Comments (2)
@chinhsuanwu Oh.. my.. I forgot that! I really really thank you so much! Have a good day. Thank you for your contribution!
from coatnet-pytorch.
Hi @jeongHwarr
If you are not using images with size 224x224, you should modify the first argument in CoAtNet.
For example,
net = CoAtNet((512, 512), 3, num_blocks, channels, num_classes=1000)
from coatnet-pytorch.
Related Issues (18)
- pretrained weights HOT 1
- When will you push your entire code?
- About stochastic depth rate
- About the Wi-j
- Model Pre-Trained CoAtNet HOT 1
- Love from China
- the question about the parameters compare with that from paper
- Perhaps a nicer way to estimate the relative position
- Inconsistencies in MBConv, with corrected code provided HOT 3
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- dots + relative positon bias having issue with dimension mismatch in Transformer Block!!!
- About the stochastic depth HOT 2
- About the # params HOT 1
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- Any pretrained network for fine-tuning? HOT 2
- Hello, first off, really appreciate your work!
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