Comments (3)
(I must explain that I use pytorch, not tensorflow, but I think it's doesn't matter) when we use tf.nn.conv2d, the model.parameters are weight and bias,and Adam or SGD will update these value; but we use EquiConv instead of conv2d, how to update parameters use Adam or SGD
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Hi!
As you can see in our code, and as it's explained in our paper, EquiConvs are built on top of deformable convolutions, that are already implemented like standard convolutions, with their correspondent learnable weights and bias.
If you are using pytorch, you will need to import 'deform_conv2d' from 'torchvision.ops.deform_conv'.
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Hi!
When I use EquiConv to train, an error occur: error in deformable_im2col: out of memory, and err = 2, cudaSuccess = 0, have you ever encountered this kind of error. Online solutions are :change to a small model 、small dataset. If you are free
(1)Can you tell me the specific machine configuration during your training? GPU……
(2) In your paper, the input of the network is image of 256128. So do you encountered similar errors when using larger images?If not, why image size is designed to be 256128?
(3)Can you share train.py with me? I want to use your code to test whether equiconv can run on my computer.
Thank you very much for your help during this time.
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Related Issues (15)
- test deform conv fails HOT 6
- Question about formula (5) in 4.1 EquiConvs Details HOT 3
- Question about pij in formula (3)
- How to understand the use of K and inv_K? HOT 2
- Error in deformable_im2col? HOT 1
- A question about CE HOT 1
- help
- layout 3d HOT 2
- Hi. where can I get the model.ckpt ? HOT 4
- Thanks for providing the code! Can you provide the training script please?
- How to recovery layout from the corner map and the edge map? HOT 2
- About results of EquiConvs and StdConvs HOT 1
- Mac air 2
- Questions about formula(5) in 4.1 EquiConvs
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