Massive memory Leak about connected-components-3d

[william-silversmith]

Hi modaresimr,

Can you show me the code that produces the memory leak? What OS, Python version, cc3d version are you running?

Thanks for reporting,
Will

[modaresimr]

I am using around 1000 time 3d arrays of 512x512x689 int

After 3 use of cc3d, the memory will be increased to 20 GB!!!!!!
It won't release memory!
After a deep debugging by changing that to the code that I mentioned it is fixed.

I will try to take out a part of my code to share soon

[william-silversmith]

That would be very helpful (along with details such as OS, Python version, and cc3d version). cc3d should be using < 2.2 GB assuming one image in memory.

One thing you can try and see if it helps: cast your array to an unsigned integer type. It shouldn't make a difference, but cc3d was manually tested mainly on unsigned arrays (though integer arrays are included in automated testing).

[modaresimr]

Thank you for your support,
I found out that this problem is due to an issue in python memory management when you create a lot of big arrays, and then remove them, the memory will be fragmented, and it can not allocate new arrays.
However, if we create a new process, and run it in a separate process, we will not face any issues.

More info on this issue on: https://stackoverflow.com/a/9617718/834117

[william-silversmith]

Thanks for looking into this more! If there's a way for you to reuse the arrays (e.g. if they're all the same size) that might help a lot. I'm going to close this issue as it's not directly related to cc3d but is a general python issue. Please reopen if you think you need more help!

[modaresimr]

Thanks for looking into this more! If there's a way for you to reuse the arrays (e.g. if they're all the same size) that might help a lot. I'm going to close this issue as it's not directly related to cc3d but is a general python issue. Please reopen if you think you need more help!

Thanks for your suggestion, however, numpy with all the operations create a new array and we can not reuse them :(

[william-silversmith]

numpy with all the operations create a new array and we can not reuse them :(

It depends on which operations you're doing. For example the += operator will avoid creating a copy. You can also check the documentation for several numpy operators which include an out= parameter. For example, np.multiply(a,b, out=a).