Demo file fails at prediction step

[TaraBartolec]

Hello,

I am trying to run Cascadia and using your demo.mzML and I get the following errors.
Do you have any suggestions on how to fix?

Best,
Tara

(cascadia_env) bartolec@mac-savitski04 DIA_Cascadia % cascadia sequence demo.mzML cascadia.ckpt

> Augmenting spectra from: demo.mzML
> Generating 3868 augmented spectra
> /Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia//Volumes/savitski/01_users/Tara/Experiments/Colaborations/Elena/01_RetronExpression/R8/DIA_Cascadia/cascadia_02-13-18:06:13/temp.asf: 471657lines [00:05, 87807.38lines/s] 
> Running inference on augmented spectra from: demo.mzML
> No GPU found - running inference on cpu
> GPU available: True (mps), used: False
> TPU available: False, using: 0 TPU cores
> IPU available: False, using: 0 IPUs
> HPU available: False, using: 0 HPUs
> Predicting: 0it [00:00, ?it/s]Traceback (most recent call last):
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/bin/cascadia", line 8, in <module>
>     sys.exit(main())
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/cascadia/cascadia.py", line 202, in main
>     sequence()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/cascadia/cascadia.py", line 83, in sequence
>     preds = trainer.predict(model, dataloaders=train_loader)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 892, in predict
>     return call._call_and_handle_interrupt(
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 38, in _call_and_handle_interrupt
>     return trainer_fn(*args, **kwargs)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 938, in _predict_impl
>     results = self._run(model, ckpt_path=self.ckpt_path)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1112, in _run
>     results = self._run_stage()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1190, in _run_stage
>     return self._run_predict()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1244, in _run_predict
>     return self.predict_loop.run()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
>     self.advance(*args, **kwargs)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/pytorch_lightning/loops/dataloader/prediction_loop.py", line 97, in advance
>     dataloader_iter = enumerate(dataloader)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 441, in __iter__
>     return self._get_iterator()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 388, in _get_iterator
>     return _MultiProcessingDataLoaderIter(self)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1042, in __init__
>     w.start()
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/process.py", line 121, in start
>     self._popen = self._Popen(self)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/context.py", line 224, in _Popen
>     return _default_context.get_context().Process._Popen(process_obj)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/context.py", line 288, in _Popen
>     return Popen(process_obj)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/popen_spawn_posix.py", line 32, in __init__
>     super().__init__(process_obj)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/popen_fork.py", line 19, in __init__
>     self._launch(process_obj)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/popen_spawn_posix.py", line 47, in _launch
>     reduction.dump(process_obj, fp)
>   File "/opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env/lib/python3.10/multiprocessing/reduction.py", line 60, in dump
>     ForkingPickler(file, protocol).dump(obj)
> TypeError: cannot pickle '_nrt_python._MemInfo' object
> Predicting: 0it [00:00, ?it/s]
> 

I am running on an M2 Mac and have the following packages returned after running conda list:

packages in environment at /opt/homebrew/Caskroom/miniforge/base/envs/cascadia_env:
Name Version Build Channel
absl-py 2.1.0 pypi_0 pypi
aiohappyeyeballs 2.4.6 pypi_0 pypi
aiohttp 3.11.12 pypi_0 pypi
aiosignal 1.3.2 pypi_0 pypi
annotated-types 0.7.0 pypi_0 pypi
anyio 4.8.0 pypi_0 pypi
appdirs 1.4.4 pypi_0 pypi
arrow 1.3.0 pypi_0 pypi
async-timeout 5.0.1 pypi_0 pypi
attrs 25.1.0 pypi_0 pypi
backoff 2.2.1 pypi_0 pypi
beautifulsoup4 4.13.3 pypi_0 pypi
blessed 1.20.0 pypi_0 pypi
boto3 1.36.18 pypi_0 pypi
botocore 1.36.18 pypi_0 pypi
bzip2 1.0.8 h99b78c6_7 conda-forge
ca-certificates 2025.1.31 hf0a4a13_0 conda-forge
cascadia 0.0.6 pypi_0 pypi
certifi 2025.1.31 pypi_0 pypi
charset-normalizer 3.4.1 pypi_0 pypi
click 8.1.8 pypi_0 pypi
contourpy 1.3.1 pypi_0 pypi
croniter 1.4.1 pypi_0 pypi
cycler 0.12.1 pypi_0 pypi
dateutils 0.6.12 pypi_0 pypi
deepdiff 7.0.1 pypi_0 pypi
dill 0.3.9 pypi_0 pypi
editor 1.6.6 pypi_0 pypi
einops 0.8.1 pypi_0 pypi
exceptiongroup 1.2.2 pypi_0 pypi
fastapi 0.115.8 pypi_0 pypi
fastobo 0.12.3 pypi_0 pypi
filelock 3.17.0 pypi_0 pypi
fonttools 4.56.0 pypi_0 pypi
frozenlist 1.5.0 pypi_0 pypi
fsspec 2024.12.0 pypi_0 pypi
grpcio 1.70.0 pypi_0 pypi
h11 0.14.0 pypi_0 pypi
h5py 3.12.1 pypi_0 pypi
idna 3.10 pypi_0 pypi
inquirer 3.4.0 pypi_0 pypi
itsdangerous 2.2.0 pypi_0 pypi
jinja2 3.1.5 pypi_0 pypi
jmespath 1.0.1 pypi_0 pypi
kiwisolver 1.4.8 pypi_0 pypi
lark 1.2.2 pypi_0 pypi
libffi 3.4.2 h3422bc3_5 conda-forge
liblzma 5.6.4 h39f12f2_0 conda-forge
libsqlite 3.48.0 h3f77e49_1 conda-forge
libzlib 1.3.1 h8359307_2 conda-forge
lightning 2.0.9.post0 pypi_0 pypi
lightning-cloud 0.5.70 pypi_0 pypi
lightning-utilities 0.12.0 pypi_0 pypi
llvmlite 0.44.0 pypi_0 pypi
lxml 5.3.1 pypi_0 pypi
markdown 3.7 pypi_0 pypi
markdown-it-py 3.0.0 pypi_0 pypi
markupsafe 3.0.2 pypi_0 pypi
matplotlib 3.10.0 pypi_0 pypi
mdurl 0.1.2 pypi_0 pypi
mpmath 1.3.0 pypi_0 pypi
multidict 6.1.0 pypi_0 pypi
ncurses 6.5 h5e97a16_3 conda-forge
networkx 3.4.2 pypi_0 pypi
numba 0.61.0 pypi_0 pypi
numpy 1.26.4 pypi_0 pypi
openssl 3.4.1 h81ee809_0 conda-forge
ordered-set 4.1.0 pypi_0 pypi
packaging 24.2 pypi_0 pypi
pillow 11.1.0 pypi_0 pypi
pip 25.0.1 pyh8b19718_0 conda-forge
propcache 0.2.1 pypi_0 pypi
protobuf 5.29.3 pypi_0 pypi
psutil 6.1.1 pypi_0 pypi
pydantic 2.1.1 pypi_0 pypi
pydantic-core 2.4.0 pypi_0 pypi
pygments 2.19.1 pypi_0 pypi
pyjwt 2.10.1 pypi_0 pypi
pyparsing 3.2.1 pypi_0 pypi
pyteomics 4.7.5 pypi_0 pypi
python 3.10.16 h870587a_1_cpython conda-forge
python-dateutil 2.9.0.post0 pypi_0 pypi
python-multipart 0.0.20 pypi_0 pypi
pytorch-lightning 1.9.5 pypi_0 pypi
pytz 2025.1 pypi_0 pypi
pyyaml 6.0.2 pypi_0 pypi
rdkit 2024.9.5 pypi_0 pypi
readchar 4.2.1 pypi_0 pypi
readline 8.2 h92ec313_1 conda-forge
requests 2.32.3 pypi_0 pypi
rich 13.9.4 pypi_0 pypi
runs 1.2.2 pypi_0 pypi
s3transfer 0.11.2 pypi_0 pypi
selfies 2.2.0 pypi_0 pypi
setuptools 75.8.0 pyhff2d567_0 conda-forge
six 1.17.0 pypi_0 pypi
sniffio 1.3.1 pypi_0 pypi
sortedcontainers 2.4.0 pypi_0 pypi
soupsieve 2.6 pypi_0 pypi
spectrum-utils 0.4.2 pypi_0 pypi
starlette 0.45.3 pypi_0 pypi
starsessions 1.3.0 pypi_0 pypi
sympy 1.13.3 pypi_0 pypi
tensorboard 2.19.0 pypi_0 pypi
tensorboard-data-server 0.7.2 pypi_0 pypi
tk 8.6.13 h5083fa2_1 conda-forge
torch 2.0.1 pypi_0 pypi
torchmetrics 1.6.1 pypi_0 pypi
tqdm 4.67.1 pypi_0 pypi
traitlets 5.14.3 pypi_0 pypi
types-python-dateutil 2.9.0.20241206 pypi_0 pypi
typing-extensions 4.12.2 pypi_0 pypi
tzdata 2025a h78e105d_0 conda-forge
urllib3 2.3.0 pypi_0 pypi
uvicorn 0.34.0 pypi_0 pypi
wcwidth 0.2.13 pypi_0 pypi
websocket-client 1.8.0 pypi_0 pypi
websockets 12.0 pypi_0 pypi
werkzeug 3.1.3 pypi_0 pypi
wheel 0.45.1 pyhd8ed1ab_1 conda-forge
xmod 1.8.1 pypi_0 pypi
yarl 1.18.3 pypi_0 pypi

[justin-a-sanders]

Hi Tara,

Thanks for raising an issue! This looks like an error I have seen previously when pytorch tries to use system resources which it shouldn't. Do you have a GPU on your system, or are you trying to run CPU only inference?

Justin

[TaraBartolec]

Hi Justin,

Thanks for the quick response. I have a M2 Pro chip in a Macbook.
I am not sure what exactly it is using (I assume CPU based on the below:

Running inference on augmented spectra from: demo.mzML
No GPU found - running inference on cpu
GPU available: True (mps), used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs

Best,
Tara

[JosefineTM]

Dear both,
I am having the exact same issue as Tara, also on the Demo file. Also running on a Mac. Did you find a solution to the problem? :)

Best,
Josefine

[justin-a-sanders]

Hi Josefine,

Sorry, there is still an issue trying to run on the MPS backend for some of the new Apple chips. I'm looking into a fix, but it's a little tricky because I don't have such a Mac so I can't reproduce the problem myself. I will let you (and Tara) know when it's resolved.

In the mean time, if you do have access to a Linux system instead it will work there. You can also run Cascadia on Google Colab, where you will get a free GPU so inference will also be faster.

Justin

[JosefineTM]

Thank you so much for your fast answer, Justin!

I will try one of those

FYI, I overlooked the M2 chip part of Tara's comment. I have a Quad-Core Intel Core i5, but the error is the same.

Thanks for a nice program!