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{bio,vis}[foss/2022a] n2v v0.3.2, CSBDeep v0.7.4 w/ CUDA 11.7.0 #19030

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@boegel boegel commented Oct 17, 2023

(created using eb --new-pr)

@boegel boegel added the update label Oct 17, 2023
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boegel commented Oct 17, 2023

Test report by @boegel
SUCCESS
Build succeeded for 3 out of 3 (2 easyconfigs in total)
node3305.joltik.os - Linux RHEL 8.8, x86_64, Intel(R) Xeon(R) Gold 6242 CPU @ 2.80GHz (cascadelake), Python 3.6.8
See https://gist.github.com/boegel/f22c2ad636780a2d8da4448a0aaa3395 for a full test report.

@boegel boegel added this to the 4.x milestone Oct 17, 2023
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boegel commented Oct 17, 2023

@boegelbot please test @ jsc-zen2

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@boegel: Request for testing this PR well received on jsczen2l1.int.jsc-zen2.easybuild-test.cluster

PR test command 'EB_PR=19030 EB_ARGS= EB_REPO=easybuild-easyconfigs /opt/software/slurm/bin/sbatch --mem-per-cpu=4000M --job-name test_PR_19030 --ntasks=8 ~/boegelbot/eb_from_pr_upload_jsc-zen2.sh' executed!

  • exit code: 0
  • output:
Submitted batch job 3564

Test results coming soon (I hope)...

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Message to humans: this is just bookkeeping information for me,
it is of no use to you (unless you think I have a bug, which I don't).

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boegel commented Oct 17, 2023

@boegelbot please test @ generoso

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Test report by @boegelbot
SUCCESS
Build succeeded for 2 out of 2 (2 easyconfigs in total)
jsczen2c1.int.jsc-zen2.easybuild-test.cluster - Linux Rocky Linux 8.5, x86_64, AMD EPYC 7742 64-Core Processor (zen2), Python 3.6.8
See https://gist.github.com/boegelbot/79f095010af97bb34b35965bcec6a45b for a full test report.

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boegel commented Oct 17, 2023

Test report by @boegel
SUCCESS
Build succeeded for 2 out of 2 (2 easyconfigs in total)
node3905.accelgor.os - Linux RHEL 8.8, x86_64, AMD EPYC 7413 24-Core Processor (zen3), 4 x NVIDIA NVIDIA A100-SXM4-80GB, 535.104.12, Python 3.6.8
See https://gist.github.com/boegel/e1057c3a82962104739cc3d9eebbb16f for a full test report.


name = 'n2v'
version = '0.3.2'
versionsuffix = '-CUDA-11.7.0'
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I'm curious, why did you remove CUDA as a direct dependency (which then prevented you from using the %(cudaver)s template here), is it the case that n2v itself doesn't use CUDA, only via CSBDeep, and you wanted to make that clear?

If that's the case, is this a distinction we should be looking out for in PRs?

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