riteshghorse commented on code in PR #28263:
URL: https://github.com/apache/beam/pull/28263#discussion_r1311970930
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sdks/python/apache_beam/ml/inference/base.py:
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@@ -308,17 +308,13 @@ class _ModelManager:
parameter, if that is set it will only hold that many models in memory at
once before evicting one (using LRU logic).
Review Comment:
remove doc statement for `max_models`
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sdks/python/apache_beam/ml/inference/base.py:
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@@ -587,6 +588,14 @@ def run_inference(
keys,
self._unkeyed.run_inference(unkeyed_batch, model, inference_args))
+ # The first time a MultiProcessShared ModelManager is used for inference
+ # from this process, we should increment its max model count
+ if self._max_models_per_worker_hint is not None:
+ lock = threading.Lock()
+ if lock.acquire(blocking=False):
Review Comment:
curious why are we not using a blocking lock?
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