Comments (2)
wilson1yan
commented on August 20, 2024
Yes, there's definitely a chance for a bad random sample, but permutation wouldn't exactly work since we could have a MADE setup with an input dimension 10, and say, a hidden layer of size 1000. In this case, we would need to sample units with repetitive autoregressive groups.
I think in practice, since we usually sample a small number of masks (i.e. 1 - 4), it's unlikely to run into a really bad masking scheme. If its a large concern, we could probably implement some naive check and re-sample if needed (e.g. make sure all groups are hit at least once)
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diff7
commented on August 20, 2024
Well, it makes sense. Thank you!
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Related Issues (13)
- Bug in MADE sampling implementation in 'hw1_solutions.ipynb' HOT 1
- `optimizer.zero_grad` called after calculating loss instead of before in `lecture3_flow_models_demos.ipynb`.
- HW2 autoregressive flow for images solution issue HOT 3
- HW1 solutions Discretized Mixture of Logistics Parameter initialization confusion HOT 2
- Is log_det in preprocess function useful? HW2 HOT 1
- Where is HW 4? HOT 1
- Question regarding solutions availability
- clarification question
- Flows demo fails because of missing `.to(ptu.device)` HOT 2
- ActNorm implementation missing division by `std` on the shift parameter
- Reporting bugs/errors in `lecture3_flow_models_demos.ipynb` HOT 4
- What is `self.loc` in `MixtureCDFFlow` class? HOT 1
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