The community member reported an issue where assigning a large NumPy array to a cell-scoped variable results in the memory remaining occupied even after the cell has finished running. Renaming the variable and rerunning the cell leads to the old memory still being occupied and a new, large chunk of memory being allocated. The community members acknowledged this as a bug and requested the original poster to report it on GitHub so they can investigate further.
See the attached code. If I assign a large numpy array to a cell-scoped variable, then after the cell is done running the memory is still occupied (about 7.5 GB). If I rename the cell-scoped variable and rerun, then the old memory still remains occupied and a new, large chunk of memory is allocated (so now taking about 15 GB).
Can you do me a favor and post this on GitHub so we can track it? You can paste the exact same text / images, no need to fill out the bug report template.
