Importing QuPathProject taking up >100GB memory

[hwarden162]

I am trying to use paquo on a linux cluster. I login to a node with 200GB of memory.

Once on the node I use tmux to open two terminals on the same node. In one of the terminals I activate a conda environment and open up a python window and run

import os
os.getpid()

I then go to my other window and run

top -p <my_pid>

which, as I understand it, allows me to see how much memory I am using. At this point it shows 134060 under VIRT.

In the python window I then run

from paquo.projects import QuPathProject

and then it shows 102.7g under VIRT. As I understand it, this means the QuPathProject object is currently using 102.7GB of memory. This is then giving me errors further down in my pipeline where I try and do much smaller operations but I don't have any memory left.

Here is my conda environment environment(1).txt

[ap--]

Hello @hwarden162,

Virtual memory is not a good proxy for real memory usage. Since paquo starts the JVM with a default setting of max ram usage of 50% of the systems ram (see: https://github.com/bayer-science-for-a-better-life/paquo/blob/51102306e7fc7d144807656641a2589233f57b11/paquo/.paquo.defaults.toml#L28 ) the value you report is a pretty good match.

I believe the memory issue you mention is probably due to something else. Could you provide the code snippet that reproduces the memory error? And provide the traceback or error message that's displayed when it occurs?

Cheers, Andreas

[hwarden162]

Hi @ap--,

This is the code I run:

from locale import normalize
from tifffile import imread
from csbdeep.utils import normalize
from stardist.models import StarDist2D
from shapely.geometry import Polygon
from paquo.projects import QuPathProject
from paquo.images import QuPathImageType

X = imread("/exports/igmm/eddie/boulter-lab/Hugh/StarDist/region.ndpi")
model = StarDist2D.from_pretrained('2D_versatile_he')
img = normalize(X, axis = (0,1))
labels, details = model.predict_instances(img, axes='YXC', n_tiles=(10,10,1), verbose = True)

<Some more code>

It is the img = normalize(X, axis = (0,1)) where the memory error gets thrown:

Traceback (most recent call last): File "", line 1, in File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/csbdeep/utils/utils.py", line 54, in normalize mi = np.percentile(x,pmin,axis=axis,keepdims=True) File "<array_function internals>", line 5, in percentile File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/lib/function_base.py", line 3867, in percentile return _quantile_unchecked( File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/lib/function_base.py", line 3986, in _quantile_unchecked r, k = _ureduce(a, func=_quantile_ureduce_func, q=q, axis=axis, out=out, File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/lib/function_base.py", line 3564, in _ureduce r = func(a, **kwargs) File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/lib/function_base.py", line 4109, in _quantile_ureduce_func x_below = take(ap, indices_below, axis=0) File "<array_function internals>", line 5, in take File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/core/fromnumeric.py", line 190, in take return _wrapfunc(a, 'take', indices, axis=axis, out=out, mode=mode) File "/exports/igmm/eddie/kudla-lab/Hugh/Conda/conda_envs/paquo-env/lib/python3.10/site-packages/numpy/core/fromnumeric.py", line 57, in _wrapfunc return bound(*args, **kwds) numpy.core._exceptions._ArrayMemoryError: Unable to allocate 7.22 GiB for an array with shape (2583691264, 3) and data type uint8

However, if I run the same code but with from paquo.projects import QuPathProject removed, the script runs perfectly with no memory errors (up to the point where I need to use paquo). Obviously this isn't an error from the paquo library, but removing the QuPathProject import does fix the problem.

Thanks, Hugh

[ap--]

Thanks for the traceback and the additional explanation!

Looks like I am wrong and we really reserve 50% of RAM then. The good thing is you can easily override the setting. But we should change the default to have a reasonable upper limit.

To fix your issue, follow the instructions here: https://paquo.readthedocs.io/en/latest/configuration.html to create a custom paquo configuration file on your cluster replacing the JAVA_OPTS -XX:MaxRAMPercentage=50 setting with -Xmx8g (I think 8Gb should be reasonable)

Let me know if anything is unclear and if this solves your issue.

Cheers, Andreas

[hwarden162]

I ran the python -m paquo config --search-tree command and chose one of the directories.

I then ran python -m paquo config --list --default > /path/to/.paquo.toml and changed

java_opts = [ "-XX:MaxRAMPercentage=50", ]

to

java_opts = [ "-Xmx8g", ]

Now, python -m paquo config --list reads

# current paquo configuration # =========================== # format: TOML qupath_dir = "" qupath_search_dirs = [ "/opt", "/Applications", "c:/Program Files", "/usr/local", "~/Applications", "~/AppData/Local", "~",] qupath_search_dir_regex = "(?i)qupath.*" qupath_search_conda = true qupath_prefer_conda = true java_opts = [ "-Xmx8g",] safe_truncate = true mock_backend = false cli_force_log_level_error = true warn_microsoft_store_python = true

so it looks like I successfully altered the .paquo.toml but importing QuPathProject is still taking up half of my memory (measured as before) and I am still getting the error as before when trying to normalise my image (and going over my memory allowance). I have tried completely exiting conda and my session on the terminal to see if rebooting would help but I am still getting the error.

Thanks, Hugh

EDIT1: Putting backslash before hashtags to fix markdown formatting EDIT2: More markdown fixes to properly show config output

[ap--]

Hmmm, just to be on the safe side: Are you running your script from the same working directory, that you used to test if python -m paquo config --list returns the correct java_opts setting?

I'd now try to go back to -XX: MaxRAMPercentage=1 and use a very small value like 1 to see if you're able to make it work. Also: what's the peak memory usage of your script without importing paquo? What are the dimensions of region.ndpi?

[hwarden162]

I am definitely running python -m paquo config --list in the same directory as I am running the code from.

I changed the .paquo.toml putting in -XX: MaxRAMPercentage=4. This showed up when I listed out the config but still when I imported paquo it seemed to take half of my memory and my pipeline failed.

Without importing paquo, the peak memory usage of my script appears to be ~38.2GB

[ap--]

Thanks for checking. Something definitely seems to be off, considering your script requiring ~40gb and you still run out of memory on a 200gb machine. I'll try to create a test case to reproduce the oom crash in a more controlled environment, and then we can hopefully improve the default behavior of paquo.

In the meantime my recommendation would be to lazy import paquo when you need it after the bigger computations are done, or factor out the paquo part into a separate script.

I'll update this issue when I start work on this.

Cheers, Andreas 😃

[hwarden162]

Thanks very much!

Paquo is a really useful bit of kit that is giving me a lot more flexibility in my workflows. Please let me know if I can help with any more information about the bug.

Best Hugh