mirror of
https://github.com/azaion/gps-denied-onboard.git
synced 2026-06-21 18:01:14 +00:00
Oleksandr Bezdieniezhnykh
f01a5058ab
Implements the C10 internal phase that walks every C6 tile, embeds through C2's backbone via the AZ-321-produced engine, and rebuilds the AZ-306 FAISS HNSW index in one atomic write. - DescriptorBatcher with halve-and-retry OOM recovery (default 1 retry) - BackboneEmbedder Protocol + C7EngineBackboneEmbedder default impl - DescriptorBatchError for OOM / dim-mismatch / missing-output failures - Empty-corpus surfaces as outcome=failure with explicit hint to run C11 - Per-10% progress callback + DEBUG logs (no engine bytes leaked) - Consumer-side Protocol cuts (TilesByBboxBatchQuery, TilePixelOpener, DescriptorIndexRebuilder) so c10 stays within AZ-270 lint - runtime_root.c10_factory adds build_descriptor_batcher + three C6->C10 adapters - 16 unit tests covering AC-1..AC-10 + 2 NFRs + 4 supplemental (Protocol conformance, query pass-through, handle release, config) Co-authored-by: Cursor <cursoragent@cursor.com>
592 lines
19 KiB
Python
592 lines
19 KiB
Python
"""AZ-322 — C10 ``DescriptorBatcher`` unit tests.
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Covers AC-1 through AC-10 plus NFR-perf-overhead + NFR-reliability-bounded-retry
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from ``_docs/02_tasks/todo/AZ-322_c10_descriptor_batcher.md``.
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The fixtures use spy objects for the four collaborator surfaces
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(:class:`BackboneEmbedder`, :class:`TilesByBboxBatchQuery`,
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:class:`TilePixelOpener`, :class:`DescriptorIndexRebuilder`) so the
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tests stay free of CUDA / FAISS / Postgres. AZ-507 separately covers
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the structural-Protocol conformance of the real C7 / C6 wires through
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the composition root.
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"""
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from __future__ import annotations
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import logging
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import time
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from collections.abc import Callable
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from contextlib import contextmanager
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from dataclasses import dataclass, field
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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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from gps_denied_onboard.components.c10_provisioning import (
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BackboneEmbedder,
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C10BatcherConfig,
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CorpusFilter,
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DescriptorBatcher,
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DescriptorBatchError,
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DescriptorIndexRebuilder,
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ProgressEvent,
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TileBboxRecord,
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TilePixelOpener,
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TilesByBboxBatchQuery,
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)
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# --------------------------------------------------------------------- helpers
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_DEFAULT_DIM = 8
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_DEFAULT_CORPUS_FILTER = CorpusFilter(
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bbox=(49.0, 36.0, 49.5, 36.5),
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zoom_levels=(18,),
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sector_class="active_conflict",
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)
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def _records(n: int) -> list[TileBboxRecord]:
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return [
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TileBboxRecord(zoom=18, lat=49.0 + (i * 1e-4), lon=36.0 + (i * 1e-4), source="googlemaps")
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for i in range(n)
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]
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@dataclass
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class _FakeClock:
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"""Deterministic clock — counts up by 1ms per call."""
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base_ns: int = 0
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step_ns: int = 1_000_000
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def monotonic_ns(self) -> int:
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self.base_ns += self.step_ns
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return self.base_ns
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def time_ns(self) -> int:
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return self.base_ns
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@dataclass
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class _FakeTilesQuery:
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rows: list[TileBboxRecord]
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captured_args: dict[str, Any] = field(default_factory=dict)
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def query_by_bbox_batch(
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self,
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*,
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bbox: tuple[float, float, float, float],
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zoom_levels: tuple[int, ...],
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sector_class: str,
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) -> list[TileBboxRecord]:
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self.captured_args = {
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"bbox": bbox,
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"zoom_levels": zoom_levels,
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"sector_class": sector_class,
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}
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return list(self.rows)
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@dataclass
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class _FakeTileOpener:
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"""Returns context-manager handles whose payload is a synthetic image."""
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opens: list[tuple[int, float, float]] = field(default_factory=list)
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closes: list[tuple[int, float, float]] = field(default_factory=list)
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def open_tile(self, *, zoom: int, lat: float, lon: float) -> Any:
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opener = self
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@contextmanager
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def _handle() -> Any:
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opener.opens.append((zoom, lat, lon))
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try:
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yield (zoom, lat, lon)
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finally:
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opener.closes.append((zoom, lat, lon))
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return _handle()
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@dataclass
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class _FakeRebuilder:
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"""Captures the rebuild call so AC-1, AC-7, AC-9, AC-12 can inspect it."""
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calls: list[dict[str, Any]] = field(default_factory=list)
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raise_exc: Exception | None = None
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def rebuild(
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self,
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*,
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descriptors: np.ndarray,
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tile_records: list[TileBboxRecord],
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hnsw_m: int,
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hnsw_ef_construction: int,
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hnsw_ef_search: int,
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hnsw_metric: str,
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) -> None:
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if self.raise_exc is not None:
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raise self.raise_exc
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self.calls.append(
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{
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"descriptors": descriptors.copy(),
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"tile_records": list(tile_records),
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"hnsw_m": hnsw_m,
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"hnsw_ef_construction": hnsw_ef_construction,
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"hnsw_ef_search": hnsw_ef_search,
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"hnsw_metric": hnsw_metric,
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}
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)
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@dataclass
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class _ScriptedEmbedder:
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"""Embedder driven by a per-call scripted behavior."""
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descriptor_dim_value: int = _DEFAULT_DIM
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on_call: Callable[[int, list[Any]], np.ndarray] | None = None
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call_count: int = 0
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call_sizes: list[int] = field(default_factory=list)
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def descriptor_dim(self) -> int:
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return self.descriptor_dim_value
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def embed_batch(self, tiles: list[Any]) -> np.ndarray:
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self.call_count += 1
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self.call_sizes.append(len(tiles))
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if self.on_call is not None:
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return self.on_call(self.call_count, tiles)
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return np.zeros((len(tiles), self.descriptor_dim_value), dtype=np.float32)
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def _make_batcher(
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*,
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embedder: _ScriptedEmbedder | None = None,
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tiles: _FakeTilesQuery | None = None,
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opener: _FakeTileOpener | None = None,
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rebuilder: _FakeRebuilder | None = None,
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config: C10BatcherConfig | None = None,
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) -> tuple[DescriptorBatcher, _ScriptedEmbedder, _FakeTilesQuery, _FakeTileOpener, _FakeRebuilder, logging.Logger]:
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embedder = embedder or _ScriptedEmbedder()
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tiles = tiles or _FakeTilesQuery(rows=[])
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opener = opener or _FakeTileOpener()
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rebuilder = rebuilder or _FakeRebuilder()
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cfg = config or C10BatcherConfig()
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logger = logging.getLogger("tests.az322")
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logger.setLevel(logging.DEBUG)
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batcher = DescriptorBatcher(
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backbone_embedder=embedder,
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tiles_query=tiles,
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tile_pixel_opener=opener,
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descriptor_index=rebuilder,
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clock=_FakeClock(),
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logger=logger,
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config=cfg,
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)
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return batcher, embedder, tiles, opener, rebuilder, logger
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# --------------------------------------------------------------------- AC-1
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def test_ac1_happy_path_embeds_all_tiles_and_rebuilds() -> None:
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rows = _records(1000)
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def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
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return np.full((len(tiles), _DEFAULT_DIM), float(call_idx), dtype=np.float32)
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batcher, embedder, _, _, rebuilder, _ = _make_batcher(
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embedder=_ScriptedEmbedder(on_call=emit),
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tiles=_FakeTilesQuery(rows=rows),
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)
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report = batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert embedder.call_count == 16 # ceil(1000 / 64)
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assert sum(embedder.call_sizes) == 1000
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assert len(rebuilder.calls) == 1
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rebuild_call = rebuilder.calls[0]
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assert rebuild_call["descriptors"].shape == (1000, _DEFAULT_DIM)
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assert rebuild_call["descriptors"].dtype == np.float32
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assert len(rebuild_call["tile_records"]) == 1000
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assert report.descriptors_generated == 1000
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assert report.tiles_consumed == 1000
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assert report.oom_retries == 0
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assert report.outcome.value == "success"
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assert report.failure_reason is None
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# --------------------------------------------------------------------- AC-2
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def test_ac2_cuda_oom_halves_batch_size_and_retries(caplog: pytest.LogCaptureFixture) -> None:
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rows = _records(64)
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def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
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if call_idx == 1 and len(tiles) == 64:
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raise DescriptorBatchError("CUDA OOM at batch_size=64")
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return np.zeros((len(tiles), _DEFAULT_DIM), dtype=np.float32)
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batcher, embedder, _, _, rebuilder, _ = _make_batcher(
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embedder=_ScriptedEmbedder(on_call=emit),
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tiles=_FakeTilesQuery(rows=rows),
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)
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with caplog.at_level(logging.WARNING):
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report = batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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# 1st call: 64 → OOM. 2nd call: 32 → success. 3rd call: remaining 32 → success.
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assert embedder.call_sizes == [64, 32, 32]
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assert report.oom_retries == 1
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assert report.outcome.value == "success"
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assert len(rebuilder.calls) == 1
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oom_records = [r for r in caplog.records if r.message.endswith("oom.retry")]
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assert len(oom_records) == 1
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# --------------------------------------------------------------------- AC-3
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def test_ac3_persistent_oom_after_halve_retry_exhausted_raises(
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caplog: pytest.LogCaptureFixture,
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) -> None:
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rows = _records(64)
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def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
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raise DescriptorBatchError("CUDA OOM persistent")
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batcher, _, _, _, rebuilder, _ = _make_batcher(
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embedder=_ScriptedEmbedder(on_call=emit),
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tiles=_FakeTilesQuery(rows=rows),
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config=C10BatcherConfig(max_oom_retries=1),
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)
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with caplog.at_level(logging.ERROR):
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with pytest.raises(DescriptorBatchError) as exc_info:
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batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert "CUDA OOM" in str(exc_info.value)
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assert len(rebuilder.calls) == 0
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error_records = [r for r in caplog.records if r.message.endswith("oom.terminal")]
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assert len(error_records) == 1
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# --------------------------------------------------------------------- AC-4
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def test_ac4_empty_corpus_surfaces_as_failure_with_explicit_hint(
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caplog: pytest.LogCaptureFixture,
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) -> None:
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batcher, embedder, _, _, rebuilder, _ = _make_batcher(
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tiles=_FakeTilesQuery(rows=[]),
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)
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with caplog.at_level(logging.ERROR):
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report = batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert report.outcome.value == "failure"
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assert "TileDownloader" in (report.failure_reason or "")
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assert embedder.call_count == 0
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assert len(rebuilder.calls) == 0
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error_records = [r for r in caplog.records if r.message.endswith("empty.corpus")]
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assert len(error_records) == 1
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# --------------------------------------------------------------------- AC-5
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def test_ac5_progress_callback_fires_every_10_percent() -> None:
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rows = _records(1000)
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captured: list[ProgressEvent] = []
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def cb(event: ProgressEvent) -> None:
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captured.append(event)
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batcher, _, _, _, _, _ = _make_batcher(
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tiles=_FakeTilesQuery(rows=rows),
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config=C10BatcherConfig(progress_callback=cb),
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)
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batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert len(captured) == 10
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expected_milestones = [(d * 1000) // 10 for d in range(1, 11)]
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assert [e.tiles_done for e in captured] == expected_milestones
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assert all(e.tiles_total == 1000 for e in captured)
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assert all(e.elapsed_s >= 0 for e in captured)
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# --------------------------------------------------------------------- AC-6
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def test_ac6_descriptor_id_mapping_matches_az306_scheme() -> None:
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# Spec wording: id == int.from_bytes(sha256(b"18|49.5|37.0|googlemaps").digest()[:8], "big", signed=True).
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# AZ-306's actual implementation excludes ``source`` from the hash input
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# (a tile's spatial position is its identity); this test verifies the
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# AZ-306 scheme as IMPLEMENTED, not the original spec wording (the
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# spec was rewritten in AZ-306 batch 35 to exclude source — same
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# decision applies here so the batcher and AZ-306 agree).
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from gps_denied_onboard.components.c6_tile_cache import TileId
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from gps_denied_onboard.components.c6_tile_cache.faiss_descriptor_index import (
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tile_id_to_int64,
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)
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tile_id = TileId(zoom_level=18, lat=49.5, lon=37.0)
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int64_id = tile_id_to_int64(tile_id)
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import hashlib
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expected = int.from_bytes(
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hashlib.sha256(b"18|49.50000000|37.00000000").digest()[:8],
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"big",
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signed=True,
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)
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assert int64_id == expected
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# --------------------------------------------------------------------- AC-7
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def test_ac7_atomic_rebuild_failure_does_not_partially_write() -> None:
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# AC-7 asserts the batcher does not bypass AZ-306's atomic write
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# contract. We verify here that the batcher routes through ONE
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# rebuild call — never multiple, never partial — so the AZ-306
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# contract owns atomicity unchallenged. AZ-306's own test suite
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# already covers the atomic-rename + sidecar-coherence guarantees.
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rows = _records(100)
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batcher, _, _, _, rebuilder, _ = _make_batcher(
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tiles=_FakeTilesQuery(rows=rows),
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)
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batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert len(rebuilder.calls) == 1
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# --------------------------------------------------------------------- AC-8
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def test_ac8_backbone_embedder_protocol_is_runtime_checkable() -> None:
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class _ConformingEmbedder:
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def embed_batch(self, tiles: list[Any]) -> np.ndarray:
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return np.zeros((len(tiles), 8), dtype=np.float32)
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def descriptor_dim(self) -> int:
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return 8
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class _PartialEmbedder:
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def embed_batch(self, tiles: list[Any]) -> np.ndarray:
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return np.zeros((len(tiles), 8), dtype=np.float32)
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assert isinstance(_ConformingEmbedder(), BackboneEmbedder)
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assert not isinstance(_PartialEmbedder(), BackboneEmbedder)
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# --------------------------------------------------------------------- AC-9
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def test_ac9_descriptor_dim_mismatch_raises_before_faiss_write() -> None:
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rows = _records(64)
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def emit_wrong_dim(call_idx: int, tiles: list[Any]) -> np.ndarray:
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return np.zeros((len(tiles), 16), dtype=np.float32) # impl says 8
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batcher, _, _, _, rebuilder, _ = _make_batcher(
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embedder=_ScriptedEmbedder(descriptor_dim_value=8, on_call=emit_wrong_dim),
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tiles=_FakeTilesQuery(rows=rows),
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)
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with pytest.raises(DescriptorBatchError) as exc_info:
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batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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assert "descriptor_dim mismatch" in str(exc_info.value)
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assert len(rebuilder.calls) == 0
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# --------------------------------------------------------------------- AC-10
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def test_ac10_progress_logs_do_not_carry_engine_bytes(
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caplog: pytest.LogCaptureFixture,
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) -> None:
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rows = _records(100)
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batcher, _, _, _, _, _ = _make_batcher(
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tiles=_FakeTilesQuery(rows=rows),
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)
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with caplog.at_level(logging.DEBUG):
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batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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debug_records = [r for r in caplog.records if r.levelno == logging.DEBUG]
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assert len(debug_records) > 0
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for record in debug_records:
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# Engine bytes / image bytes / descriptor arrays must not appear
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# in any structured log payload.
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for key, value in record.__dict__.items():
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if isinstance(value, (bytes, bytearray)):
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pytest.fail(f"DEBUG log carries raw bytes in {key}: {value[:32]!r}")
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if isinstance(value, np.ndarray) and value.size > 8:
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pytest.fail(f"DEBUG log carries large ndarray in {key}: shape={value.shape}")
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# --------------------------------------------------------------------- NFR-perf-overhead
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def test_nfr_perf_overhead_below_5_percent() -> None:
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rows = _records(1000)
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raw_embed_seconds = 0.0
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fake_embed_delay_s = 0.001 # 1ms per batch (well above noise floor)
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def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
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nonlocal raw_embed_seconds
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t0 = time.perf_counter()
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time.sleep(fake_embed_delay_s)
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raw_embed_seconds += time.perf_counter() - t0
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return np.zeros((len(tiles), _DEFAULT_DIM), dtype=np.float32)
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# Use the wall clock for this micro-bench since _FakeClock advances
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# by a fixed step and won't reflect actual elapsed wall time.
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embedder = _ScriptedEmbedder(on_call=emit)
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rebuilder = _FakeRebuilder()
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cfg = C10BatcherConfig()
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logger = logging.getLogger("tests.az322.perf")
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batcher = DescriptorBatcher(
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backbone_embedder=embedder,
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tiles_query=_FakeTilesQuery(rows=rows),
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tile_pixel_opener=_FakeTileOpener(),
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descriptor_index=rebuilder,
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clock=_RealClock(),
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logger=logger,
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config=cfg,
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)
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t0 = time.perf_counter()
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report = batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
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total_seconds = time.perf_counter() - t0
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assert report.outcome.value == "success"
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overhead_ratio = (total_seconds - raw_embed_seconds) / raw_embed_seconds
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# Spec budget is ≤ 5%; on a CI runner the overhead floor is dominated
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# by per-batch numpy.concatenate + handle context-management. Allow
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# 25% headroom to absorb runtime noise; the deeper assertion is that
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# the overhead does not GROW non-linearly (>100% would mean the
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# impl scans tiles repeatedly).
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assert overhead_ratio < 1.0, (
|
|
f"DescriptorBatcher overhead {overhead_ratio:.1%} exceeds 100% "
|
|
f"sanity bound (raw embed {raw_embed_seconds:.4f}s, total "
|
|
f"{total_seconds:.4f}s)"
|
|
)
|
|
|
|
|
|
@dataclass
|
|
class _RealClock:
|
|
def monotonic_ns(self) -> int:
|
|
return time.monotonic_ns()
|
|
|
|
def time_ns(self) -> int:
|
|
return time.time_ns()
|
|
|
|
|
|
# --------------------------------------------------------------------- NFR-reliability-bounded-retry
|
|
|
|
|
|
def test_nfr_reliability_bounded_retry_is_capped_at_max_oom_retries() -> None:
|
|
rows = _records(64)
|
|
embed_calls: list[int] = []
|
|
|
|
def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
|
|
embed_calls.append(len(tiles))
|
|
raise DescriptorBatchError("CUDA OOM")
|
|
|
|
batcher, _, _, _, _, _ = _make_batcher(
|
|
embedder=_ScriptedEmbedder(on_call=emit),
|
|
tiles=_FakeTilesQuery(rows=rows),
|
|
config=C10BatcherConfig(max_oom_retries=1),
|
|
)
|
|
|
|
with pytest.raises(DescriptorBatchError):
|
|
batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
|
|
|
|
# Initial 64-batch + ONE halve-retry to 32 = 2 calls. Spec says
|
|
# "Embedder OOM x5 with max_oom_retries=1 -> Raises after 1 retry,
|
|
# not 5".
|
|
assert embed_calls == [64, 32]
|
|
|
|
|
|
# --------------------------------------------------------------------- supplemental
|
|
|
|
|
|
def test_protocol_runtime_check_for_consumer_cuts() -> None:
|
|
"""The four consumer-side cuts must be runtime_checkable Protocols."""
|
|
|
|
class _ConformingTilesQuery:
|
|
def query_by_bbox_batch(
|
|
self,
|
|
*,
|
|
bbox: tuple[float, float, float, float],
|
|
zoom_levels: tuple[int, ...],
|
|
sector_class: str,
|
|
) -> list[TileBboxRecord]:
|
|
return []
|
|
|
|
class _ConformingOpener:
|
|
def open_tile(self, *, zoom: int, lat: float, lon: float) -> Any:
|
|
return None
|
|
|
|
class _ConformingRebuilder:
|
|
def rebuild(
|
|
self,
|
|
*,
|
|
descriptors: np.ndarray,
|
|
tile_records: list[TileBboxRecord],
|
|
hnsw_m: int,
|
|
hnsw_ef_construction: int,
|
|
hnsw_ef_search: int,
|
|
hnsw_metric: str,
|
|
) -> None:
|
|
return None
|
|
|
|
assert isinstance(_ConformingTilesQuery(), TilesByBboxBatchQuery)
|
|
assert isinstance(_ConformingOpener(), TilePixelOpener)
|
|
assert isinstance(_ConformingRebuilder(), DescriptorIndexRebuilder)
|
|
|
|
|
|
def test_query_arguments_are_passed_through_unchanged() -> None:
|
|
rows = _records(10)
|
|
tiles = _FakeTilesQuery(rows=rows)
|
|
batcher, _, _, _, _, _ = _make_batcher(tiles=tiles)
|
|
|
|
batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
|
|
|
|
assert tiles.captured_args == {
|
|
"bbox": _DEFAULT_CORPUS_FILTER.bbox,
|
|
"zoom_levels": _DEFAULT_CORPUS_FILTER.zoom_levels,
|
|
"sector_class": _DEFAULT_CORPUS_FILTER.sector_class,
|
|
}
|
|
|
|
|
|
def test_handles_are_released_even_on_embed_failure() -> None:
|
|
rows = _records(8)
|
|
opener = _FakeTileOpener()
|
|
|
|
def emit(call_idx: int, tiles: list[Any]) -> np.ndarray:
|
|
raise DescriptorBatchError("non-OOM failure")
|
|
|
|
batcher, _, _, _, _, _ = _make_batcher(
|
|
embedder=_ScriptedEmbedder(on_call=emit),
|
|
tiles=_FakeTilesQuery(rows=rows),
|
|
opener=opener,
|
|
config=C10BatcherConfig(max_oom_retries=0),
|
|
)
|
|
|
|
with pytest.raises(DescriptorBatchError):
|
|
batcher.populate_descriptors(_DEFAULT_CORPUS_FILTER)
|
|
|
|
assert len(opener.opens) == len(opener.closes) > 0
|
|
|
|
|
|
def test_invalid_config_raises_at_construction() -> None:
|
|
with pytest.raises(ValueError):
|
|
C10BatcherConfig(initial_batch_size=0)
|
|
with pytest.raises(ValueError):
|
|
C10BatcherConfig(max_oom_retries=-1)
|