Segmentation fault running example on Mac Big Sur

[limsammy]

Hey, I'm having an odd issue.

Environment:

OS: macOS Big Sur 10.16 20G165 x86_64

$ uname -a
Darwin slim-Macbook.local 20.6.0 Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64 x86_64 i386 MacBookPro15,2 Darwin
$ xcode-select --version
xcode-select version 2384
$ python
Python 3.9.7 (default, Sep 14 2021, 16:22:39)
[Clang 12.0.5 (clang-1205.0.22.9)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> print(sys.version)
3.9.7 (default, Sep 14 2021, 16:22:39)
[Clang 12.0.5 (clang-1205.0.22.9)]
$ pip list
Package         Version
--------------- ---------
cycler          0.10.0
imageio         2.9.0
joblib          1.0.1
kiwisolver      1.3.2
llvmlite        0.37.0
matplotlib      3.4.3
networkx        2.6.3
numba           0.54.0
numpy           1.20.3
Pillow          8.3.2
pip             21.2.3
pyparsing       2.4.7
python-dateutil 2.8.2
PyWavelets      1.1.1
scikit-image    0.18.3
scikit-learn    1.0
scipy           1.7.1
setuptools      57.4.0
six             1.16.0
threadpoolctl   2.2.0
tifffile        2021.8.30

When I clone the repository and run the example notebook everything runs perfectly.

However when I try to copy the example code and run it standalone (or simply edit the notebook with an image of my own) I get a segmentation fault.

Any idea why this is happening? The segfault occurs with the example blazkowicz.jpg image too, even though it runs fine in the notebook on first run.

I am using Python 3.9.7 by the way. I've also tried installing all deps in both a virtual env as well as my global. On a macbook, do I need more resources?

EDIT: attempting to run the notebook again (specifically the first example with blazkowicz) causes the jupyter kernel to die.

Here is my stacktrace:

ERROR:asyncio:Exception in callback <TaskWakeupMethWrapper object at 0x112d2a0d0>(<Future finis...C: 1\r\n\r\n'>)
handle: <Handle <TaskWakeupMethWrapper object at 0x112d2a0d0>(<Future finis...C: 1\r\n\r\n'>)>
Traceback (most recent call last):
  File "/Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/asyncio/events.py", line 80, in _run
    self._context.run(self._callback, *self._args)
RuntimeError: Cannot enter into task <Task pending name='Task-4' coro=<HTTP1ServerConnection._server_request_loop() running at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/tornado/http1connection.py:823> wait_for=<Future finished result=b'GET /api/co...PC: 1\r\n\r\n'> cb=[IOLoop.add_future.<locals>.<lambda>() at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/tornado/ioloop.py:688]> while another task <Task pending name='Task-2' coro=<KernelManager._async_start_kernel() running at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/jupyter_client/manager.py:336>> is being executed.
ERROR:asyncio:Exception in callback <TaskWakeupMethWrapper object at 0x112f06ca0>(<Future finis...db1"\r\n\r\n'>)
handle: <Handle <TaskWakeupMethWrapper object at 0x112f06ca0>(<Future finis...db1"\r\n\r\n'>)>
Traceback (most recent call last):
  File "/Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/asyncio/events.py", line 80, in _run
    self._context.run(self._callback, *self._args)
RuntimeError: Cannot enter into task <Task pending name='Task-5' coro=<HTTP1ServerConnection._server_request_loop() running at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/tornado/http1connection.py:823> wait_for=<Future finished result=b'GET /kernel...9db1"\r\n\r\n'> cb=[IOLoop.add_future.<locals>.<lambda>() at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/tornado/ioloop.py:688]> while another task <Task pending name='Task-2' coro=<KernelManager._async_start_kernel() running at /Users/red_rocket/.pyenv/versions/3.9.7/lib/python3.9/site-packages/jupyter_client/manager.py:336>> is being executed.

---

Diving deeper into the actual pyxelate source with the example code and using a local copy of pyxelate codebase, I pinpointed the exact call that causes the segfault in the pyx module: It is the BayesianGaussianMixture.fit() method. The specific line in pyx.py is the super().fit(X) call on line 74

---

I also found a relevant issue regarding segfaults on the auto-sklearn repository: automl/auto-sklearn#688

Looks like there were some success using the the auto-sklearn docker container, but it does not appear pyxelate uses auto-sklearn, so I'm not sure if this docker container would fix the issue (I will attempt to run it in this container after posting).

[limsammy]

Ok, I just ran the example in the auto-sklearn docker container and it works. Must be an issue with Big Sur.

[sedthh]

Thanks for the update.