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Merge branch 'main' into rknn-toolkit-lite2

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This commit is contained in:
Yoni Yang
2025-01-18 16:45:38 +08:00
committed by GitHub
parent 9926045d5e f40fdce658
commit 4e42fbc091
141 changed files with 4341 additions and 2242 deletions
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4
machine-learning/Dockerfile
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@@ -1,6 +1,6 @@
ARG DEVICE=cpu
FROM python:3.11-bookworm@sha256:b337e1fd27dbacda505219f713789bf82766694095876769ea10c2d34b4f470b AS builder-cpu
FROM python:3.11-bookworm@sha256:f997d3f71b7dcff3f937703c02861437f2b41a94e1ddbd1b5fa357ee99f5cce4 AS builder-cpu
FROM builder-cpu AS builder-openvino
@@ -36,7 +36,7 @@ RUN python3 -m venv /opt/venv
COPY poetry.lock pyproject.toml ./
RUN poetry install --sync --no-interaction --no-ansi --no-root --with ${DEVICE} --without dev
FROM python:3.11-slim-bookworm@sha256:873952659a04188d2a62d5f7e30fd673d2559432a847a8ad5fcaf9cbd085e9ed AS prod-cpu
FROM python:3.11-slim-bookworm@sha256:6ed5bff4d7d377e2a27d9285553b8c21cfccc4f00881de1b24c9bc8d90016e82 AS prod-cpu
FROM prod-cpu AS prod-openvino

24
machine-learning/app/config.py
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@@ -14,9 +14,29 @@ from uvicorn import Server
from uvicorn.workers import UvicornWorker
class ClipSettings(BaseModel):
textual: str | None = None
visual: str | None = None
class FacialRecognitionSettings(BaseModel):
recognition: str | None = None
detection: str | None = None
class PreloadModelData(BaseModel):
clip: str | None = None
facial_recognition: str | None = None
clip_fallback: str | None = os.getenv("MACHINE_LEARNING_PRELOAD__CLIP", None)
facial_recognition_fallback: str | None = os.getenv("MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION", None)
if clip_fallback is not None:
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL"] = clip_fallback
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__VISUAL"] = clip_fallback
del os.environ["MACHINE_LEARNING_PRELOAD__CLIP"]
if facial_recognition_fallback is not None:
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION"] = facial_recognition_fallback
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION"] = facial_recognition_fallback
del os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION"]
clip: ClipSettings = ClipSettings()
facial_recognition: FacialRecognitionSettings = FacialRecognitionSettings()
class MaxBatchSize(BaseModel):

39
machine-learning/app/main.py
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@@ -75,21 +75,46 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
async def preload_models(preload: PreloadModelData) -> None:
log.info(f"Preloading models: {preload}")
if preload.clip is not None:
model = await model_cache.get(preload.clip, ModelType.TEXTUAL, ModelTask.SEARCH)
log.info(f"Preloading models: clip:{preload.clip} facial_recognition:{preload.facial_recognition}")
if preload.clip.textual is not None:
model = await model_cache.get(preload.clip.textual, ModelType.TEXTUAL, ModelTask.SEARCH)
await load(model)
model = await model_cache.get(preload.clip, ModelType.VISUAL, ModelTask.SEARCH)
if preload.clip.visual is not None:
model = await model_cache.get(preload.clip.visual, ModelType.VISUAL, ModelTask.SEARCH)
await load(model)
if preload.facial_recognition is not None:
model = await model_cache.get(preload.facial_recognition, ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION)
if preload.facial_recognition.detection is not None:
model = await model_cache.get(
preload.facial_recognition.detection,
ModelType.DETECTION,
ModelTask.FACIAL_RECOGNITION,
)
await load(model)
model = await model_cache.get(preload.facial_recognition, ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION)
if preload.facial_recognition.recognition is not None:
model = await model_cache.get(
preload.facial_recognition.recognition,
ModelType.RECOGNITION,
ModelTask.FACIAL_RECOGNITION,
)
await load(model)
if preload.clip_fallback is not None:
log.warning(
"Deprecated env variable: 'MACHINE_LEARNING_PRELOAD__CLIP'. "
"Use 'MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL' and "
"'MACHINE_LEARNING_PRELOAD__CLIP__VISUAL' instead."
)
if preload.facial_recognition_fallback is not None:
log.warning(
"Deprecated env variable: 'MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION'. "
"Use 'MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION' and "
"'MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION' instead."
)
def update_state() -> Iterator[None]:
global active_requests, last_called

24
machine-learning/app/test_main.py
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@@ -750,11 +750,13 @@ class TestCache:
await model_cache.get("test_model_name", ModelType.TEXTUAL, ModelTask.SEARCH)
async def test_preloads_clip_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
os.environ["MACHINE_LEARNING_PRELOAD__CLIP"] = "ViT-B-32__openai"
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL"] = "ViT-B-32__openai"
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__VISUAL"] = "ViT-B-32__openai"
settings = Settings()
assert settings.preload is not None
assert settings.preload.clip == "ViT-B-32__openai"
assert settings.preload.clip.textual == "ViT-B-32__openai"
assert settings.preload.clip.visual == "ViT-B-32__openai"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)
@@ -771,11 +773,13 @@ class TestCache:
async def test_preloads_facial_recognition_models(
self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock
) -> None:
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION"] = "buffalo_s"
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION"] = "buffalo_s"
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION"] = "buffalo_s"
settings = Settings()
assert settings.preload is not None
assert settings.preload.facial_recognition == "buffalo_s"
assert settings.preload.facial_recognition.detection == "buffalo_s"
assert settings.preload.facial_recognition.recognition == "buffalo_s"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)
@@ -790,13 +794,17 @@ class TestCache:
)
async def test_preloads_all_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
os.environ["MACHINE_LEARNING_PRELOAD__CLIP"] = "ViT-B-32__openai"
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION"] = "buffalo_s"
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__TEXTUAL"] = "ViT-B-32__openai"
os.environ["MACHINE_LEARNING_PRELOAD__CLIP__VISUAL"] = "ViT-B-32__openai"
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__RECOGNITION"] = "buffalo_s"
os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION__DETECTION"] = "buffalo_s"
settings = Settings()
assert settings.preload is not None
assert settings.preload.clip == "ViT-B-32__openai"
assert settings.preload.facial_recognition == "buffalo_s"
assert settings.preload.clip.visual == "ViT-B-32__openai"
assert settings.preload.clip.textual == "ViT-B-32__openai"
assert settings.preload.facial_recognition.recognition == "buffalo_s"
assert settings.preload.facial_recognition.detection == "buffalo_s"
model_cache = ModelCache()
monkeypatch.setattr("app.main.model_cache", model_cache)

6
machine-learning/poetry.lock generated
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@@ -2498,13 +2498,13 @@ files = [
[[package]]
name = "pydantic"
version = "2.10.4"
version = "2.10.5"
description = "Data validation using Python type hints"
optional = false
python-versions = ">=3.8"
files = [
{file = "pydantic-2.10.4-py3-none-any.whl", hash = "sha256:597e135ea68be3a37552fb524bc7d0d66dcf93d395acd93a00682f1efcb8ee3d"},
{file = "pydantic-2.10.4.tar.gz", hash = "sha256:82f12e9723da6de4fe2ba888b5971157b3be7ad914267dea8f05f82b28254f06"},
{file = "pydantic-2.10.5-py3-none-any.whl", hash = "sha256:4dd4e322dbe55472cb7ca7e73f4b63574eecccf2835ffa2af9021ce113c83c53"},
{file = "pydantic-2.10.5.tar.gz", hash = "sha256:278b38dbbaec562011d659ee05f63346951b3a248a6f3642e1bc68894ea2b4ff"},
]
[package.dependencies]