I am trying to use templates generated from a volume and get the following error message
[CPU: 352.0 MB Avail: 122.15 GB]
Traceback (most recent call last):
File “cryosparc_master/cryosparc_compute/run.py”, line 96, in cryosparc_compute.run.main
File “cryosparc_master/cryosparc_compute/jobs/template_picker_gpu/run.py”, line 61, in cryosparc_compute.jobs.template_picker_gpu.run.run
File “cryosparc_master/cryosparc_compute/jobs/template_picker_gpu/run.py”, line 237, in cryosparc_compute.jobs.template_picker_gpu.run.do_pick
File “cryosparc_master/cryosparc_compute/jobs/template_picker_gpu/template_pick_gpu.py”, line 171, in cryosparc_compute.jobs.template_picker_gpu.template_pick_gpu.rotate_downsample
numpy.core._exceptions._ArrayMemoryError: Unable to allocate 168. GiB for an array with shape (8, 72, 8860, 8860) and data type float32
Another strange issue, and I assume with a related cause, is that the images of the templates in the template picker event log do not match those from the create template job. In the event log they are displayed as blank, grey squares. The create template image shows each template as expected, looking like the map they were generated from. The first pictures are the templates as they look from Create Templates, the second is what an individual template looks like in the Template Picker event log.
Initially I generated the default 50 templates from the map volume I imported, with the “Unable to allocate” number being much higher. The workstation has 256 GB of memory, more than the 168 apparently needed for this job, which had only 8 templates. I’m using only 250 movies while optimizing other parameters, so it’s not like I’m running a 4000 movie set and running out of swap or storage space.
Strangely, if I use templates from Select 2D, this issue does not occur. I used 14 templates from Select 2D successfully with the exact same set of movies, same settings for template picker; cloned the successful job and replaced only the templates. The pixel box value was 280, I also tried reducing that to 70 (four-fold reduction), but the error persists.
Any assistance is welcome, thank you.