tvalentyn commented on code in PR #31052:
URL: https://github.com/apache/beam/pull/31052#discussion_r1576760164
##########
sdks/python/apache_beam/ml/inference/base.py:
##########
@@ -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:
do we need to explicitly release the multi-process shared handle for it to
be freed-up? Guessing we currently don't do that as per TODO on line 1516?
If we are using the model update functonality via side input , are we
reusing the same mutliprocess shared handle during the update , or will side
input update result in allocating more memory
##########
sdks/python/apache_beam/ml/inference/base.py:
##########
@@ -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:
do we need to explicitly release the multi-process shared handle for it to
be freed-up? Guessing we currently don't do that as per TODO on line 1516?
If we are using the model update functonality via side input , are we
reusing the same mutliprocess shared handle during the update , or will side
input update iteratation result in allocating more memory
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