try using caching to speed up pipeline loads
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@ -1,5 +1,5 @@
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import os
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from functools import partial
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from functools import partial, lru_cache
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from itertools import chain, tee
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from typing import Iterable
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@ -20,6 +20,7 @@ from image_prediction.utils.generic import lift, starlift
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
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@lru_cache()
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def load_pipeline(**kwargs):
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model_loader = get_mlflow_model_loader(MLRUNS_DIR)
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model_identifier = CONFIG.service.mlflow_run_id
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