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PyTorch implementation of the CVPR 2019 paper “Pyramid Feature Attention Network for Saliency Detection”

Results 5 PyTorch-Pyramid-Feature-Attention-Network-for-Saliency-Detection issues
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Hi,Sairajk. Your work is helpful to me. However, the following error pops up during training the model.Thus, the saved model does not achieve the desired effect. ![connect ECONNREFUSED报错](https://user-images.githubusercontent.com/55178320/171330455-ed5e876c-65d9-41b5-8b45-a6aff3f8b622.png) Based on...

Hi, I got the problem, I can begin trainging the code. But while run epoch=2, it show this problem and stop to train. File "train.py", line 212, in trainer.train() File...

I have made some changes to your scripts so it can run on Colab. And I have fix some bugs, changed the name of the workers to threads, and made...

torch.save(mod_chkpt, self.model_path + 'weights/best-model_epoch-{:03}_mae-{:.4f}_loss-{:.4f}.pth'.format(epoch, best_test_mae, te_avg_loss)) while self.model_path = args.base_save_path + '/alph-{}_wbce_w0-{}_w1-{}'.format(str(self.alpha_sal), str(self.wbce_w0), str(self.wbce_w1)) you are supposed to plus a '/' in self.model_path = args.base_save_path + '/alph-{}_wbce_w0-{}_w1-{}/'.

Bumps [torch](https://github.com/pytorch/pytorch) from 1.1.0 to 2.2.0. Release notes Sourced from torch's releases. PyTorch 2.2: FlashAttention-v2, AOTInductor PyTorch 2.2 Release Notes Highlights Backwards Incompatible Changes Deprecations New Features Improvements Bug fixes...

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