fix(utility): add lock for cached file between processes #1151
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linjiX
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Dec 6, 2021
tensorbay/utility/common.py
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| def wrapper(self: Any, *arg: Any, **kwargs: Any) -> None: | ||
| key = getattr(self, attr_name) if attr_name else id(self) | ||
| # https://github.com/PyCQA/pylint/issues/3313 | ||
| lock = process_locks.setdefault(key, manager.Lock()) # pylint: disable=no-member |
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get item from a Manager.dict() seems a copy behavior, which means the gotten lock is a copy of the lock in the dict. That means the operation in the outside lock will not affect the inside lock?
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Shared objects are capable of being nested. The manager.Lock() is also a shared object, thus the change will be synced to the dict.
https://docs.python.org/3.8/library/multiprocessing.html#multiprocessing.managers.SyncManager
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tensorbay/utility/common.py
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| def wrapper(func_self: Any, *arg: Any, **kwargs: Any) -> None: | ||
| key = getattr(func_self, self._attr_name) | ||
| lock_exists = False | ||
| if key in self.process_locks: |
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will it possible that two processes go into this if statement at the same time, and two processes both return false, which makes them both create their own locks?
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Dec 14, 2021
tensorbay/utility/common.py
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| # https://github.com/PyCQA/pylint/issues/3313 | ||
| self.process_locks[key] = self._manager.Lock() # pylint: disable=no-member | ||
| with _acquire(self.process_locks[key]) as success: | ||
| self._lock.release() |
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if there are something wrong happens before releasing the self._lock, will it cause self._lock never release?
linjiX
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Dec 14, 2021
| self._lock.release() | ||
| if success and not lock_exists: | ||
| func(func_self, *arg, **kwargs) | ||
| del self.process_locks[key] |
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It that possible one process is deleting the lock from self.process_locks, and at the same time another process is checking whether the key in the self.process_locks?
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linjiX
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Dec 28, 2021
When using PyTorch dataloader with multiple workers, the cache file will be accessed by different processes. And the cache file can be written and read at the same time, which would lead to the read content being empty. Thus, use a temp filename while writing the cache file and then change it to the cache path. And add a lock to avoid repeatedly writing cache. PR Closed: Graviti-AI#1151
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When using PyTorch dataloader with multiple workers, the cache file will
be accessed by different processes. And the cache file can be written
and read at the same time, which would lead to the read content being
empty.
Thus, use a temp filename while writing the cache file and then change
it to the cache path. And add a lock to avoid repeatedly writing cache.