tvalentyn commented on code in PR #31052:
URL: https://github.com/apache/beam/pull/31052#discussion_r1576791498
##########
sdks/python/apache_beam/ml/inference/base.py:
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@@ -1434,19 +1519,27 @@ def load():
if isinstance(side_input_model_path, str) and side_input_model_path != '':
model_tag = side_input_model_path
if self._model_handler.share_model_across_processes():
- model = multi_process_shared.MultiProcessShared(
- load, tag=model_tag, always_proxy=True).acquire()
+ models = []
+ for i in range(self._model_handler.model_copies()):
+ models.append(
+ multi_process_shared.MultiProcessShared(
Review Comment:
> will side input update iteration result in creating a new multiprocess
shared handle without releasing the previous one
As far as I can tell, we will recreate new handles, since we will call
_RunInferenceDoFn.update_model() from
https://github.com/apache/beam/blob/58bea3f19e5220c08a900a3005e80473561dabaf/sdks/python/apache_beam/ml/inference/base.py#L1525
and then we will create a new ModelWrapper with a new SharedHandle(s) in:
https://github.com/apache/beam/blob/58bea3f19e5220c08a900a3005e80473561dabaf/sdks/python/apache_beam/ml/inference/base.py#L1474
Sounds like this would be a concern without either reusing handles or
releasing them?
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