BASIL-error

Dear BASIL-developer,
we are using oxford_asl for analyzing a pASL experiment. However,  we are currently facing an error that I am not able to figure out.
You can find the terminal output attached.
Thank you very much and best wishes,
Christian
Terminal output:
(base) christian@xlsserver:/data/Christian/sub-021/ses-03$ oxford_asl -i perf/sub-021_ses-03_run-01_asl -c perf/sub-021_ses-03_run-01_m0scan_flirt --fslanat=anat/sub-021_ses-03_run-01_T1w.anat --mc --wp --spatial --tis 1.99 --iaf=tc -o perf/cbf_run-01 --bolus 0.7 --tr=4.6 --cmethod=voxel --fmap=fmap/sub-021_ses-03_run-01_phasediff --fmapmagbrain=fmap/sub-021_ses-03_run-01_magnitude1_fsl-bet --fmapmag=fmap/sub-021_ses-03_run-01_magnitude1 --pedir=-y --echospacing=0.00061 --region-analysis
OXFORD_ASL - running
Version: v4.0.29-dirty Mon Feb 20 16:19:06 2023
Input file: perf/sub-021_ses-03_run-01_asl
Analysis in white paper mode
Pre-processing
Using structural images (bias corrected) from fsl_anat: anat/sub-021_ses-03_run-01_T1w.anat
Standard brain is: /usr/local/fsl/data/standard/MNI152_T1_2mm
Structural to standard transformation warp: anat/sub-021_ses-03_run-01_T1w.anat/T1_to_MNI_nonlin_coeff.nii.gz
Motion Correction
Motion correction to calibration image
Bolus duration: 0.7
Number of TIs in list: 1
TIs list: --ti1=1.99
Input ASL format is: tc
Input block format is: rpt
Number of voxels is:655360
Number of repeats in data is:4
Outputting ASL data mean at each TI
Done.
Number of inversion times: 1
Number of timepoints in data: 4
Number of repeats in data: 4
Operating in Single TI mode
1.99 1.99 1.99 1.99
1.99
Using FSL_ANAT outputs at: anat/sub-021_ses-03_run-01_T1w.anat
Bias field extracted from anat/sub-021_ses-03_run-01_T1w.anat sucessfully
Defaulting brain extracted mean ASL image as initial registration reference
Using brain extracted mean ASL image as initial registration reference
Creating WMseg for BBR registration
Performing registration
Using /tmp/fsl_vjf_kxhf_ox_asl/meanasl_brain as base for inital registration
Initial registration is FLIRT only
Performing registration
ASL_REG
Input file is: /tmp/fsl_vjf_kxhf_ox_asl/meanasl_brain
Registration MAIN stage (FLIRT)
Tidying up
ASL_REG - Done.
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/tmp_asl_reg/lowtohigh"
Generating calibration image in structural space
Creating mask
Generating dilated mask for initial BASIL runs
Distortion Correction using asl_reg
Performing registration
ASL_REG
Input file is: /tmp/fsl_vjf_kxhf_ox_asl/pwi
Creating output directory
Registration FINAL stage (BBR)
Registering fieldmap to structural
Running BBR with fieldmap
1.000113 0.997557 -0.069762 0.003601 0.000000 0.069843 0.995126 -0.069617 0.000000 0.001274 0.069699 0.997567 0.000000 -14.691910 2.985404 18.631045 1.000000
Making warp fields and applying registration to EPI series
BBR end
Saving FINAL output
Tidying up
ASL_REG - Done.
Applying combined warps to original data:

Warp: /tmp/fsl_vjf_kxhf_ox_asl/asldist_warp
Jacobian: /tmp/fsl_vjf_kxhf_ox_asl/distcorr/jacobian
Applying warps to ASL data
Moco: /tmp/fsl_vjf_kxhf_ox_asl/asldata.cat
Applying warps to calibration data
Calib->ASL: /tmp/fsl_vjf_kxhf_ox_asl/calib2asl.mat
Number of voxels is:655360
Number of repeats in data is:4
Outputting ASL data mean at each TI
Done.
T1: 1.65
T1b: 1.65
Setting up BASIL
pASL model
Fixed bolus duration
Variable arterial arrival time
Setting prior/initial (tissue/gray matter) bolus arrival time to 0
Single volume: informative noise prior will be used
Using SNR of 10 to set noise std dev
Runtime error (func=(main), adr=29): Square root of a negative number
Using a prior noise sd of:
Instructing BASIL to use automated spatial smoothing
BASIL options (/tmp/fsl_vjf_kxhf_ox_asl/basil_options.txt):

#FABBER options created by Oxford_asl --t1=1.65 --t1b=1.65 --tau=0.7 --bat=0 --prior-noise-stddev= --save-model-fit
Calling BASIL on data - conventional perusion image
Initial run of BASIL on data where we have avareged all repeats at each TI
Run time basil options:
--spatial
Creating output directory: /tmp/fsl_vjf_kxhf_ox_asl/init/basil
STEP 1: VB - Tissue
Welcome to FABBER 4.0.11-12-g99c29e6-dirty
Last commit: Wed May 11 07:38:41 2022
Logfile started: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step1/logfile
NEWMAT exception caught in fabber:
Invalid value given for option: = (Failed to convert to required type)
Final logfile: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step1/logfile
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/init/basil/step1/finalMVN"
STEP 2: Spatial VB Tissue - init with STEP 1
Welcome to FABBER 4.0.11-12-g99c29e6-dirty
Last commit: Wed May 11 07:38:41 2022
Logfile started: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/logfile
NEWMAT exception caught in fabber:
Invalid value given for option: = (Failed to convert to required type)
Final logfile: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/logfile
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/finalMVN"
End.
Using BASIL step /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/mean_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/mean_ftiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718723 Aborted                 (core dumped) fslmaths ${finalstep}/mean_ftiss -thr 0 $2/ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/mean_delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/mean_delttiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718726 Aborted                 (core dumped) fslmaths ${finalstep}/mean_delttiss -thr 0 $2/delttiss
Fabber variance calculator
Working in /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2
Calculating variance for: ftiss
FABBER: MVNtool
FabberRunDataNewimage::Loading mask data from '/tmp/fsl_vjf_kxhf_ox_asl/mask_dil'
FabberRunDataNewimage::Dimensions: x=128, y=128, z=40, vols=1
FabberRunDataNewimage::Voxel size: x=1.5mm, y=1.5mm, z=3mm, TR=1 sec
FabberRunDataNewimage::Intents: 0, 0, 0, 0
FabberRunDataNewimage::Setting coordinates from extent
Voxel data not found: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/finalMVN (File is invalid or does not exist)
Calculating variance for: delttiss
FABBER: MVNtool
FabberRunDataNewimage::Loading mask data from '/tmp/fsl_vjf_kxhf_ox_asl/mask_dil'
FabberRunDataNewimage::Dimensions: x=128, y=128, z=40, vols=1
FabberRunDataNewimage::Voxel size: x=1.5mm, y=1.5mm, z=3mm, TR=1 sec
FabberRunDataNewimage::Intents: 0, 0, 0, 0
FabberRunDataNewimage::Setting coordinates from extent
Voxel data not found: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/finalMVN (File is invalid or does not exist)
Done.
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/var_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/var_ftiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718739 Aborted                 (core dumped) fslmaths ${finalstep}/var_ftiss -bin -add 1 -uthr 1 -mul 1e12 -add ${finalstep}/var_ftiss $2/var_ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/var_delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/var_delttiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718741 Aborted                 (core dumped) fslmaths ${finalstep}/var_delttiss -bin -add 1 -uthr 1 -mul 1e12 -add ${finalstep}/var_delttiss $2/var_delttiss
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/init/basil/step2/finalMVN"
Main run of BASIL on ASL data
Run time basil options:
--spatial
Initial MVN for BASIL is: /tmp/fsl_vjf_kxhf_ox_asl/init/finalMVN
Creating output directory: /tmp/fsl_vjf_kxhf_ox_asl/basil
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/init/finalMVN"
STEP 1: VB - Tissue - init with STEP 0
Welcome to FABBER 4.0.11-12-g99c29e6-dirty
Last commit: Wed May 11 07:38:41 2022
Logfile started: /tmp/fsl_vjf_kxhf_ox_asl/basil/step1/logfile
NEWMAT exception caught in fabber:
Invalid value given for option: = (Failed to convert to required type)
Final logfile: /tmp/fsl_vjf_kxhf_ox_asl/basil/step1/logfile
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/basil/step1/finalMVN"
STEP 2: Spatial VB Tissue - init with STEP 1
Welcome to FABBER 4.0.11-12-g99c29e6-dirty
Last commit: Wed May 11 07:38:41 2022
Logfile started: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/logfile
NEWMAT exception caught in fabber:
Invalid value given for option: = (Failed to convert to required type)
Final logfile: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/logfile
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/basil/step2/finalMVN"
End.
Using BASIL step /tmp/fsl_vjf_kxhf_ox_asl/basil/step2
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/mean_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/mean_ftiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718791 Aborted                 (core dumped) fslmaths ${finalstep}/mean_ftiss -thr 0 $2/ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/mean_delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/mean_delttiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718793 Aborted                 (core dumped) fslmaths ${finalstep}/mean_delttiss -thr 0 $2/delttiss
Fabber variance calculator
Working in /tmp/fsl_vjf_kxhf_ox_asl/basil/step2
Calculating variance for: ftiss
FABBER: MVNtool
FabberRunDataNewimage::Loading mask data from '/tmp/fsl_vjf_kxhf_ox_asl/mask_dil'
FabberRunDataNewimage::Dimensions: x=128, y=128, z=40, vols=1
FabberRunDataNewimage::Voxel size: x=1.5mm, y=1.5mm, z=3mm, TR=1 sec
FabberRunDataNewimage::Intents: 0, 0, 0, 0
FabberRunDataNewimage::Setting coordinates from extent
Voxel data not found: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/finalMVN (File is invalid or does not exist)
Calculating variance for: delttiss
FABBER: MVNtool
FabberRunDataNewimage::Loading mask data from '/tmp/fsl_vjf_kxhf_ox_asl/mask_dil'
FabberRunDataNewimage::Dimensions: x=128, y=128, z=40, vols=1
FabberRunDataNewimage::Voxel size: x=1.5mm, y=1.5mm, z=3mm, TR=1 sec
FabberRunDataNewimage::Intents: 0, 0, 0, 0
FabberRunDataNewimage::Setting coordinates from extent
Voxel data not found: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/finalMVN (File is invalid or does not exist)
Done.
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/var_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/var_ftiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718805 Aborted                 (core dumped) fslmaths ${finalstep}/var_ftiss -bin -add 1 -uthr 1 -mul 1e12 -add ${finalstep}/var_ftiss $2/var_ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/var_delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/basil/step2/var_delttiss
/usr/local/fsl/bin/oxford_asl: line 532: 1718807 Aborted                 (core dumped) fslmaths ${finalstep}/var_delttiss -bin -add 1 -uthr 1 -mul 1e12 -add ${finalstep}/var_delttiss $2/var_delttiss
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl/basil/step2/finalMVN"
Performing final registration
Performing registration
ASL_REG
Input file is: /tmp/fsl_vjf_kxhf_ox_asl/ftiss
Registration FINAL stage (BBR)
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl/ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl/ftiss
Aborted (core dumped)
'/tmp/fsl_vjf_kxhf_ox_asl/mask.nii.gz' and '/tmp/fsl_vjf_kxhf_ox_asl/mask.nii.gz' are the same file
Running BBR
Image Exception : #63 :: No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Image Exception : #22 :: Failed to read volume /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Error : No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Failed to read volume /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Error : No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Could not open matrix file /tmp/fsl_llo_qz1e_asl_reg/low2high_final.mat
Image Exception : #63 :: No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Image Exception : #22 :: Failed to read volume /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Error : No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
Error : No image files match: /tmp/fsl_llo_qz1e_asl_reg/asldata_brain
/usr/local/fsl/bin/epi_reg: line 390: 1718967 Aborted                 (core dumped) $FSLDIR/bin/applywarp -i ${vepi} -r ${vrefhead} -o ${vout} --premat=${vout}.mat --interp=spline
BBR end
Saving FINAL output
cp: cannot stat '/tmp/fsl_llo_qz1e_asl_reg/low2high_final.mat': No such file or directory
Could not find a supported file with prefix "/tmp/fsl_llo_qz1e_asl_reg/low2high_final"
'/tmp/fsl_vjf_kxhf_ox_asl/tissseg.nii.gz' and '/tmp/fsl_vjf_kxhf_ox_asl/tissseg.nii.gz' are the same file
Tidying up
ASL_REG - Done.
Generating calibration image in structural space
Generating analysis mask from final structural registration
Using user-supplied structural->standard space warp to generate cortical GM/WM masks
T1t (for calibration): 1.3
Doing calibration using voxelwise M0 map
mkdir: cannot create directory 'perf/cbf_run-01/calib': File exists
Correcting the calibration (M0) image for short TR (using T1 of tissue 1.3)
Number of voxels is:216468
Number of repeats in data is:1
Start extrapolation!
Done.
Output: ftiss perfusion / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///ftiss"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
/usr/local/fsl/bin/oxford_asl: line 268: 1722736 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Mean perfusion in gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Mean perfusion in cortical gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/std_space///perfusion
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/std_space///perfusion
/usr/local/fsl/bin/oxford_asl: line 354: 1722741 Aborted                 (core dumped) fslmaths $outdir/std_space/$subdir_out/$parname -div $normval $outdir/std_space/$subdir_out/${parname}_norm
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/native_space///perfusion
/usr/local/fsl/bin/oxford_asl: line 354: 1722744 Aborted                 (core dumped) fslmaths $outdir/native_space/$subdir_out/$parname -div $normval $outdir/native_space/$subdir_out/${parname}_norm
Image Exception : #63 :: No image files match: perf/cbf_run-01/struct_space///perfusion
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/struct_space///perfusion
/usr/local/fsl/bin/oxford_asl: line 354: 1722746 Aborted                 (core dumped) fslmaths $outdir/struct_space/$subdir_out/$parname -div $normval $outdir/struct_space/$subdir_out/${parname}_norm
Output: delttiss arrival / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///delttiss"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///delttiss
/usr/local/fsl/bin/oxford_asl: line 268: 1722752 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///arrival
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Mean arrival in gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///arrival
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Mean arrival in cortical gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Mean perfusion in wm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Failed to read volume perf/cbf_run-01/native_space///perfusion
Error : No image files match: perf/cbf_run-01/native_space///perfusion
Mean perfusion in cerebral wm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///arrival
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Mean arrival in wm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///arrival
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Failed to read volume perf/cbf_run-01/native_space///arrival
Error : No image files match: perf/cbf_run-01/native_space///arrival
Mean arrival in cerebral wm is
Output: var_ftiss perfusion_var / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///var_ftiss"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
/usr/local/fsl/bin/oxford_asl: line 268: 1722769 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
(standard_in) 1: syntax error
Image Exception : #63 :: No image files match: perf/cbf_run-01/std_space///perfusion_var
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/std_space///perfusion_var
/usr/local/fsl/bin/oxford_asl: line 378: 1722775 Aborted                 (core dumped) fslmaths $outdir/std_space/$subdir_out/${parname}_var -div $normval $outdir/std_space/$subdir_out/${parname}_var_norm
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion_var
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/native_space///perfusion_var
/usr/local/fsl/bin/oxford_asl: line 378: 1722777 Aborted                 (core dumped) fslmaths $outdir/native_space/$subdir_out/${parname}_var -div $normval $outdir/native_space/$subdir_out/${parname}_var_norm
Image Exception : #63 :: No image files match: perf/cbf_run-01/struct_space///perfusion_var
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: perf/cbf_run-01/struct_space///perfusion_var
/usr/local/fsl/bin/oxford_asl: line 378: 1722779 Aborted                 (core dumped) fslmaths $outdir/struct_space/$subdir_out/${parname}_var -div $normval $outdir/struct_space/$subdir_out/${parname}_var_norm
Output: var_delttiss arrival_var / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///var_delttiss"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_delttiss
/usr/local/fsl/bin/oxford_asl: line 268: 1722790 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss
/usr/local/fsl/bin/oxford_asl: line 313: 1722794 Aborted                 (core dumped) fslmaths $tempdir/$subdir_in/$param -div $Moval -mul $multiplier $tempdir/$subdir_in/${param}_calib
Output: ftiss_calib perfusion_calib / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///ftiss_calib
/usr/local/fsl/bin/oxford_asl: line 268: 1722801 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion_calib
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Mean perfusion_calib in gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion_calib
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Mean perfusion_calib in cortical gm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion_calib
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Mean perfusion_calib in wm is
Image Exception : #63 :: No image files match: perf/cbf_run-01/native_space///perfusion_calib
Image Exception : #22 :: Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Failed to read volume perf/cbf_run-01/native_space///perfusion_calib
Error : No image files match: perf/cbf_run-01/native_space///perfusion_calib
Mean perfusion_calib in cerebral wm is
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
terminate called after throwing an instance of 'std::runtime_error'
what():  No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss
/usr/local/fsl/bin/oxford_asl: line 313: 1722808 Aborted                 (core dumped) fslmaths $tempdir/$subdir_in/$param -div $Moval -mul $multiplier $tempdir/$subdir_in/${param}_calib
Output: var_ftiss_calib perfusion_var_calib / /
Could not find a supported file with prefix "/tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib"
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Image Exception : #63 :: No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Image Exception : #22 :: Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
terminate called after throwing an instance of 'std::runtime_error'
what():  Failed to read volume /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
Error : No image files match: /tmp/fsl_vjf_kxhf_ox_asl///var_ftiss_calib
/usr/local/fsl/bin/oxford_asl: line 268: 1722814 Aborted                 (core dumped) applywarp --in=$tempdir/$subdir_in/$param --out=$outdir/std_space/$subdir_out/$parname --ref=$std --premat=$tempdir/asl2struct.mat --warp=$warp $APPLYWARP_OPTS
Regionwise analysis

Using oxford_asl output in perf/cbf_run-01/native_space
Traceback (most recent call last):
File "/usr/local/fsl/bin/oxford_asl_roi_stats", line 10, in
sys.exit(main())
File "/usr/local/fsl/lib/python3.10/site-packages/oxford_asl/roi_stats.py", line 594, in main
asl_ref = Image(os.path.join(outdir, "perfusion"))
File "/usr/local/fsl/lib/python3.10/site-packages/fsl/data/image.py", line 1246, in init
image      = op.abspath(addExt(image))
File "/usr/local/fsl/lib/python3.10/site-packages/fsl/data/image.py", line 1951, in addExt
raise e
File "/usr/local/fsl/lib/python3.10/site-packages/fsl/data/image.py", line 1938, in addExt
return fslpath.addExt(prefix,
File "/usr/local/fsl/lib/python3.10/site-packages/fsl/utils/path.py", line 196, in addExt
raise PathError('Could not find a supported file '
fsl.utils.path.PathError: Could not find a supported file with prefix "perf/cbf_run-01/native_space/perfusion"
Output is perf/cbf_run-01/
OXFORD_ASL - done.

I'm in the process of updating oxford_asl to v4.0.29-5-g09a5cba-dirty (fsl-oxford_asl=v4.0.29 via conda) in ASLPrep (see https://github.com/PennLINC/aslprep/pull/399) and am getting the same error. Does anyone know what causes it?


Optimize new value and start time bug

When trying to optimize with new value and start time we get an index out of range error.
Traceback (most recent call last): File "/usr/local/lib/python3.10/site-packages/rq/worker.py", line 1428, in perform_job rv = job.perform() File "/usr/local/lib/python3.10/site-packages/rq/job.py", line 1278, in perform self._result = self._execute() File "/usr/local/lib/python3.10/site-packages/rq/job.py", line 1315, in _execute result = self.func(*self.args, **self.kwargs) File "/service/./execute.py", line 33, in run output = eval(operation_name)(**kwargs) File "/usr/local/lib/python3.10/site-packages/pyciemss/interfaces.py", line 982, in optimize ).solve() File "/usr/local/lib/python3.10/site-packages/pyciemss/ouu/ouu.py", line 219, in solve result = basinhopping( File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_basinhopping.py", line 714, in basinhopping bh = BasinHoppingRunner(x0, wrapped_minimizer, take_step_wrapped, File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_basinhopping.py", line 78, in __init__ minres = minimizer(self.x) File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_basinhopping.py", line 302, in __call__ return self.minimizer(self.func, x0, **self.kwargs) File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_minimize.py", line 737, in minimize res = _minimize_cobyla(fun, x0, args, constraints, callback=callback, File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_cobyla_py.py", line 35, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_cobyla_py.py", line 278, in _minimize_cobyla sf = _prepare_scalar_function(fun, x0, args=args, jac=_jac) File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_optimize.py", line 288, in _prepare_scalar_function sf = ScalarFunction(fun, x0, args, grad, hess, File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_differentiable_functions.py", line 222, in __init__ self._update_fun() File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_differentiable_functions.py", line 294, in _update_fun fx = self._wrapped_fun(self.x) File "/usr/local/lib/python3.10/site-packages/scipy/optimize/_differentiable_functions.py", line 20, in wrapped fx = fun(np.copy(x), *args) File "/usr/local/lib/python3.10/site-packages/pyciemss/interfaces.py", line 969, in objfun_penalty return objfun(x) + max(5 * np.abs(objfun(x)), 5.0) File "/service/./models/operations/optimize.py", line 239, in <lambda> "objfun": lambda x: objfun( File "/service/./models/operations/optimize.py", line 96, in objfun weight = relative_importance[i] / sum_of_all_weights IndexError: list index out of range

Just keepings notes on why this is happening:
We have written out obj function lamda to be such that

x
initial_guess
objective_function_option
relative_importance

All have the same length. The issue with that is that x is the amount of variables being optimized over and our relative_importance is the amount of interventions we have
In this picture we have 1 relative importance of 5, but we have two variables being optimized over. beta's value and beta's time.

This has been finished with
https://github.com/DARPA-ASKEM/terarium/pull/5360
https://github.com/DARPA-ASKEM/pyciemss-service/pull/124
https://github.com/DARPA-ASKEM/pyciemss-service/pull/125


Return client payment pointer in introspection response

Instead of returning the client jwk and an opaque client id in the token introspection response, return the client payment pointer.
https://github.com/interledger/rafiki/blob/d808c85c428bfc5bc1193882905ce5fdc8fa5888/packages/auth/src/openapi/resource-server.yaml#L37-L41
This not only makes us consistently pass the client (and key) by reference (see: https://github.com/interledger/open-payments/pull/211), the RS will be able to check if a client request fits the grant access before querying the client's jwks.json
Implications:

client (id) no longer opaque to RS
RS makes request to client payment pointer's jwks.json (and/or caches key(s)), instead of AS
grants are bound to client instead of a specific client key

This kind of requires:

https://github.com/interledger/rafiki/issues/740

because it is currently using the token introspection definition from the old auth-server-open-api-spec.yaml instead of https://github.com/interledger/rafiki/blob/main/packages/auth/src/openapi/resource-server.yaml


As a user, I can edit the details of my appointments,

so that I can respond to any changes that clients might make

Closed as duplicate


PR test for Wercker

Current coverage is 32.03%

Merging #4 into master will not affect coverage as of 3f53557

@@            master      #4   diff @@
======================================
  Files           11      11
  Stmts          206     206
  Branches         0       0
  Methods         84      84
======================================
  Hit             66      66
  Partial          0       0
  Missed         140     140

Review entire Coverage Diff as of 3f53557

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Using sqlite in WAL mode causes file saving failure when used on JupyterHub on NFS

Description
We upgraded from lab 3.5 to 3.6, and that seems to have brought this dependency in. At startup, it seems to try to open a sqlite db in WAL mode under ~/.local/share/jupyter, which is on NFS. This fails intermittently, as sqlite's WAL mode is not supported on NFS. https://www.sqlite.org/wal.html states:

All processes using a database must be on the same host computer; WAL does not work over a network filesystem.

So on server startup, this fails with these log messages:
[I 2023-02-22 14:05:52.993 FileIdExtension] Configured File ID manager: ArbitraryFileIdManager
[I 2023-02-22 14:05:52.993 FileIdExtension] ArbitraryFileIdManager : Configured root dir: /home/jovyan
[I 2023-02-22 14:05:52.993 FileIdExtension] ArbitraryFileIdManager : Configured database path: /home/jovyan/.local/share/jupyter/file_id_manager.db
[I 2023-02-22 14:05:53.009 FileIdExtension] ArbitraryFileIdManager : Successfully connected to database file.
[I 2023-02-22 14:05:53.009 FileIdExtension] ArbitraryFileIdManager : Creating File ID tables and indices.
[W 2023-02-22 14:05:53.096 SingleUserLabApp manager:359] jupyter_server_fileid | extension failed loading with message: unable to open database file
[E 2023-02-22 14:05:53.096 SingleUserLabApp manager:360] jupyter_server_fileid | stack trace
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/manager.py", line 355, in load_extension
        extension.load_all_points(self.serverapp)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/manager.py", line 229, in load_all_points
        return [self.load_point(point_name, serverapp) for point_name in self.extension_points]
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/manager.py", line 229, in <listcomp>
        return [self.load_point(point_name, serverapp) for point_name in self.extension_points]
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/manager.py", line 222, in load_point
        return point.load(serverapp)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/manager.py", line 148, in load
        return loader(serverapp)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/application.py", line 453, in _load_jupyter_server_extension
        extension.initialize()
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/application.py", line 420, in initialize
        self._prepare_settings()
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/extension/application.py", line 302, in _prepare_settings
        self.initialize_settings()
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server_fileid/extension.py", line 23, in initialize_settings
        file_id_manager = self.file_id_manager_class(
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server_fileid/manager.py", line 244, in __init__
        self.con.execute("PRAGMA journal_mode = WAL")
    sqlite3.OperationalError: unable to open database file

Unfortunately, this means all file save operations via contentsmanager fail! So this is in the critical path for all file saves, new notebook creations, etc - even when not using RTC.
[E 2023-02-22 14:09:35.383 SingleUserLabApp web:1798] Uncaught exception GET /user/<name>/api/contents/KMeans_Tutorial.ipynb?type=notebook&_=1677092974636 (<IP_ADDRESS>)
    HTTPServerRequest(protocol='https', host='jupyter.utoronto.ca', method='GET', uri='/user/<name>/api/contents/KMeans_Tutorial.ipynb?type=notebook&_=1677092974636', version='HTTP/1.1', remote_ip='<IP_ADDRESS>')
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.10/site-packages/tornado/web.py", line 1713, in _execute
        result = await result
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/services/contents/handlers.py", line 116, in get
        self.contents_manager.get(
      File "/opt/conda/lib/python3.10/site-packages/jupytext/contentsmanager.py", line 207, in get
        model = self.super.get(path, content, type="notebook", format=format)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/services/contents/filemanager.py", line 424, in get
        model = self._notebook_model(path, content=content)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/services/contents/filemanager.py", line 372, in _notebook_model
        nb = self._read_notebook(
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/services/contents/fileio.py", line 267, in _read_notebook
        with self.open(os_path, "r", encoding="utf-8") as f:
      File "/opt/conda/lib/python3.10/contextlib.py", line 135, in __enter__
        return next(self.gen)
      File "/opt/conda/lib/python3.10/site-packages/jupyter_server/services/contents/fileio.py", line 198, in open
        with open(os_path, *args, **kwargs) as f:
    OSError: [Errno 121] Remote I/O error: '/home/jovyan/KMeans_Tutorial.ipynb'

We have reverted to JupyterLab 3.5 in the meantime.
Questions

Is fileid required even when not using RTC?
Does the db need to persist across JupyterHub sessions? if not, we can put it in /tmp (like in https://github.com/2i2c-org/infrastructure/pull/2246).
Does it need the WAL? Based on https://github.com/jupyter-server/jupyter_server_fileid/blob/99c183064f948279ed7ecda8d033786a4cee8ca8/jupyter_server_fileid/manager.py#L243 that looks like an intentional decision. If so, this would cause lots of problems on NFS

Very sorry to hear that you're running into compatibility issues. I wasn't aware that the WAL journal mode fails on NFS.

Is fileid required even when not using RTC?

Not at the moment, though there are plans to build new extensions that depend on fileid.

Does the db need to persist across JupyterHub sessions? if not, we can put it in /tmp (like in https://github.com/2i2c-org/infrastructure/pull/2246).

cc @fcollonval
Well, it depends on the extensions that are using fileid. If RTC is persisting the fileids in their own persistent store (which I believe they do, but am not certain of this), then the fileid database also must be persisted. Otherwise, no.

Does it need the WAL?

It's required when separate threads and processes are calling FileIdManager methods. Otherwise, database reads in the main process block writes in other processes.
However, I don't think it's required just for a fresh JupyterLab 3.6.x instance to work with RTC. The most obvious solution for NFS support is to make the WAL journal mode a configurable defaulting to False.
This issue may be remedied by migrating away from using sqlite directly and instead opting for aiosqlite, which should handle this case on its own. Assuming aiosqlite doesn't require the WAL journal mode, we can preserve functionality for the multi-process case, while supporting NFS.

The most obvious solution for NFS support is to make the WAL journal mode a configurable defaulting to False.

+1, I think this would be helpful in preventing issues for other JupyterHub users as they migrate to JupyterLab 3.6! We found it pretty quick but might be more difficult and frustrating for others, as this dependency comes through quite a few layers :)
I appreciate all the work on this! \o/

I was writing this up when these responses came in. Rather than on or off, would it make sense to provide different defaults based on the configured class and allow all values (via configuration)?

Hi @yuvipanda - I agree that WAL is the wrong value for the ArbitraryFileIdManager journal mode given this class is supposed to be file-system agnostic.
Seems like a db_journal_mode trait is desirable here with the default for ArbitraryFileIdManager being DELETE (i.e., default journal mode) and the default for LocalFileIdManager being WAL - which is already file-system sensitive.  This way operators/admins can "tune" their transaction journaling however they like but OOTB values "just work".

If I cut a new release of jupyter_server_fileid to revert the default journal mode, where does the target version need to be bumped? IOW, in which of the JupyterLab transitive dependencies is jupyter_server_fileid explicitly listed in pyproject.toml?

@kevin-bates

Rather than on or off, would it make sense to provide different defaults based on the configured class and allow all values (via configuration)?

Yes, that seems very reasonable. My apologies, I didn't get as much coffee today as I should have.

The main idea is that the default should not be the WAL journal mode however. I think we should try to support NFS out-of-the-box given the popularity of JupyterHub.

Rather than on or off, would it make sense to provide different defaults based on the configured class and allow all values (via configuration)?

Yes, that seems very reasonable. My apologies, I didn't get as much coffee today as I should have.

The main idea is that the default should not be the WAL journal mode however. I think we should try to support NFS out-of-the-box given the popularity of JupyterHub.

OK - even with LocalFileIdManager?  (So DELETE is the default for both classes?)
I ask for clarification because your previous comments contradict each other.  Seems like the default for LocalFIleIdManager could still be WAL given it is not the default class and its use is opt-in.

Good observation. Yes, that's also reasonable. To summarize: the next steps would be to make journal mode configurable, default to DELETE for ArbitraryFIDM and WAL for LocalFIDM.

This change should be fairly straight-forward. I'm currently really busy trying to get an initial release of Jupyter AI setup; can anybody else own this? If not, I can still tackle this by the end of the week.

I can go ahead and toss this in.
Regarding the dependency resolution/mystery...
It turns out that the package jupyter_server_ydoc is what is pulling in fileID.  However, it also appears that jupyter_server_ydoc has been both moved and renamed from the juptyer-server org to the jupyterlab org and is now called juptyerlab/jupyter_collaboration which can be inferred from the releases page.

Unfortunately, this means all file save operations via contentsmanager fail! So this is in the critical path for all file saves, new notebook creations, etc - even when not using RTC.

@yuvipanda - I'm not immediately seeing the connection between this issue and the general failures to persist content from the included stack trace.  Could you please shed light on how the inability to initialize the fileID manager interferes with opening a notebook file?

@yuvipanda Can you try installing the fileid 0.8.0 release manually and see if this fixes your issue?

@kevin-bates i did a little more digging, and unfortunately I couldn't find any logs indicating that file_id stuff is actually in the critical path for file saves. I did find stacktraces implicating the signatures database though (https://github.com/2i2c-org/infrastructure/issues/2245#issuecomment-1444602512), so perhaps that is to blame and not this?
Regardless, I think not using WAL on NFS is still the right call, but perhaps this is not as serious as I had feared. Thank you for digging in!
@dlqqq I'm going to be on vacation for a couple of weeks so won't really be able to do much until I'm back.

I couldn't find any logs indicating that file_id stuff is actually in the critical path for file saves.

Thanks for the update @yuvipanda - no worries, pure curiosity on my part (always trying to gain information).

I did find stacktraces implicating the signatures database though (https://github.com/2i2c-org/infrastructure/issues/2245#issuecomment-1444602512), so perhaps that is to blame and not this?

Interesting.  Looking at nbformat's use of SQLite, I see that it doesn't specify the journal_mode PRAGMA, but, as you state on that issue, the nbsignatures.db is on NFS, which implies that making the default journal_mode for ArbitraryFileIdManager default to DELETE isn't going to help if there's a general SQLite vs. NFS conflict any way.

Regardless, I think not using WAL on NFS is still the right call

Totally agree - making it completely configurable is more correct, but we may have other NFS-related battles per what we see in nbformat.
(Have a great vacation! 🌴)


Get / Set Project Owner

Hi all.
The TSC should be able to get and set the Project Owner. Any plans to have it implemented?

@Eddie7mail I saw your comment in the existing enhancement request for this (#269), so let's keep that as the issue to track this request. I'll also ping some people to find out what the latest status is there.

Great thanks!


Search results box persists while new query underway

The search result box (e.g. "In total 18 linked genes and 2 unlinked genes were found (2.17 seconds).") remains despite a new query starting until it is replaced by a new search result output

well spotted! will add a fix soon.


Upgrade npm version

Upgraded our npm version to 6.1.0 and ran the npm audit fix command that was introduced which upgrades dependencies with security issues to fixed versions, also ran npm dedupe to clean up our node modules.
My reasons for upgrading the npm version is:

Fixes this annoying issue https://github.com/npm/npm/issues/17749
Stops taking a full minute to resolve git repos (relevant as long as we're maintaining a fork of Falcor)
Stops randomly uninstalling the Falcor fork (again problems with git repos I guess)
Nice benefit is the npm ci command which runs faster as it skips some redundant steps and checks the consistency of our lockfile for us

I tried just upgrading our node version, but node v10 somehow crashes node-sass which we use to compile our .scss styles, and I have no idea what's going on there, would definitely have been cleaner, but I think this is worth it giving the annoying issues above

It's also new in npm 10 :). Yarn has had something similar for a while, but I think this is actually better than what yarn offers now, as it's also faster and skips a lot of stuff not relevant for deployment / CI. It also adds a lot of other nice features actually, (most of them stolen from Yarn I think haha), like automatic merge conflict in package-lock resolution etc, the security audits etc.


Implemented Graphs on User Profiles

This implements graphs for their lifetime statistics and therefore closes #88

I removed the Bindable usage here, because it is unnecessary as this is class intern. Bindables should be used when we need to bind data from logic (player, engine, etc.) to the ui, because the logic does not depend on ui stuff anymore.


change URI with URL

Fix #28

IMHO it should cache the varied keys too like that https://github.com/darkweak/souin/blob/master/rfc/standalone.go#L23 because some responses can set the Vary header.

Maybe different levels of cache


Not working

Hi. The Plugin appears in Homebridge but does not show any % and status shows "off". I tried switching to "on" but no difference. Checked Station Id, key etc and all OK. Any ideas?


Feature Request: Make on/off and Mode a single entity

Hi
great work! I was working on something like that but more complicated as I'm not good at programming ;-)
I was trying to get it run as a rest sensor via the api but I never had the time to actually get this to work.
I would like to have the on/off and the modes as single entity not as "controls" to use it for my functions.
My plan is to turn the device on and off or change the mode via an scheduler and the automation. I'm not using the auto humidity function.
Thank you so much.

Hey,
I am not sure what do you mean, this should be already available via standard home assistant services e.g. humidifier.turn_on / humidifer.turn_off / humidifier.set_mode that you can run in automation.
Is this what you need?

Hi.
Thank you for your fast reply. I'm relatively new to home assistant and I just found the services ;-)
I tried setting up an automation with  humidifier.turn_on / humidifer.turn_off and a toggle helper but it's not working.
I tried to call the service at the development tools / services tab but my humidifier (AH555) is not responding. Your card works perfectly fine.
Could it be related to https://github.com/Michsior14/ha-venta/issues/1 where you have to send the complete informations?
$ curl -H "Content-Type: application/json" -X POST "$VENTA_LOCAL_IP/api/telemetry?request=set" -d '{
"Power": 0,
"Automatic": 0,
"SleepMode": 0,
"FanSpeed": 1,
"Action": "control"
}'

Strange, this is exactly the same functionality that the humidifier entity uses. By default turn_on/off sends everything as mentioned in #1. What happens if you use humidifier.set_mode with level 1? Maybe there is something different in AH555 :/

Hi
nothing happens, see picture

I switched to YAML mode, see second picture. Could it be that there is something missing? I'm mor a Hardware than a Software guy ;-)

Happy new Year!

You need to specify either device or an entity (blue or green button in graphic mode / proper ids in yaml mode). This is the same for on/off service.

Ahh damnit...
those buttons were so obvious that accidentally I ignored them even in the automation...
Now it's working, thank you very much.
I guess the bug sat in front of the screen again.
Happy new Year

Great it works ;)
Happy new year!


Fix typings for IPrivateKey and IPublicKey

I've see missing types in IPrivateKey and IPublicKey.

@snanovskyi Is this released? I am still facing tsc error in recent packages.

@hyochan yes. react-native-virgil-crypto 0.60 has identifier property in both public and private keys.
The only problem right now is e3kit due to some TypeScript issues in our unit tests.

You can follow it here - https://github.com/VirgilSecurity/virgil-e3kit-js/pull/108. I think it will be available later today.

@snanovskyi Still facing this problem. I've updated packages today in here.

Hi @hyochan !
Sorry for a delay, we've just published e3kit version 2.2.1 with new crypto-types.
Please try it out.


TEPHRA-65 Transaction in progress should be able to read its own writes

Modifies the time range end used for reads to include the current transaction's write pointer and adds testing around write visibility.

LGTM


[Question] Is there any way to transpile to vanilla js? No commonjs or adm.

Hello!
I'm trying to build a module that the user (developer) will consume by either using:

Pure javascript: He'll have my class loaded in the global scope, for example.
Commonjs: He'll be able to call it using require - and maybe with SystemJS.
AMD: He'll be able to use it with RequireJS and maybe with SystemJS.
ES6: He'll be able to use it with the ES6 syntax.

So, right now I'm using gulp-typescript to transpile my code to the dist folder. I transpile once for commonjs, once for amd, once for es6.. but it seems that there's no way to transpile to pure Javascript (other than using the module syntax inside my .ts file).
Is there any way to accomplish this?
Thanks in advance!

For vanilla case, CommonJS and AMD, you could wrap your code in a UMD loader.
I'm fairly sure that detecting ES6 loading capability is still an unsolved problem.

As per #2036 we'll have the umd option for the --module flag in 1.5, but I don't think it covers the "standard JS" case.

@LPGhatguy, @DanielRosenwasser: well, I'll have to wait for 1.5 then.
Do you guys know if SystemJS compatibility is also target for 1.5?

Do you guys know if SystemJS compatibility is also target for 1.5?

Yes I do and yes it is. :smile:
Also see our list of compiler options.

Awesome!
Thank you!


Adds incorrect whitespace to output (needs "no-format" option)

If you pass this JSX string:

fooorbaz

You get this output:

    foo

  or

    baz

This will add whitespace between the em, "or" and strong, which is incorrect. If you use ReactDOMServer.renderToStaticMarkup, you get this, which is correct:

fooorbaz

This could be resolved by a noformat or similar option, which removed indentation and newlines in the output.

I like the idea of having a format: false option. Are you up for a pull request on that one?
I'm not sure when I will have time to address this request.

Thanks for the reply!
So, I wrote a PR, but then realized that I misconstrued slightly in that this issue is predicated on the output of the function being HTML. In my use case, I have JSX without Components, which I need to render to HTML cheaply (without bringing on renderToStaticMarkup).
However, the output of this function is JSX, which means that the whitespace no longer matters in the same sense. So I'm inclined to close this, unless you disagree with my assessment above.


Bug | Cheque details get reset if the file uploaded is large

Uploading a large file resets the fields without saving in E FIling. Size of the file uploaded 12.4 MB uploaded 3 times
https://drive.google.com/file/d/147Fz-XLwx0Akm1wCKMUSsGKMsOuPd2ft/view?usp=sharing

All testing is happening on UAT @manimaarans

It is working fine in both kerala dev and uat for large file upload (used 30 mb file).
ocr-service/verify is still giving 400, error is (The data value transmitted exceeds the capacity limit.)
@ankitSharmaBeehyv plz look into it.

Hi @Ramu-kandimalla  @rajeshcherukumalli I tested by uploading the 47mb it is working fine.
When network is Stable working fine without any issues, checked with low network connection working fine without encountering any issues, below are the reference for the same,

Litigant details = https://jam.dev/c/f59cd2c8-8153-411e-ab15-c529423546d6
Cheque details = https://jam.dev/c/457b3c6c-3645-4eff-bde3-e7bce6da0365
Debt/Liability = https://jam.dev/c/bcbd5430-ffe0-41bd-9842-41ea236643c0
Legal Demand Notice = https://jam.dev/c/c5a1d2d9-24fd-43d5-a31b-77565e343bcc
Complainant & Sworn Statement -- https://jam.dev/c/85a66eed-036d-47c6-b871-8460e669e142
Advocate details screen -- https://jam.dev/c/662f89b9-4047-4f7d-88cd-2421852c1d7e

Hi @devarajd94  Can you please verify and confirm


request package is deprecated, consider replacing with an alternative like node-fetch

The request package has been deprecated. This package only seems to use it in the http.js file, the advice appears to migrate to an alternative like node-fetch.
https://github.com/nodeca/probe-image-size/blob/7d7e4a91d232d2d6fca2339df61432e3c415b0b8/http.js#L38
https://github.com/nodeca/probe-image-size/blob/7d7e4a91d232d2d6fca2339df61432e3c415b0b8/http.js#L57
I'm not raising the issue due to any bug or vulnerabilities, just making you aware of the deprecation as it is raised as a warning during package installs:
warning gatsby-plugin-sharp > probe-image-size ><EMAIL_ADDRESS>request has been deprecated, see https://github.com/request/request/issues/3142

Cheers.

If isomorphic-fetch were used, it might even work on client-side code which would be amazing, instead of this:
error - ./node_modules/request/lib/har.js:3:0
Module not found: Can't resolve 'fs'

MEMO: https://github.com/tomas/needle looks promissing. Others has suspicious issues in tracker or lack of features.

https://github.com/nodeca/probe-image-size/commit/40f0968732808dcacfb1000b250e0d278c388727
Switched to needle


هنگام curl زدن اطلاعات بصورت JSON برنمیگرده.

Describe the bug
هنگام curl زدن اطلاعات بصورت JSON برنمیگرده.
To Reproduce
Steps to reproduce the behavior:
curl --request GET \
     --url https://api.priceto.day/v1/latest/irr/usd \
     --header 'accept: application/json'

Screenshots

Additional context
بنظر داخل مرورگر همه چیز اوکیه اما داخل کد پاسخ HTML میاد.
تصویر داخل مرورگر:

This API is hosted on a free version of Netlify, which has a limit on the number of executions.
To avoid exceeding this limit, I have setup a Rate Limit policy to block the sources that are sending many requests.
The first picture is the result of such requests.
The API endpoint you are hitting (https://api.priceto.day/v1/latest/irr/usd ) does not provide such a real time data. It means you don't need to request this URL more than once in at most 15 minutes. The source of the data rarely updates the data in less than an hour.
So you have two options:

Send less requests to the API, for example at most once every 15 minutes.

Use the other API endpoint which is direct JSON file in GitHub. This doesn't have any limit. So in your application replace https://api.priceto.day/v1/latest/irr/usd with https://raw.github.com/margani/pricedb/main/tgju/current/price_dollar_rl/latest.json.
The api.priceto.day API is exactly doing this here.
As you can see for getting USD which is a well-known currency, we map it to the price_dollar_rl which is the currency name in the source website. If you want a currency other than USD, you can find its mapping here.


Add support for plugin openvpn-auth-ldap

Hi, congratulations to this image, it works perfect.
Would it be possible to add support for the openvpn-auth-ldap plugin in order to allow authentication by need against an LDAP (ActiveDirectory).
By adding this line in the OVPN config by need together with the corresponding configuration would then enable the plugin:
plugin /usr/lib/openvpn/openvpn-auth-ldap.so /etc/openvpn/auth/auth-ldap.conf

+1

+1

Any news on that ? Could I just mount the openvpn-auth-ldap.so inside the container ?

+1


Hash keys returning an array

Consider the following JSON-structure converted to a Hash.
{
  "measured_at": "2013-04-30T12:03:29.968Z",
  "measurement_type": "measurement",
  "entries": [
    {"name": "weight", "unit": "cm", "value": "80.0"},
    {"name": "thighs", "unit": "cm", "value": "40.5"}
  ]
}

Let us assume that entries is a required key and a record can not be created without it.
params.require(:entries).permit(:name, :unit, :value)

This will unfortunately not work due to require returning the given key, which in this case results in an array.
[
  {"name": "weight", "unit": "cm", "value": "80.0"},
  {"name": "thighs", "unit": "cm", "value": "40.5"}
]

I'm more than willing to solve the use case as long as this is behavior that should be a part of Strong Parameters domain. If so, do you have any ideas @dhh?

@wizztjh Thanks for your solution :+1:

@wizztjh  Thanks !

Since @wizztjh seems to have a working solution for this problem I'm closing the issue.

Thanks for the solution @wizztjh, Works perfectly! :)

@wizztjh thanks man..solved the problem

@wizztjh thanks man you save my day.


Encountered unresolved custom op: TensorListReserve and failed to prepare

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): 18.04
TensorFlow installed from (source or binary): source
TensorFlow version (or github SHA if from source): training, export model used tensorflow 1.15.0, inference model used tensorflow lite CPP 2.3.1 (master) and 1.15.0 as well.

Provide the text output from tflite_convert
Added tf.enable_control_flow_v2() to model before exporting.
Used command (tensorflow 1.15.0) : tflite_convert --saved_model_dir=superpoint_640x480x_control_flow --enable_select_tf_ops --allow_custom_ops --output_file=testing.tflite
2020-10-29 14:18:08.106202: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-10-29 14:18:08.127674: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.127922: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2020-10-29 14:18:08.128040: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.128856: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-10-29 14:18:08.129575: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-10-29 14:18:08.129739: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-10-29 14:18:08.130698: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-10-29 14:18:08.131440: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-10-29 14:18:08.133886: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-10-29 14:18:08.133976: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.134418: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.134628: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-10-29 14:18:08.134848: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2020-10-29 14:18:08.158045: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2020-10-29 14:18:08.158687: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55b335094940 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-10-29 14:18:08.158725: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-10-29 14:18:08.158925: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.159353: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2020-10-29 14:18:08.159391: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.159408: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-10-29 14:18:08.159426: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-10-29 14:18:08.159441: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-10-29 14:18:08.159456: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-10-29 14:18:08.159471: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-10-29 14:18:08.159486: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-10-29 14:18:08.159550: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.159921: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.160242: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-10-29 14:18:08.160279: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.270633: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-10-29 14:18:08.270654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-10-29 14:18:08.270659: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-10-29 14:18:08.270764: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.271031: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.271270: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.271500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2968 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-10-29 14:18:08.272684: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55b337854f60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-10-29 14:18:08.272696: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce GTX 1050 Ti, Compute Capability 6.1
WARNING:tensorflow:From /home/anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/lite/python/convert_saved_model.py:60: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.
W1029 14:18:08.273251<PHONE_NUMBER>02816 deprecation.py:323] From /anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/lite/python/convert_saved_model.py:60: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.
INFO:tensorflow:Restoring parameters from superpoint_640x480x_control_flow/variables/variables
I1029 14:18:08.345254<PHONE_NUMBER>02816 saver.py:1284] Restoring parameters from superpoint_640x480x_control_flow/variables/variables
INFO:tensorflow:The given SavedModel MetaGraphDef contains SignatureDefs with the following keys: {'serving_default'}
I1029 14:18:08.741633<PHONE_NUMBER>02816 convert_saved_model.py:80] The given SavedModel MetaGraphDef contains SignatureDefs with the following keys: {'serving_default'}
INFO:tensorflow:input tensors info:
I1029 14:18:08.741893<PHONE_NUMBER>02816 convert_saved_model.py:99] input tensors info:
INFO:tensorflow:Tensor's key in saved_model's tensor_map: image
I1029 14:18:08.742036<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: image
INFO:tensorflow: tensor name: superpoint/image:0, shape: (1, 480, 640, 1), type: DT_FLOAT
I1029 14:18:08.742112<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/image:0, shape: (1, 480, 640, 1), type: DT_FLOAT
INFO:tensorflow:output tensors info:
I1029 14:18:08.742195<PHONE_NUMBER>02816 convert_saved_model.py:101] output tensors info:
INFO:tensorflow:Tensor's key in saved_model's tensor_map: descriptors
I1029 14:18:08.742318<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: descriptors
INFO:tensorflow: tensor name: superpoint/descriptors:0, shape: (1, 480, 640, 256), type: DT_FLOAT
I1029 14:18:08.742387<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/descriptors:0, shape: (1, 480, 640, 256), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: descriptors_raw
I1029 14:18:08.742443<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: descriptors_raw
INFO:tensorflow: tensor name: superpoint/descriptors_raw:0, shape: (1, 60, 80, 256), type: DT_FLOAT
I1029 14:18:08.742491<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/descriptors_raw:0, shape: (1, 60, 80, 256), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: prob_nms
I1029 14:18:08.742545<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: prob_nms
INFO:tensorflow: tensor name: superpoint/prob_nms:0, shape: (1, 480, 640), type: DT_FLOAT
I1029 14:18:08.742592<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/prob_nms:0, shape: (1, 480, 640), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: pred
I1029 14:18:08.742646<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: pred
INFO:tensorflow: tensor name: superpoint/pred:0, shape: (1, 480, 640), type: DT_INT32
I1029 14:18:08.742693<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/pred:0, shape: (1, 480, 640), type: DT_INT32
INFO:tensorflow:Tensor's key in saved_model's tensor_map: logits
I1029 14:18:08.742746<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: logits
INFO:tensorflow: tensor name: superpoint/logits:0, shape: (1, 60, 80, 65), type: DT_FLOAT
I1029 14:18:08.742793<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/logits:0, shape: (1, 60, 80, 65), type: DT_FLOAT
INFO:tensorflow:Tensor's key in saved_model's tensor_map: prob
I1029 14:18:08.742845<PHONE_NUMBER>02816 convert_saved_model.py:41] Tensor's key in saved_model's tensor_map: prob
INFO:tensorflow: tensor name: superpoint/prob:0, shape: (1, 480, 640), type: DT_FLOAT
I1029 14:18:08.742892<PHONE_NUMBER>02816 convert_saved_model.py:43]  tensor name: superpoint/prob:0, shape: (1, 480, 640), type: DT_FLOAT
2020-10-29 14:18:08.743259: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.743479: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2020-10-29 14:18:08.743506: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.743519: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-10-29 14:18:08.743530: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-10-29 14:18:08.743540: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-10-29 14:18:08.743551: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-10-29 14:18:08.743561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-10-29 14:18:08.743572: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-10-29 14:18:08.743610: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.743803: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.743984: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-10-29 14:18:08.744021: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-10-29 14:18:08.744028: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-10-29 14:18:08.744034: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-10-29 14:18:08.744104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.744316: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.744505: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2968 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
INFO:tensorflow:Restoring parameters from superpoint_640x480x_control_flow/variables/variables
I1029 14:18:08.809329<PHONE_NUMBER>02816 saver.py:1284] Restoring parameters from superpoint_640x480x_control_flow/variables/variables
2020-10-29 14:18:08.899389: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.899605: I tensorflow/core/grappler/devices.cc:55] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0
2020-10-29 14:18:08.899660: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2020-10-29 14:18:08.900032: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.900221: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2020-10-29 14:18:08.900248: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.900261: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-10-29 14:18:08.900272: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-10-29 14:18:08.900283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-10-29 14:18:08.900295: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-10-29 14:18:08.900306: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-10-29 14:18:08.900317: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-10-29 14:18:08.900352: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.900544: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.900711: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-10-29 14:18:08.900730: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-10-29 14:18:08.900736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-10-29 14:18:08.900742: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-10-29 14:18:08.900797: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.900991: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.901166: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2968 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-10-29 14:18:08.922872: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: graph_to_optimize
2020-10-29 14:18:08.922897: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: Graph size after: 675 nodes (0), 1166 edges (0), time = 5.041ms.
2020-10-29 14:18:08.922905: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: Graph size after: 675 nodes (0), 1166 edges (0), time = 4.969ms.
2020-10-29 14:18:08.922911: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: superpoint_pred_tower0_map_while_body_529
2020-10-29 14:18:08.922918: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: function_optimizer did nothing. time = 0.001ms.
2020-10-29 14:18:08.922924: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: function_optimizer did nothing. time = 0ms.
2020-10-29 14:18:08.922930: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: superpoint_pred_tower0_map_while_cond_528
2020-10-29 14:18:08.922936: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: function_optimizer did nothing. time = 0ms.
2020-10-29 14:18:08.922942: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   function_optimizer: function_optimizer did nothing. time = 0ms.
WARNING:tensorflow:From /home/anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/lite/python/util.py:249: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.convert_variables_to_constants`
W1029 14:18:08.937568<PHONE_NUMBER>02816 deprecation.py:323] From /home/anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/lite/python/util.py:249: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.convert_variables_to_constants`
WARNING:tensorflow:From /home/anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/python/framework/graph_util_impl.py:277: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.extract_sub_graph`
W1029 14:18:08.937732<PHONE_NUMBER>02816 deprecation.py:323] From /home/anaconda3/envs/dynim/lib/python3.7/site-packages/tensorflow_core/python/framework/graph_util_impl.py:277: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.compat.v1.graph_util.extract_sub_graph`
INFO:tensorflow:Froze 72 variables.
I1029 14:18:08.979997<PHONE_NUMBER>02816 graph_util_impl.py:334] Froze 72 variables.
INFO:tensorflow:Converted 72 variables to const ops.
I1029 14:18:08.988762<PHONE_NUMBER>02816 graph_util_impl.py:394] Converted 72 variables to const ops.
2020-10-29 14:18:08.996008: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.996231: I tensorflow/core/grappler/devices.cc:55] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 0
2020-10-29 14:18:08.996275: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2020-10-29 14:18:08.996592: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.996781: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2020-10-29 14:18:08.996805: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-10-29 14:18:08.996814: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-10-29 14:18:08.996821: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-10-29 14:18:08.996830: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-10-29 14:18:08.996838: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-10-29 14:18:08.996846: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-10-29 14:18:08.996853: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-10-29 14:18:08.996885: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.997076: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.997241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-10-29 14:18:08.997260: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-10-29 14:18:08.997265: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-10-29 14:18:08.997268: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-10-29 14:18:08.997320: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.997593: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-10-29 14:18:08.997811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2968 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-10-29 14:18:09.044065: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: graph_to_optimize
2020-10-29 14:18:09.044089: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 184 nodes (-67), 191 edges (-60), time = 21.371ms.
2020-10-29 14:18:09.044094: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 184 nodes (0), 191 edges (0), time = 6.549ms.
2020-10-29 14:18:09.044098: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: superpoint_pred_tower0_map_while_body_529
2020-10-29 14:18:09.044102: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 43 nodes (0), 49 edges (0), time = 0.965ms.
2020-10-29 14:18:09.044106: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 43 nodes (0), 49 edges (0), time = 0.767ms.
2020-10-29 14:18:09.044110: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:786] Optimization results for grappler item: superpoint_pred_tower0_map_while_cond_528
2020-10-29 14:18:09.044114: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 10 nodes (0), 7 edges (0), time = 0.403ms.
2020-10-29 14:18:09.044119: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:788]   constant_folding: Graph size after: 10 nodes (0), 7 edges (0), time = 0.141ms.

Same issue when use TFLiteConverter:
saved_model_dir = "superpoint_640x480x_control_flow"

converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir, input_arrays=["superpoint/image"] , input_shapes={"superpoint/image" : [1, 480, 640, 1]}, output_arrays=['superpoint/logits', 'superpoint/prob', 'superpoint/descriptors_raw', 'superpoint/descriptors', 'superpoint/prob_nms', 'superpoint/pred'])
converter.target_spec.supported_ops = [
  tf.lite.OpsSet.TFLITE_BUILTINS, # enable TensorFlow Lite ops.
  tf.lite.OpsSet.SELECT_TF_OPS # enable TensorFlow ops.
]
converter.allow_custom_ops = True
converter.experimental_new_converter = True
converter.optimizations = [tf.lite.Optimize.DEFAULT]
converter.target_spec.supported_types = [tf.float32]

tflite_model = converter.convert()
open("testing.tflite", "wb").write(tflite_model)

Standalone code to reproduce the issue
Reproduce with cpp code :
#include <iostream>

#include <tensorflow/tensorflow/lite/interpreter.h>
#include <tensorflow/tensorflow/lite/kernels/register.h>
#include <tensorflow/tensorflow/lite/string_util.h>
#include <tensorflow/tensorflow/lite/model.h>

int main()
{
    std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromFile("testing.tflite");
    if (!model)
    {
        std::cerr << "Failed to mmap tflite model" << std::endl;
        exit(0);
    }
    tflite::ops::builtin::BuiltinOpResolver resolver;
    std::unique_ptr<tflite::Interpreter> interpreter;
    if (tflite::InterpreterBuilder(*model.get(), resolver)(&interpreter) != kTfLiteOk)
    {
        std::cerr << "Failed to interpreter tflite model" << std::endl;
        exit(0);
    }
    interpreter->AllocateTensors();
}

Also, please include a link to a GraphDef or the model if possible. Attached saved model :
superpoint_640x480x_control_flow.tar.gz
Output Logs
ERROR: Encountered unresolved custom op: TensorListReserve.
ERROR: Node number 1 (TensorListReserve) failed to prepare.
I couldn't allocate input tensor memory, probably because of interpreter->AllocateTensors() failed.

Solved by myself by adding : tf.enable_resource_variables(), tf.enable_control_flow_v2() in export model script, and use this script to convert saved model to tflite
`converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS, tf.lite.OpsSet.SELECT_TF_OPS]
converter.allow_custom_ops = True
converter.experimental_new_converter = False
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()
`


Use gulp-cached to speed up development

https://github.com/timkurvers/blizzardry/blob/master/gulpfile.js#L17

Covered by f0aed46aa636a83ebb51ff48615025f06befa899.


Bots

When server auto restart the bots disappear

I'd assume that you mean the serverBots config doesn't spawn more bots upon restart.

Yes

@Agarian How to make aways spawn ?

@GhostShot3 Try adding the following code to the restart function:
if (this.config.serverBots) {
    for (var i = 0; i < this.config.serverBots; i++) this.bots.addBot();
    Logger.info("Added " + this.config.serverBots + " player bots");
}

Ok

Let me know if it doesn't work for you, but I can't guarantee I can help right away (no PC to test on).

I will test it

http://prntscr.com/ib4f9c

You probably added it wrong

Working ,you will add it as commit ?

Will do.


Fix BaseRegistry's items observable map

Fixes regression caused by Mobx-6

🤔

ERROR in /home/runner/work/lens/lens/src/renderer/components/dock/log.store.ts
[tsl] ERROR in /home/runner/work/lens/lens/src/renderer/components/dock/log.store.ts(123,4)
TS2552: Cannot find name 'autobind'. Did you mean 'autoBind'?
error Command failed with exit code 2.

@nevalla Let me fix that in master, #2260 was green but shouldn't have been.


enhance 3dt errors and bug fixes

make 3dt report more verbose errors
https://github.com/dcos/3dt/pull/49

fix bug to inject git commit to revision variable

:ship:

Turns out verbose is too much.

@spahl fixed

:ship:


feat(contract): add ability for admin to freeze diamond

What ❔
Add more control for hyperchain's admin

Why ❔

Checklist

[ ] PR title corresponds to the body of PR (we generate changelog entries from PRs).
[ ] Tests for the changes have been added / updated.
[ ] Documentation comments have been added / updated.

thank you @StanislavBreadless
too many conflicts, I have recreated the PR
https://github.com/matter-labs/era-contracts/pull/674


Improve readability of container/bin/prtester.sh

To simplify identifying ebuilds for testing, the new code makes use of git's ability to:

show multiple commits with one invocation
We can avoid an unnecessary for loop this way.

narrow down the output to certain types of changes
Possible types are:

Files that are Added (A), Copied (C), Deleted (D), Modified (M), Renamed (R),
have their type (i.e. regular file, symlink, submodule, ...) changed (T), are Unmerged (U),
are Unknown (X), or have had their pairing Broken (B)

I considered also scanning for copied files (if diff.renames is set to copies or copy), but I couldn't recreate any examples, where the changes weren't picked up by R.

format the log such that everything except the diffs (commits are separated by \n) is omitted.
Further boil down the output by only showing the names of changed files. This makes grepping for ebuilds easy.

I also dropped the second loop in favor of passing the ebuilds to pkg-testing-tool all at once. The newly unified testing report is  now identified by the commit hash of  HEAD. That's not too descriptive but I couldn't think of a suitable alternative.

Thank you! I'll sync the update on incus repo.


[Bug][java-client] No Retry when subscribing to topic via pattern

Search before asking

[X] I searched in the issues and found nothing similar.

Version
v2.9.3 is working,
v2.9.4, v2.10.x, v2.11.x aren't
Minimal reproduce step
Here is a sample main code that illustrate issue:
import org.apache.pulsar.client.api.PulsarClient;
import org.apache.pulsar.client.api.PulsarClientException;

public class Main {
    public static void main(String[] args) throws PulsarClientException {

        PulsarClient client =  PulsarClient.builder()
                .serviceUrl("pulsar://unresolvable.service:6650")
                .build();

        client.newConsumer().topicsPattern("public/default/.*").subscriptionName("test").subscribe();

    }
}

With client in version 2.9.3, you will see theses logs
Failed to open connection to unresolvable.service:6650 : org.apache.pulsar.shade.io.netty.resolver.dns.DnsResolveContext$SearchDomainUnknownHostException: Failed to resolve 'unresolvable.service' and search domain query for configured domains failed as well: [.]
...
[namespace: public/default] Could not get connection while getTopicsUnderNamespace -- Will try again in 1459 ms
multiple retry until timeout

With 2.9.4, you only have the first error, the future is never resolved, and the scheduled runnable is never run.
The behavior is different with non pattern subscription, that retry until address resolves.
What did you expect to see?
Same behavior as in v2.9.3
What did you see instead?
See minimal step, uncompleted future when subscribing a multiple topic consumer.
Anything else?
I've read commits between v2.9.3 and v2.9.4 and my guess is that https://github.com/apache/pulsar/commit/d9211c97776fe61baddb4d9b3c4049dfd37b48c7 may be responsible
Are you willing to submit a PR?

[X] I'm willing to submit a PR!

If my guess is correct it might even be a simple class cast exception not catched nor logged by future when casting executor to scheduled executor