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- [x] Dataset
- [ ] Basic visualization (follow #7 )
- [ ] Literature
- [x] #8
- [x] @Tanvig Add the other paper for which you found code here
- [ ] Implementing the (2+1)D model (used i…
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Hello, I noticed you did not set bias=False in the 1x1 3d convolution layers which implements
phi=W_phi*x+B_phi
g=W_g*x+B_g
theta=W_theta*x+B_theta
I have read some materials and papers. None…
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Hi,
I'd like to use your library with models that are trained on 3d images. How hard do you think would it be for me to add support for 3d convolutions?
best regards
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## Description
Currently MXNet does not support upsampling on 5D tensors (3D images). There is more and more work being done in the medical field where 3D images are very common. As MXNet supports 3D…
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I was trying to make 3D convolutions work with DirectML with the following snippet:
```python
import numpy as np
import torch
import torch.nn as nn
import torch_directml as tdml
dml = tdml.dev…
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Is there any chance for a quick implementation of 3D convolutions with PAC? Thanks!
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Hi everyone,
does Caffe2 support N-dimensional datasets? For example 3D medical image data with multiple contrsats (4th dimension) and multiple time steps (5th dimension). So at least 3D convolutio…
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It was trained on 3D runs at 100x100x100. It would be good to work out how to do inference on 3D volumes bigger than this. We could process large 3D runs in batches and stitch the results together. Th…
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Right now does not seem to support 3D convolutions. I tried to convert my model with a bunch of conv3D layers and I get
`
ERROR: LoadError: "expected output_padding to be a single integer value o…
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### 🚀 The feature, motivation and pitch
Posting here to shop around and get feedback on the idea of generalizing the cross product operations in Pytorch to a hodge star operator: https://en.wikiped…