Comments (2)
I'm not too familiar with FMNs, but it seems like it's a hierarchical network with a different attention mechanism? In principle you can use ToMe on anything that uses tokens, but like you said you'd need to be careful about the downsampling layers. You might be able to use ToMe instead of those downsampling layers, but that would probably require some exploration to figure out what's best.
from tome.
This problem is still up for debate in the research world, so we can only answer things that have already been covered in our paper.
from tome.
Related Issues (20)
- Does ToMe work for focal modulation networks? HOT 1
- (Question) LayerNorm for queries and keys HOT 2
- I keep getting this issue, how do I fix it? HOT 1
- Does ToMe work for Restormer? HOT 2
- hyper-parm "r" in ViT-g/14 HOT 4
- Can ToMe be applied together with RoPE? HOT 1
- Used in the vanilla Transformer HOT 6
- How do you understand the phrase "This can change the outcome of softmax attention: if we merge two tokens with the same key, that key has less effect in the softmax term" in Part Tracking Token Size ? HOT 5
- Has anyone been able to successfully convert the timm+tome model to onnx? HOT 2
- How to restore it to its original shape HOT 1
- Training Speedup for ToMe with Video HOT 3
- How to implement ToMe to image encoders in CLIP model? HOT 1
- Video Classification off-the-shelf model
- About inference acceleration for multi-modal large language models HOT 3
- End-to-end inference doesn't be accelerated. HOT 3
- AttributeError: 'ToMeVisionTransformer' object has no attribute 'blocks' HOT 3
- About using ToMe in ImageEncoderViT within segment anything HOT 2
- Question regarding scatter_reduce
- Why do we need this code snippet for training MAE? HOT 1
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from tome.