Summary of what happened:
Hi all,
I am currently running MRIQC with the newest version and keep running into crash reports. Sometimes it works and sometimes it doesn’t. See example crash report below. I’m assuming this is due to space/RAM availability (correct me if I’m wrong). How do you keep from constantly having to edit your script for space?
Command used (and if a helper script was used, a link to the helper script or the command generated):
#!/usr/bin/bash
#SBATCH -A PAS2302 # Account
#SBATCH -t 05:00:00 # Time limit (HH:MM:SS)
#SBATCH --mem=20G # Memory allocation per node
#SBATCH --output=slurm-%j.out # Standard output log file
#SBATCH --error=slurm-%j.err # Standard error log file
# Read command-line arguments
subject=$1
session=$2
##Note: Make sure you have the most updated version of MRIQC installed. This is version MRIQC v24.1.0.dev0+gd5b13cb5.d20240826 downloaded on 12/21/2024
# Then run your MRIQC command
singularity run --cleanenv \
--bind /fs/ess/PCON0341/projects/TERBO/YT/BIDS_temp:/mnt/bids_dir \
--bind /fs/ess/PCON0341/projects/TERBO/YT/MRIQC:/mnt/output_dir \
/fs/ess/PCON0341/projects/TERBO/containers/mriqc_latest.sif \
/mnt/bids_dir \
/mnt/output_dir \
participant \
--participant_label sub-$subject \
--session-id $session \
--n_procs 20 \
--mem_gb 20 \
-v \
--verbose-reports \
--resource-monitor \
--notrack \
--no-sub \
Version:
MRIQC v24.1.0.dev0+gd5b13cb5.d20240826
Environment (Docker, Singularity / Apptainer, custom installation):
Singularity .sif file
Data formatted according to a validatable standard? Please provide the output of the validator:
BIDS validator used through Python
Relevant log outputs (up to 20 lines):
Node: mriqc_wf.funcMRIQC.synthstrip_wf.synthstrip
Working directory: /fs/ess/PCON0341/projects/TERBO/TERBO_Pipeline/work/mriqc_wf/funcMRIQC/synthstrip_wf/23c0b96e96590090b543292b164a1c6eafb994bc/synthstrip
Node inputs:
args = <undefined>
border_mm = 1
environ = {}
in_file = /fs/ess/PCON0341/projects/TERBO/TERBO_Pipeline/work/mriqc_wf/funcMRIQC/synthstrip_wf/23c0b96e96590090b543292b164a1c6eafb994bc/pre_n4/clipped_corrected.nii.gz
model = /opt/freesurfer/models/synthstrip.1.pt
num_threads = 1
out_file = <undefined>
out_mask = <undefined>
use_gpu = False
Traceback (most recent call last):
File "/opt/conda/lib/python3.11/site-packages/mriqc/engine/plugin.py", line 64, in run_node
result['result'] = node.run(updatehash=updatehash)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 527, in run
result = self._run_interface(execute=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 645, in _run_interface
return self._run_command(execute)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/conda/lib/python3.11/site-packages/nipype/pipeline/engine/nodes.py", line 771, in _run_command
raise NodeExecutionError(msg)
nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node synthstrip.
Cmdline:
synthstrip -b 1 -i /fs/ess/PCON0341/projects/TERBO/TERBO_Pipeline/work/mriqc_wf/funcMRIQC/synthstrip_wf/23c0b96e96590090b543292b164a1c6eafb994bc/pre_n4/clipped_corrected.nii.gz --model /opt/freesurfer/models/synthstrip.1.pt -n 1 -o clipped_corrected_desc-brain.nii.gz -m clipped_corrected_desc-brain_mask.nii.gz
Stdout:
Stderr:
/opt/conda/lib/python3.11/site-packages/mriqc/synthstrip/cli.py:119: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
checkpoint = torch.load(modelfile, map_location=device)
Segmentation fault (core dumped)
Traceback:
RuntimeError: subprocess exited with code 139.
Screenshots / relevant information:
Getting error codes 137 and 139. Both sem to be similar.
Thanks.
–Subbi M.