typing import Optional, Sequence
from ..defaults import DEFAULT_INTERVAL_SCALE, DEFAULT_INTERVAL_UNIT
from ..exceptions import SimpleBenchTypeError
from ..iteration import Iteration
from ..validators import validate_sequence_of_numbers
from . import Stats, StatsSummary
from .exceptions.operation_timings import _OperationTimingsErrorTag
[docs]
class OperationTimings(Stats):
"""Container for the operation timing statistics of a benchmark.
:ivar unit: The unit of measurement for the timings (e.g., "ns").
:vartype unit: str
:ivar scale: The scale factor for the timings (e.g., "1e-9" for nanoseconds).
:vartype scale: float
:ivar rounds: The number of data points in the benchmark.
:vartype rounds: int
:ivar data: Tuple of timing data points.
:vartype data: tuple[int | float, ...]
:ivar mean: The mean time per operation.
:vartype mean: float
:ivar median: The median time per operation.
:vartype median: float
:ivar minimum: The minimum time per operation.
:vartype minimum: float
:ivar maximum: The maximum time per operation.
:vartype maximum: float
:ivar standard_deviation: The standard deviation of the time per operation.
:vartype standard_deviation: float
:ivar relative_standard_deviation: The relative standard deviation of the time per
operation.
:vartype relative_standard_deviation: float
:ivar percentiles: Percentiles of time per operation.
:vartype percentiles: dict[int, float]
"""
def __init__(self,
*,
iterations: Sequence[Iteration] | None = None,
unit: str = DEFAULT_INTERVAL_UNIT,
scale: float = DEFAULT_INTERVAL_SCALE,
rounds: int = 1,
data: Optional[Sequence[int | float]] = None):
"""Construct OperationTimings stats from Iteration or raw timing data.
:param iterations: Sequence of
:class:`~simplebench.iteration.Iteration` objects to extract timing data from.
:param unit: The unit of measurement for the timings (e.g., "ns").
:param scale: The scale factor for the timings (e.g., "1e-9" for nanoseconds).
:param rounds: The number of data points in the benchmark.
:param data: Optional sequence of timing data points. If not provided,
timing data will be extracted from the iterations if available.
:raises ~simplebench.exceptions.SimpleBenchTypeError: If any of the arguments are
of the wrong type.
:raises ~simplebench.exceptions.SimpleBenchValueError: If any of the arguments have
invalid values.
"""
if iterations is None and data is None:
raise SimpleBenchTypeError(
"either iterations or data must be provided",
tag=_OperationTimingsErrorTag.NO_DATA_OR_ITERATIONS_PROVIDED)
if data is None:
data = []
imported_data: list[int | float] = list(validate_sequence_of_numbers(
data, 'data',
type_tag=_OperationTimingsErrorTag.INVALID_DATA_ARG_TYPE,
value_tag=_OperationTimingsErrorTag.INVALID_DATA_ARG_VALUE))
if iterations is not None:
if not isinstance(iterations, Sequence):
raise SimpleBenchTypeError(
"passed iterations arg is not a Sequence",
tag=_OperationTimingsErrorTag.INVALID_ITERATIONS_ARG_TYPE)
if not all(isinstance(iteration, Iteration) for iteration in iterations):
raise SimpleBenchTypeError(
"There are items in the iterations arg sequence that are not Iteration objects",
tag=_OperationTimingsErrorTag.INVALID_ITERATIONS_ITEM_ARG_TYPE)
imported_data.extend(iteration.per_round_elapsed for iteration in iterations)
super().__init__(unit=unit, scale=scale, rounds=rounds, data=imported_data)
[docs]
class OperationTimingsSummary(StatsSummary):
"""Container for summary of operation timing statistics of a benchmark.
:ivar unit: The unit of measurement for the benchmark (e.g., "ops/s").
:vartype unit: str
:ivar scale: The scale factor for the interval (e.g. 1 for seconds).
:vartype scale: float
:ivar rounds: The number of data points in the benchmark.
:vartype rounds: int
:ivar mean: The mean operations per time interval.
:vartype mean: float
:ivar median: The median operations per time interval.
:vartype median: float
:ivar minimum: The minimum operations per time interval.
:vartype minimum: float
:ivar maximum: The maximum operations per time interval.
:vartype maximum: float
:ivar standard_deviation: The standard deviation of operations per time interval.
:vartype standard_deviation: float
:ivar relative_standard_deviation: The relative standard deviation of ops per time
interval.
:vartype relative_standard_deviation: float
:ivar percentiles: Percentiles of operations per time interval.
:vartype percentiles: dict[int, float]
"""