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Code Issues Releases Activity

chore(ml): set higher worker timeout for openvino (#11174)

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Mert 2024-07-18 10:50:57 -04:00 committed by GitHub
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3 changed files with 16 additions and 14 deletions
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24
docs/docs/install/environment-variables.md
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@ -155,18 +155,18 @@ Redis (Sentinel) URL example JSON before encoding:
## Machine Learning
| Variable | Description | Default | Containers |
| :----------------------------------------------- | :------------------------------------------------------------------- | :-----------------: | :--------------- |
| `MACHINE_LEARNING_MODEL_TTL` | Inactivity time (s) before a model is unloaded (disabled if \<= 0) | `300` | machine learning |
| `MACHINE_LEARNING_MODEL_TTL_POLL_S` | Interval (s) between checks for the model TTL (disabled if \<= 0) | `10` | machine learning |
| `MACHINE_LEARNING_CACHE_FOLDER` | Directory where models are downloaded | `/cache` | machine learning |
| `MACHINE_LEARNING_REQUEST_THREADS`<sup>\*1</sup> | Thread count of the request thread pool (disabled if \<= 0) | number of CPU cores | machine learning |
| `MACHINE_LEARNING_MODEL_INTER_OP_THREADS` | Number of parallel model operations | `1` | machine learning |
| `MACHINE_LEARNING_MODEL_INTRA_OP_THREADS` | Number of threads for each model operation | `2` | machine learning |
| `MACHINE_LEARNING_WORKERS`<sup>\*2</sup> | Number of worker processes to spawn | `1` | machine learning |
| `MACHINE_LEARNING_WORKER_TIMEOUT` | Maximum time (s) of unresponsiveness before a worker is killed | `120` | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP` | Name of a CLIP model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION` | Name of a facial recognition model to be preloaded and kept in cache | | machine learning |
| Variable | Description | Default | Containers |
| :----------------------------------------------- | :------------------------------------------------------------------- | :-----------------------------------: | :--------------- |
| `MACHINE_LEARNING_MODEL_TTL` | Inactivity time (s) before a model is unloaded (disabled if \<= 0) | `300` | machine learning |
| `MACHINE_LEARNING_MODEL_TTL_POLL_S` | Interval (s) between checks for the model TTL (disabled if \<= 0) | `10` | machine learning |
| `MACHINE_LEARNING_CACHE_FOLDER` | Directory where models are downloaded | `/cache` | machine learning |
| `MACHINE_LEARNING_REQUEST_THREADS`<sup>\*1</sup> | Thread count of the request thread pool (disabled if \<= 0) | number of CPU cores | machine learning |
| `MACHINE_LEARNING_MODEL_INTER_OP_THREADS` | Number of parallel model operations | `1` | machine learning |
| `MACHINE_LEARNING_MODEL_INTRA_OP_THREADS` | Number of threads for each model operation | `2` | machine learning |
| `MACHINE_LEARNING_WORKERS`<sup>\*2</sup> | Number of worker processes to spawn | `1` | machine learning |
| `MACHINE_LEARNING_WORKER_TIMEOUT` | Maximum time (s) of unresponsiveness before a worker is killed | `120` (`300` if using OpenVINO image) | machine learning |
| `MACHINE_LEARNING_PRELOAD__CLIP` | Name of a CLIP model to be preloaded and kept in cache | | machine learning |
| `MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION` | Name of a facial recognition model to be preloaded and kept in cache | | machine learning |
\*1: It is recommended to begin with this parameter when changing the concurrency levels of the machine learning service and then tune the other ones.

1
machine-learning/Dockerfile
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@ -77,6 +77,7 @@ RUN apt-get update && \
rm -rf /var/lib/apt/lists/*
WORKDIR /usr/src/app
ARG DEVICE
ENV TRANSFORMERS_CACHE=/cache \
PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \

5
machine-learning/start.sh
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@ -5,12 +5,13 @@ lib_path="/usr/lib/$(arch)-linux-gnu/libmimalloc.so.2"
if ! [ "$DEVICE" = "openvino" ]; then
export LD_PRELOAD="$lib_path"
export LD_BIND_NOW=1
: "${MACHINE_LEARNING_WORKER_TIMEOUT:=120}"
else
: "${MACHINE_LEARNING_WORKER_TIMEOUT:=300}"
fi
: "${IMMICH_HOST:=[::]}"
: "${IMMICH_PORT:=3003}"
: "${MACHINE_LEARNING_WORKERS:=1}"
: "${MACHINE_LEARNING_WORKER_TIMEOUT:=120}"
gunicorn app.main:app \
-k app.config.CustomUvicornWorker \