Fixing and documenting the CrowdGuard workflow tutorial #1289
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Signed-off-by: Teodor Parvanov <[email protected]>
Signed-off-by: Teodor Parvanov <[email protected]>
Signed-off-by: Teodor Parvanov <[email protected]>
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Signed-off-by: Teodor Parvanov <[email protected]>
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Signed-off-by: Teodor Parvanov <[email protected]>
rahulga1
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openfl-tutorials/experimental/workflow/CrowdGuard/PoisoningAttackDemo.ipynb
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bandatarunkumar
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In this PR I've focused on enabling the CrowdGuard example to run on CPU (5 train/defend rounds are runnable within a reasonable amount of time). It is noteworthy, however, that this example cannot execute on a normal PC, as it requires at least 18GB of dedicated RAM. Running CrowdGuard on GPU-accelerated collaborators probably doesn't make much sense anyway as GPUs offer limited (if any) support for confidential computing.
Thanks, @bandatarunkumar for helping me thoroughly test the proposed changes!
PS: I've also added a step-by-step guide on how to run the
cifar10_crowdguard.pydemo script.