wehub-resource-sync
78 lines
2.3 KiB
Python
78 lines
2.3 KiB
Python
"""Per-call overhead micro-benchmarks for the rr.log() pipeline.
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See README.md for usage.
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"""
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from __future__ import annotations
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from typing import Any
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import numpy as np
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import pytest
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import rerun as rr
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import rerun_bindings as bindings
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from rerun._log import _log_components
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ARCHETYPE_CASES = [
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pytest.param(lambda: rr.Scalars(42.0), id="Scalars"),
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pytest.param(
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lambda: rr.Points3D([[1, 2, 3]], colors=[0xFF0000FF], radii=[0.1]),
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id="Points3D",
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),
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pytest.param(
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lambda: rr.Transform3D(translation=[1, 2, 3], mat3x3=np.eye(3, dtype=np.float32)),
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id="Transform3D",
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),
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pytest.param(
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lambda: rr.Boxes3D(half_sizes=[[1, 2, 3]], colors=[0xFF0000FF]),
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id="Boxes3D",
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),
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]
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def _init() -> None:
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"""Common setup: init rerun + memory recording."""
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rr.init("rerun_example_micro_benchmark", spawn=False)
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rr.memory_recording()
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@pytest.mark.parametrize("make_archetype", ARCHETYPE_CASES)
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def test_bench_micro_construct(benchmark: Any, make_archetype: Any) -> None:
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_init()
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benchmark(make_archetype)
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@pytest.mark.parametrize("make_archetype", ARCHETYPE_CASES)
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def test_bench_micro_as_component_batches(benchmark: Any, make_archetype: Any) -> None:
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_init()
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archetype = make_archetype()
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benchmark(archetype.as_component_batches)
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@pytest.mark.parametrize("make_archetype", ARCHETYPE_CASES)
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def test_bench_micro_log_components(benchmark: Any, make_archetype: Any) -> None:
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_init()
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batches = make_archetype().as_component_batches()
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benchmark(_log_components, "test_entity", batches)
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@pytest.mark.parametrize("make_archetype", ARCHETYPE_CASES)
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def test_bench_micro_log_arrow_msg(benchmark: Any, make_archetype: Any) -> None:
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_init()
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batches = make_archetype().as_component_batches()
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instanced = {b.component_descriptor(): b.as_arrow_array() for b in batches if b.as_arrow_array() is not None}
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benchmark(bindings.log_arrow_msg, "test_entity", components=instanced, static_=False, recording=None)
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@pytest.mark.parametrize("make_archetype", ARCHETYPE_CASES)
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def test_bench_micro_log(benchmark: Any, make_archetype: Any) -> None:
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_init()
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archetype = make_archetype()
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benchmark(rr.log, "test_entity", archetype)
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def test_bench_micro_set_time(benchmark: Any) -> None:
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_init()
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benchmark(rr.set_time, "frame", sequence=42)
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