Memory chokeholds

[mgxd]

Some troublesome nodes to monitor. I have not been able to profile the specifics here yet.

• aCompCor

  nibabies/nibabies/workflows/bold/confounds.py

  Lines 217 to 221 in b5d16d3

  	acompcor = pe.Node(
  	ACompCor(components_file='acompcor.tsv', header_prefix='a_comp_cor_', pre_filter='cosine',
  	save_pre_filter=True, save_metadata=True, mask_names=['CSF', 'WM', 'combined'],
  	merge_method='none', failure_mode='NaN'),
  	name="acompcor", mem_gb=8, nprocs=6) # TODO: Lessen expensive restrictions

• SignalExtraction

  nibabies/nibabies/workflows/bold/confounds.py

  Lines 248 to 249 in b5d16d3

  	signals = pe.Node(SignalExtraction(class_labels=signals_class_labels),
  	name="signals", mem_gb=8, n_procs=6) # TODO: Lessen expensive restrictions

• ROIsPlot

  nibabies/nibabies/workflows/bold/confounds.py

  Lines 296 to 297 in b5d16d3

  	rois_plot = pe.Node(ROIsPlot(colors=['b', 'magenta'], generate_report=True),
  	name='rois_plot', mem_gb=4) # TODO: Lessen expensive restrictions

When all run in parallel, the workflow crashes, likely due to memory. For now, the bandaid fix is to set n_procs to something fairly high and avoid running concurrently.

[mgxd]

another troublesome interface: sdcflows.interfaces.bspline.Coefficients2Warp

memory_profiler

Line #    Mem usage    Increment  Occurences   Line Contents
============================================================
    11     57.5 MiB     57.5 MiB           1   @profile
    12                                         def coeff():
    13     57.5 MiB      0.0 MiB           1       import os
    14     59.3 MiB      1.8 MiB           1       from scipy.sparse import vstack as sparse_vstack
    15     59.3 MiB      0.0 MiB           1       import numpy as np
    16     59.3 MiB      0.0 MiB           1       import nibabel as nb
    17     59.3 MiB      0.0 MiB           1       from nipype.utils.filemanip import fname_presuffix
    18     59.3 MiB      0.0 MiB           1       from sdcflows.interfaces.bspline import grid_bspline_weights
    19                                         
    20                                             # Calculate the physical coordinates of target grid
    21     59.4 MiB      0.2 MiB           1       targetnii = nb.load(in_target)
    22     62.8 MiB      3.4 MiB           1       allmask = np.ones_like(targetnii.dataobj, dtype="uint8")
    23                                         
    24     62.8 MiB      0.0 MiB           1       weights = []
    25     62.8 MiB      0.0 MiB           1       coeffs = []
    26                                         
    27    339.0 MiB      0.0 MiB           2       for cname in in_coeff:
    28     62.8 MiB      0.0 MiB           1           coeff_nii = nb.load(cname)
    29    337.8 MiB    274.9 MiB           1           wmat = grid_bspline_weights(targetnii, coeff_nii)
    30    337.8 MiB      0.0 MiB           1           weights.append(wmat)
    31    339.0 MiB      1.2 MiB           1           coeffs.append(coeff_nii.get_fdata(dtype="float32").reshape(-1))
    32                                         
    33    342.0 MiB      3.0 MiB           1       data = np.zeros(targetnii.shape, dtype="float32")
    34    389.5 MiB     47.4 MiB           1       data[allmask == 1] = np.squeeze(np.vstack(coeffs).T) @ sparse_vstack(weights)
    35                                         
    36    389.7 MiB      0.3 MiB           1       hdr = targetnii.header.copy()
    37    389.8 MiB      0.1 MiB           1       hdr.set_data_dtype("float32")
    38    390.0 MiB      0.1 MiB           2       out_field = fname_presuffix(
    39    389.8 MiB      0.0 MiB           1           in_target, suffix="_field", newpath=os.getcwd(),
    40                                             )
    41    391.7 MiB      1.7 MiB           2       targetnii.__class__(data, targetnii.affine, hdr).to_filename(
    42    390.8 MiB      0.0 MiB           1           out_field
    43                                             )
    44                                         
    45                                             # Generate warp field
    46    391.7 MiB      0.0 MiB           1       phaseEncDim = "ijk".index(pe_dir[0])
    47    391.7 MiB      0.0 MiB           1       phaseEncSign = [1.0, -1.0][len(pe_dir) != 2]
    48                                         
    49    391.7 MiB      0.0 MiB           1       data *= phaseEncSign * ro_time
    50                                         
    51    391.7 MiB      0.0 MiB           1       fieldshape = tuple(list(data.shape[:3]) + [3])
    52    391.7 MiB      0.0 MiB           2       out_warp = fname_presuffix(
    53    391.7 MiB      0.0 MiB           1           in_target, suffix="_xfm", newpath=os.getcwd(),
    54                                             )
    55                                             # Compose a vector field
    56    400.6 MiB      8.9 MiB           1       field = np.zeros((data.size, 3), dtype="float32")
    57    400.6 MiB      0.0 MiB           1       field[..., phaseEncDim] = data.reshape(-1)
    58    400.6 MiB      0.0 MiB           1       aff = targetnii.affine.copy()
    59    400.6 MiB      0.0 MiB           1       aff[:3, 3] = 0.0
    60                                             # Multiplying by the affine implicitly applies the voxel size to the shift map
    61    438.1 MiB     37.5 MiB           1       field = nb.affines.apply_affine(aff, field).reshape(fieldshape)
    62    438.8 MiB      0.7 MiB           2       warpnii = targetnii.__class__(
    63    438.1 MiB      0.0 MiB           1           field[:, :, :, np.newaxis, :].astype("float32"), targetnii.affine, None
    64                                             )
    65    438.8 MiB      0.0 MiB           1       warpnii.header.set_intent("vector", (), "")
    66    438.8 MiB      0.0 MiB           1       warpnii.header.set_xyzt_units("mm")
    67    445.9 MiB      7.0 MiB           1       warpnii.to_filename(out_warp)
    68                                         
    69    445.9 MiB      0.0 MiB           1       return out_field, out_warp