Comments (2)
I'm confused with this just like u, so i found in torch documents, and it demonstrates that when using torch.max(x ,dim) returns [max matrix, indict matrix] , [0] helps getting a max matrix. 👍
from attention-module.
I'm confused with this just like u, so i found in torch documents, and it demonstrates that when using torch.max(x ,dim) returns [max matrix, indict matrix] , [0] helps getting a max matrix. 👍
You are perfectly right. Thanks very much!
from attention-module.
Related Issues (20)
- About lp_pool and lse_pool
- about ResNet50+CBAM trained model. HOT 2
- can you give the bibtex, i want to cite you paper HOT 1
- BAM :unsupported operand type(s) for //: 'list' and 'int'
- The locations where BAM and CBAM are applied
- How to use your proposed model ResNet50+CBAM as backbone in other model on different dataset? HOT 1
- visualization HOT 2
- Combining two attention branches HOT 1
- "the ReLU activation function is followed by W0" Mentioned in your paper is different from your code? HOT 5
- Could you release the training code of MobileNet V2 ?
- Did anyone run the test code
- pre-trained model
- Can you please provide pre-trained model again? HOT 1
- About the pre-trained model HOT 1
- Has anyone run CBAM/BAM on 3D images?
- How to combine with CAM or Grad-CAM?
- the model_resnet.py code can not run on CUDA
- Question: Position of BN in BAM. HOT 2
- Bug in BAM: only support input height = width
- Issue in combine two channel step in BAM
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