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microsoft / ProDA

Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021)
https://arxiv.org/abs/2101.10979
MIT License
286 stars 44 forks source link

About the usage of your code with PyTorch>=1.6.0 #22

Open LinfengYuan1997 opened 3 years ago

LinfengYuan1997 commented 3 years ago

Thanks for sharing your fantastic work!

I am using your code with PyTorch version >= 1.6.0. And it seems that the operation of F.affine_grid() & F.grid_sample() has been changed leading to the warning :

UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details. "Default grid_sample and affine_grid behavior has changed "

Because I don't know the running Pytorch version of your environment, I am not sure whether I need to change the align_corners argument.

The same issues occur for upsample function

UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and now uses scale_factor directly, instead of relying on the computed output size. If you wish to restore the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. "The default behavior for interpolate/upsample with float scale_factor changed "

Could you please tell me the running version of your PyTorch?

zhangmozhe commented 3 years ago

Hi, we train the model using pytorch 1.5.0. We did not test the code on higher versions.

LinfengYuan1997 commented 3 years ago

Hi, we train the model using pytorch 1.5.0. We did not test the code on higher versions.

So you also met the warning about the "Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details. "Default grid_sample and affine_grid behavior has changed "", and a warning about 'mean' & 'reduction' of cross_entropy_2d(), right?