9e336ecc01
- Update pyinfra with absolute file path support (still supports dossierID fileID format) - Update CI, use new template
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
from image_prediction import logger
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from image_prediction.config import Config
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from image_prediction.locations import CONFIG_FILE
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from image_prediction.pipeline import load_pipeline
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from image_prediction.utils.banner import load_banner
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from image_prediction.utils.process_wrapping import wrap_in_process
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from pyinfra import config
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from pyinfra.payload_processing.processor import make_payload_processor
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from pyinfra.queue.queue_manager import QueueManager
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PYINFRA_CONFIG = config.get_config()
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IMAGE_CONFIG = Config(CONFIG_FILE)
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logger.setLevel(PYINFRA_CONFIG.logging_level_root)
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# A component of the processing pipeline (probably tensorflow) does not release allocated memory (see RED-4206).
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# See: https://stackoverflow.com/questions/39758094/clearing-tensorflow-gpu-memory-after-model-execution
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# Workaround: Manage Memory with the operating system, by wrapping the processing in a sub-process.
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# FIXME: Find more fine-grained solution or if the problem occurs persistently for python services,
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@wrap_in_process
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def process_data(data: bytes) -> list:
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pipeline = load_pipeline(verbose=IMAGE_CONFIG.service.verbose, batch_size=IMAGE_CONFIG.service.batch_size)
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return list(pipeline(data))
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def main():
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logger.info(load_banner())
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process_payload = make_payload_processor(process_data, config=PYINFRA_CONFIG)
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queue_manager = QueueManager(PYINFRA_CONFIG)
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queue_manager.start_consuming(process_payload)
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if __name__ == "__main__":
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main()
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