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nipreps / smriprep

Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools)
https://nipreps.github.io/smriprep
Apache License 2.0
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23.2.0a1: `DynamicTraitedSpec` object has no attribute `T1w_preproc` #398

Closed smeisler closed 11 months ago

smeisler commented 11 months ago

What happened?

Using the new alpha release, fMRIPrep quickly failed. Note that this same command worked on the same dataset at an earlier version of the next branch pulled about a week ago.

What command did you use?

singularity run -e --containall -B ${scratch},${templateflow_dir} \ 
$fmriprep_IMG $scratch/data $scratch/data/derivatives/fmriprep participant \
--participant_label ${subject:4} \
-w $scratch \
--fs-license-file ${scratch}/license.txt \
--fs-subjects-dir $scratch/data/derivatives/freesurfer/ \
--cifti-output 91k \
--project-goodvoxels \
--notrack \
--mem_mb 60000 \
--nprocs 16 \
--omp-nthreads 8  \
--slice-time-ref 0 \
--output-spaces T1w fsnative MNI152NLin2009cAsym

What version of fMRIPrep are you running?

23.2.0a1

How are you running fMRIPrep?

Singularity

Is your data BIDS valid?

Yes

Are you reusing any previously computed results?

FreeSurfer

Please copy and paste any relevant log output.

bids-validator@1.13.1
(node:17) Warning: Closing directory handle on garbage collection
(Use `node --trace-warnings ...` to show where the warning was created)
This dataset appears to be BIDS compatible.
        Summary:                Available Tasks:                     Available Modalities: 
        92 Files, 2.44GB        NSD Functional Localizer Task        MRI                   
        1 - Subject                                                                        
        1 - Session                                                                        

   If you have any questions, please post on https://neurostars.org/tags/bids.
231121-12:51:29,909 nipype.workflow IMPORTANT:
     Running fMRIPrep version 23.2.0a1

         License NOTICE ##################################################
         fMRIPrep 23.2.0a1
         Copyright 2023 The NiPreps Developers.

         This product includes software developed by
         the NiPreps Community (https://nipreps.org/).

         Portions of this software were developed at the Department of
         Psychology at Stanford University, Stanford, CA, US.

         This software is also distributed as a Docker container image.
         The bootstrapping file for the image ("Dockerfile") is licensed
         under the MIT License.

         This software may be distributed through an add-on package called
         "Docker Wrapper" that is under the BSD 3-clause License.
         #################################################################
231121-12:51:30,273 nipype.workflow IMPORTANT:
     Building fMRIPrep's workflow:
           * BIDS dataset path: /om2/scratch/tmp/smeisler/fsub_proc/sub-01/data.
           * Participant list: ['01'].
           * Run identifier: 20231121-125116_d251562e-f5a8-4dc6-8496-73f04e37b896.
           * Output spaces: T1w fsnative MNI152NLin2009cAsym:res-native.
           * Pre-run FreeSurfer's SUBJECTS_DIR: /om2/scratch/tmp/smeisler/fsub_proc/sub-01/data/derivatives/freesurfer.
231121-12:51:31,727 nipype.workflow INFO:
     ANAT Stage 1: Adding template workflow
231121-12:51:32,324 nipype.workflow INFO:
     ANAT Stage 2: Preparing brain extraction workflow
231121-12:51:32,414 nipype.workflow INFO:
     ANAT Stage 3: Preparing segmentation workflow
231121-12:51:32,420 nipype.workflow INFO:
     ANAT Stage 4: Preparing normalization workflow for ['MNI152NLin2009cAsym', 'MNI152NLin6Asym']
231121-12:51:32,433 nipype.workflow INFO:
     ANAT Stage 5: Preparing surface reconstruction workflow
231121-12:51:32,454 nipype.workflow INFO:
     ANAT Stage 6: Preparing mask refinement workflow
231121-12:51:32,457 nipype.workflow INFO:
     ANAT Stage 7: Creating T2w template
231121-12:51:32,466 nipype.workflow INFO:
     ANAT Stage 8: Creating GIFTI surfaces for ['white', 'pial', 'midthickness', 'sphere_reg', 'sphere']
231121-12:51:32,487 nipype.workflow INFO:
     ANAT Stage 8: Creating GIFTI metrics for ['thickness', 'sulc']
231121-12:51:32,495 nipype.workflow INFO:
     ANAT Stage 8a: Creating cortical ribbon mask
231121-12:51:32,499 nipype.workflow INFO:
     ANAT Stage 9: Creating fsLR registration sphere
231121-12:51:32,503 nipype.workflow INFO:
     ANAT Stage 10: Creating MSM-Sulc registration sphere
231121-12:51:33,717 nipype.workflow INFO:
     B0 field inhomogeneity map will be estimated with the following 3 estimator(s): [<EstimatorType.PHASEDIFF: 3>, <EstimatorType.PHASEDIFF: 3>, <EstimatorType.PHASEDIFF: 3>].
231121-12:51:34,413 nipype.workflow INFO:
     Setting-up fieldmap "auto_00000" (EstimatorType.PHASEDIFF) with <sub-01_acq-fMRI_run-2_phasediff.nii.gz, sub-01_acq-fMRI_run-2_magnitude1.nii.gz, sub-01_acq-fMRI_run-2_magnitude2.nii.gz>
231121-12:51:34,413 nipype.workflow INFO:
     Setting-up fieldmap "auto_00001" (EstimatorType.PHASEDIFF) with <sub-01_acq-fMRI_run-3_phasediff.nii.gz, sub-01_acq-fMRI_run-3_magnitude1.nii.gz, sub-01_acq-fMRI_run-3_magnitude2.nii.gz>
231121-12:51:34,413 nipype.workflow INFO:
     Setting-up fieldmap "auto_00002" (EstimatorType.PHASEDIFF) with <sub-01_acq-fMRI_run-4_phasediff.nii.gz, sub-01_acq-fMRI_run-4_magnitude1.nii.gz, sub-01_acq-fMRI_run-4_magnitude2.nii.gz>
231121-12:51:35,102 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:35,110 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:35,119 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:35,184 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:36,62 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:36,68 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:36,73 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:36,132 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:36,404 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:36,410 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:36,416 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:36,478 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:36,749 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:36,755 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:36,761 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:36,820 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:37,92 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:37,99 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:37,104 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:37,161 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:37,434 nipype.workflow INFO:
     Stage 1: Adding HMC boldref workflow
231121-12:51:37,598 nipype.workflow INFO:
     Stage 2: Adding motion correction workflow
231121-12:51:37,603 nipype.workflow INFO:
     Stage 3: Adding coregistration boldref workflow
231121-12:51:37,663 nipype.workflow IMPORTANT:
     BOLD series will be slice-timing corrected to an offset of 0s.
231121-12:51:41,882 nipype.workflow INFO:
     fMRIPrep workflow graph with 1961 nodes built successfully.
231121-12:51:55,5 nipype.workflow IMPORTANT:
     fMRIPrep started!
231121-12:51:56,682 nipype.workflow CRITICAL:
     fMRIPrep failed: 'DynamicTraitedSpec' object has no attribute 'T1w_preproc'

Additional information / screenshots

An HTML file was created that said there were no errors, oddly enough.

effigies commented 11 months ago

Wow, not sure how I missed that one. That'll be a fix in smriprep.