This podcast episode delves into weak references, their implementation, and consequences in PyTorch and C++. It explores use cases and implementation details of weak references, discussing their role in caching and how they allow objects to be garbage collected even with remaining references. The episode compares C++'s reference counting and Python's weak reference list implementations, highlighting their consequences and the need for careful optimization to ensure efficient memory management.
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