[Bug]: `PoseEstimationSeries` creation is significantly increasing sleap-io test runtimes

[keyaloding]

What happened?

Since the pynwb update from version 2.7.0 to 2.8.0, sleap-io tests have been experiencing significantly longer runtimes, which prevent our GitHub workflows from completing. For example, on Windows (Python 3.12), three of our tests that create new .nwb files take ~23s with pynwb==2.7.0 and ~159s with pynwb==2.8.1, as shown in these two runs: 2.7.0, 2.8.1.

After profiling and debugging runs, we found that the slowdown occurs when we create new PoseEstimationSeries objects using a kwargs dictionary on lines 460-461 of sleap-io/sleap_io/io/nwb.py. I have reproduced the issue and printed profiling results in the following colab notebooks.

pynwb==2.7.0 pynwb==2.8.1

Steps to Reproduce

See colab notebooks above

Traceback

No response

Operating System

Windows

Python Executable

Conda

Python Version

3.11

Package Versions

No response

Code of Conduct

• [X] I agree to follow this project's Code of Conduct
• [X] Have you checked the Contributing document?
• [X] Have you ensured this bug was not already reported?

[rly]

Thanks for the bug report @keyaloding . I am not sure why that is happening. I will run some tests on my end and get back to you next week.

[sneakers-the-rat]

seems primarily related to docval being very inefficient. sorting by cumulative time, it seems like the main difference is that hdmf.utils.func_call (specifically the is_method branch on line 666) is called 704 times in both, but has 768072 recursive calls in 2.7 and 3569184 recursive calls in 2.8.1 (both run with hdmf==3.14.4). all the other profiling info is the same, just scaled by ~5.

that's not all that helpful since docval makes it look like every call is func_call, but if you look for the other things that have their call numbers scaled by that much it might help - eg. manager.register_container_type is also called ~5x more, but it took me awhile puzzing at the comparison to see what i think is going on.

this change: https://github.com/NeurodataWithoutBorders/pynwb/compare/2.7.0..2.8.2#diff-e1599233197e637d0598c751d848a922cba3458d6e206efda4c10c4704fd0432R50-R51

now uses pynwb's get_type_map function, which deepcopy's pynwb's type map, which is substantially larger than hdmf's. the only place i see that get used is here: https://github.com/hdmf-dev/hdmf/blob/874db31fb171577bfc0c962708786f9774ea6b1b/src/hdmf/container.py#L91

which constructs a setter method when docval requests one. The problem is that _get_type_map gets called every time that a property is set, and it makes a very expensive deepcopy call (to hdmf's TypeMap.__deepcopy__).

that __deepcopy__ calls TypeMap.merge, which explains the additional register_container_type et al extra calls.

i've found similar things in pynwb in the past where deepcopy is used to protect against mutation in a context where it isn't needed, eg in those setter calls there's no path to mutate the type map, so it should just return without copying.