Comments (2)
@sczhou the issue was that non optimal number of threads per block were used for the backward function of the correlation layer, hence the slow speed.
it is now faster by about 5x.
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mode details in the commit 94b023
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Related Issues (20)
- ValueError (inference) HOT 1
- inference error
- Error when running Inference: forward call is outdated and returns an error when called.
- Flownet2 model for faces HOT 1
- Thanks for this repository! could you please provide the pretrained model for FlowNet2ss or FlowNet2s (lower-case letters, pytorch)? HOT 2
- AttributeError: Module 'time' has no attribute 'clock'
- 想问下如何跑多个文件
- I cannot load the pretrained FlowNetS
- Training with MultiScale loss
- Should I extact "tar" for FlowNet2_checkpoint.pth.tar ?
- Groundtruth of my dataset!!!
- How to achieve the 3D version of correlation layer?
- CUDA error: the provided PTX was compiled with an unsupported toolchain
- start_epoch argument fix
- Error when training Flownet2S HOT 1
- Wrong calculation of EPE HOT 1
- Installation is a nightmare HOT 3
- TypeError: forward() takes 2 positional arguments but 3 were given,flownetc_flow2 = self.flownetc(x)[0].why!!!!
- cuda version HOT 2
- Segmentation fault
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