Pull request #46: RED-6205 add prometheus monitoring
Merge in RR/image-prediction from RED-6205-add-prometheus-monitoring to master
Squashed commit of the following:
commit 6932b5ee579a31d0317dc3f76acb8dd2845fdb4b
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Mar 16 17:30:57 2023 +0100
update pyinfra
commit d6e55534623eae2edcddaa6dd333f93171d421dc
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Mar 16 16:30:14 2023 +0100
set pyinfra subproject to current master commit
commit 030dc660e6060ae326c32fba8c2944a10866fbb6
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Mar 16 16:25:19 2023 +0100
adapt serve script to advanced pyinfra API including monitoring of the processing time of images.
commit 0fa0c44c376c52653e517d257a35793797f7be31
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Mar 16 15:19:57 2023 +0100
Update dockerfile to work with new pyinfra package setup utilizing pyproject.toml instad of setup.py and requirments.txt
commit aad53c4d313f908de93a13e69e2cb150db3be6cb
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Mar 16 14:16:04 2023 +0100
remove no longer needed dependencies
This commit is contained in:
Julius Unverfehrt
parent
ed25af33ad
commit
81520b1a53
3
.gitmodules
vendored
3
.gitmodules
vendored
@ -1,6 +1,3 @@
|
||||
[submodule "incl/pyinfra"]
|
||||
path = incl/pyinfra
|
||||
url = ssh://git@git.iqser.com:2222/rr/pyinfra.git
|
||||
[submodule "incl/pdf2image"]
|
||||
path = incl/pdf2image
|
||||
url = ssh://git@git.iqser.com:2222/rr/pdf2image.git
|
||||
|
||||
@ -4,7 +4,6 @@ WORKDIR /app/service
|
||||
|
||||
COPY src src
|
||||
COPY incl/pyinfra incl/pyinfra
|
||||
COPY incl/pdf2image incl/pdf2image
|
||||
COPY data data
|
||||
COPY image_prediction image_prediction
|
||||
COPY setup.py setup.py
|
||||
@ -14,12 +13,9 @@ COPY banner.txt banner.txt
|
||||
|
||||
# Install dependencies differing from base image.
|
||||
RUN python3 -m pip install -r requirements.txt
|
||||
RUN python3 -m pip install -r incl/pyinfra/requirements.txt
|
||||
RUN python3 -m pip install -r incl/pdf2image/requirements.txt
|
||||
|
||||
RUN python3 -m pip install -e .
|
||||
RUN python3 -m pip install -e incl/pyinfra
|
||||
RUN python3 -m pip install -e incl/pdf2image
|
||||
RUN python3 -m pip install incl/pyinfra
|
||||
|
||||
EXPOSE 5000
|
||||
EXPOSE 8080
|
||||
|
||||
@ -7,7 +7,6 @@ WORKDIR /app/service
|
||||
|
||||
COPY src src
|
||||
COPY incl/pyinfra incl/pyinfra
|
||||
COPY incl/pdf2image incl/pdf2image
|
||||
COPY data data
|
||||
COPY image_prediction image_prediction
|
||||
COPY setup.py setup.py
|
||||
@ -17,12 +16,9 @@ COPY banner.txt banner.txt
|
||||
|
||||
# Install module & dependencies
|
||||
RUN python3 -m pip install -r requirements.txt
|
||||
RUN python3 -m pip install -r incl/pyinfra/requirements.txt
|
||||
RUN python3 -m pip install -r incl/pdf2image/requirements.txt
|
||||
|
||||
RUN python3 -m pip install -e .
|
||||
RUN python3 -m pip install -e incl/pyinfra
|
||||
RUN python3 -m pip install -e incl/pdf2image
|
||||
RUN python3 -m pip install incl/pyinfra
|
||||
|
||||
RUN apt update --yes
|
||||
RUN apt install vim --yes
|
||||
|
||||
@ -1 +0,0 @@
|
||||
Subproject commit f7292c30ad7c7ae5f07cee6925adda096301b60a
|
||||
@ -1 +1 @@
|
||||
Subproject commit 46157031b588b4bda03f8ddbb9c2e2fadbb47af5
|
||||
Subproject commit ff6f437e8491d48c1e0ccb08ad7b164477e15fbe
|
||||
47
src/serve.py
47
src/serve.py
@ -1,7 +1,3 @@
|
||||
import gzip
|
||||
import json
|
||||
import logging
|
||||
|
||||
from image_prediction import logger
|
||||
from image_prediction.config import Config
|
||||
from image_prediction.locations import CONFIG_FILE
|
||||
@ -9,8 +5,8 @@ from image_prediction.pipeline import load_pipeline
|
||||
from image_prediction.utils.banner import load_banner
|
||||
from image_prediction.utils.process_wrapping import wrap_in_process
|
||||
from pyinfra import config
|
||||
from pyinfra.payload_processing import make_payload_processor
|
||||
from pyinfra.queue.queue_manager import QueueManager
|
||||
from pyinfra.storage.storage import get_storage
|
||||
|
||||
PYINFRA_CONFIG = config.get_config()
|
||||
IMAGE_CONFIG = Config(CONFIG_FILE)
|
||||
@ -18,50 +14,23 @@ IMAGE_CONFIG = Config(CONFIG_FILE)
|
||||
logger.setLevel(PYINFRA_CONFIG.logging_level_root)
|
||||
|
||||
|
||||
# A component of the callback (probably tensorflow) does not release allocated memory (see RED-4206).
|
||||
# A component of the processing pipeline (probably tensorflow) does not release allocated memory (see RED-4206).
|
||||
# See: https://stackoverflow.com/questions/39758094/clearing-tensorflow-gpu-memory-after-model-execution
|
||||
# Workaround: Manage Memory with the operating system, by wrapping the callback in a sub-process.
|
||||
# Workaround: Manage Memory with the operating system, by wrapping the processing in a sub-process.
|
||||
# FIXME: Find more fine-grained solution or if the problem occurs persistently for python services,
|
||||
# FIXME: move the process wrapper to a general module (see RED-4929).
|
||||
@wrap_in_process
|
||||
def process_request(request_message):
|
||||
dossier_id = request_message["dossierId"]
|
||||
file_id = request_message["fileId"]
|
||||
target_file_name = f"{dossier_id}/{file_id}.{request_message['targetFileExtension']}"
|
||||
response_file_name = f"{dossier_id}/{file_id}.{request_message['responseFileExtension']}"
|
||||
logger.info("Processing file %s w/ file_id=%s and dossier_id=%s", target_file_name, file_id, dossier_id)
|
||||
|
||||
bucket = PYINFRA_CONFIG.storage_bucket
|
||||
storage = get_storage(PYINFRA_CONFIG)
|
||||
|
||||
logger.debug("loading model pipeline")
|
||||
def process_data(data: bytes) -> list:
|
||||
pipeline = load_pipeline(verbose=IMAGE_CONFIG.service.verbose, batch_size=IMAGE_CONFIG.service.batch_size)
|
||||
|
||||
if storage.exists(bucket, target_file_name):
|
||||
logger.info("fetching file for file_id=%s and dossier_id=%s", file_id, dossier_id)
|
||||
object_bytes = storage.get_object(bucket, target_file_name)
|
||||
object_bytes = gzip.decompress(object_bytes)
|
||||
|
||||
classifications = list(pipeline(pdf=object_bytes))
|
||||
logger.info("predictions ready for file_id=%s and dossier_id=%s", file_id, dossier_id)
|
||||
|
||||
result = {**request_message, "data": classifications}
|
||||
storage_bytes = gzip.compress(json.dumps(result).encode("utf-8"))
|
||||
|
||||
logger.info("storing predictions for file_id=%s and dossier_id=%s", file_id, dossier_id)
|
||||
storage.put_object(bucket, response_file_name, storage_bytes)
|
||||
|
||||
return {"dossierId": dossier_id, "fileId": file_id}
|
||||
else:
|
||||
logger.info("no files found for file_id=%s and dossier_id=%s", file_id, dossier_id)
|
||||
return None
|
||||
return list(pipeline(data))
|
||||
|
||||
|
||||
def main():
|
||||
logger.info(load_banner())
|
||||
|
||||
process_payload = make_payload_processor(process_data, config=PYINFRA_CONFIG)
|
||||
|
||||
queue_manager = QueueManager(PYINFRA_CONFIG)
|
||||
queue_manager.start_consuming(process_request)
|
||||
queue_manager.start_consuming(process_payload)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user