Comments (2)
albertfgu
commented on July 26, 2024
1
There is a bug in PyTorch 1.11 which is causing the behavior of Dropout2d that you've observed: pytorch/pytorch#77081
We will add a warning and a fix for this.
dropinp is a hyperparameter that people sometimes use, and we also used in earlier experiments on WikiText-103.
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albertfgu
commented on July 26, 2024
1
The READMEs have been updated to mention this issue, and we have implemented a custom dropout function to avoid problems with the PyTorch implementation. Perhaps in the far future when everyone is using torch 1.12 or later we can switch back to using the official functions.
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Related Issues (20)
- Paper, Table 1, Convolution number of parameters HOT 2
- About `krylov()` HOT 1
- Missing or misplaced "old" config folder? HOT 4
- "pretrained_model" is not defined before being called in train.py HOT 2
- Question on HMDB51 Dataset (S4ND Video Experiment)
- Unable to generate the weather using generate.py with time Series training checkpoint
- Large difference of inference result between forward and step
- AttributeError: 'SSMKernelDPLR' object has no attribute 'kernel' HOT 1
- Training on 12bits audio instead of 8bit? (Question, what do I need to change?)
- S4 Listops have nan loss HOT 2
- Quantization for S4/ Hippo
- The dynamics of the latent state of the model
- segmentation fault when running python -m train pipeline=mnist model=s4 HOT 1
- how to use the S4Block .step()
- KeyError in train.py self.dataset = SequenceDataset.registry[self.hparams.dataset._name_]
- Why is Sashimi's effect in speech signal enhancement (denoisy) so bad？
- Passing a video to S4ND
- CUDA error: no kernel image is available for execution on the device HOT 3
- Different results on the same dataset with the same Settings in the paper s4d
- Help with Forex Dataset Configuration for s4 Model
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