tensorflow / tensorflow/privacy
Poor performance while using DPAdam in WGAN-GP
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- Python
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Description
I am trying to add privacy to my WGAN. With Adam optimizer without DP, my WGAN works well. But after I change it to
optimizer = DPAdamGaussianOptimizer(
l2_norm_clip=3,
noise_multiplier=0.5,
num_microbatches=1,
learning_rate=0.001)
The D_loss never went smaller than 1. And my output is not convincing neither. Anybody knows how to fix it?
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First steps
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Research direction
No files or tests are named. Start by reproducing the WGAN-GP training behavior with the shown DPAdamGaussianOptimizer settings, then compare it with the non-DP Adam configuration. Check whether the loss and output differences are reproducible and document a confirmed cause or a minimal, validated fix.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning, security
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100