Comments (5)
Expect the tensorflow interface
from fast-mpn-cov.
@guyibang @SoulCoderCN Hi all, we have implemented the TensorFlow version of our fast MPN-COV, but the code is not evaluated for reproducing the results as reported in our paper. We'll finish it as soon as possible. :)
from fast-mpn-cov.
@jiangtaoxie Hi,
May I ask if the Tensorflow implementation is ready ? I believe it will help many researchers who are following your great work. Thanks.
from fast-mpn-cov.
@WeitaoVan Thanks for your attention to our work! There are some problems in our current Tensorflow implementation, which cannot reproduce the results as our paper reported. As such, we are not ready to release Tensorflow version until it works fine.
from fast-mpn-cov.
TensorFlow implementation (https://github.com/XuChunqiao/Tensorflow-Fast-MPNCOV)
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Related Issues (20)
- RuntimeError: Error(s) in loading state_dict for DataParallel: HOT 4
- Fatal IO error: client killed HOT 5
- Why is your manual implementation via autograd.Function even faster than PyTorch 's autograd engine? HOT 2
- 1D version of Fast-MPN-Cov HOT 5
- Downloading problem? HOT 8
- CUB-200-20122数据集实验 HOT 2
- Should we use SVMs for FGVC? HOT 2
- fine tune issue HOT 4
- When will you update the Fine-grained classification results of resnet101 HOT 4
- Loss and Accuracy dont change HOT 2
- what are suggested training parameters for CUB_200_2001? HOT 4
- can't download the pretrained pth HOT 1
- The performance of released model 'mpncovresnet50-15991845.pth' HOT 4
- the result of the combination of mpncov & efficientnet did not meet expectations
- About the implementation of MPNCOV meta layer in pytorch 0.3.1
- About the post-compensation implementation using trace
- Model parameters
- 模型参数下载 HOT 3
- gradcheck for Sqrtm in MPNCOV.py
- where should I put the pre-training model? HOT 1
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