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The interpreter object from TensorFlow Lite holds the loaded model in memory.
Models can be large and the interpreter uses native resources like C++ memory, not just the JVM.
If you don't close it, you may leak memory.
So for that, we're going to use the function close here.
And inside it we're gonna close the interpreter.
So interpreter dot close and interpreter equals to null.
After closing the interpreter you set the variable to null.
This does two things.
Here.
We are preventing the accidental reuse of a closed interpreter and helps garbage collection.
The object reference is cleared so it can be freed.
We need to close the interpreter to free up resources.
Interpreter is not garbage collected, so it needs to be closed explicitly and preventing accidental
reuse of closed interpreter and helping garbage collection.
By freeing up resources, we assigned the interpreter to null.
Okay, so this is the function how we free up memory.
And this close function is a clean up method.
It shuts down the TensorFlow Lite interpreter safely.
It releases system memory.
It ensures the variable won't point to a dead object.