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I followed the readme to run the training scripts And I could run the
bash scripts/run.sh --train
it could train and predict but in the last epoch after saving and loading the best kept it do a more evaluation and will have the following error
Moment Retrieval loss: 0.0235 Step Captioning loss: 0.6253 Saved ./checkpoints/hirest_joint_model/moment_retrieval_epoch_049.json Saved ./checkpoints/hirest_joint_model/moment_segmentation_epoch_049.json Saved ./checkpoints/hirest_joint_model/step_captioning_epoch_049.json Model saved at ./checkpoints/hirest_joint_model/LAST.pth Best Epoch: 5 Model loaded from ./checkpoints/hirest_joint_model/BEST Moment_retrieval Prediction: 0%| Moment_retrieval Prediction: 1%|▎ Moment_retrieval Prediction: 4%|██ Moment_retrieval Prediction: 6%|███▍ Moment_retrieval Prediction: 10%|█████ Moment_retrieval Prediction: 12%|██████▍ Moment_retrieval Prediction: 15%|███████▊ Moment_retrieval Prediction: 17%|█████████▏ Moment_retrieval Prediction: 20%|██████████▌ Moment_retrieval Prediction: 22%|███████████▉ Moment_retrieval Prediction: 25%|█████████████▎ Moment_retrieval Prediction: 28%|██████████████▉ Moment_retrieval Prediction: 31%|████████████████▋ Moment_retrieval Prediction: 35%|██████████████████▎ Moment_retrieval Prediction: 38%|████████████████████ Moment_retrieval Prediction: 41%|█████████████████████▋ Moment_retrieval Prediction: 44%|███████████████████████▍ Moment_retrieval Prediction: 47%|█████████████████████████▏ Moment_retrieval Prediction: 50%|██████████████████████████▌ Moment_retrieval Prediction: 53%|███████████████████████████▊ Moment_retrieval Prediction: 55%|█████████████████████████████▏ Moment_retrieval Prediction: 58%|██████████████████████████████▌ Moment_retrieval Prediction: 60%|███████████████████████████████▉ Moment_retrieval Prediction: 63%|█████████████████████████████████▎ Moment_retrieval Prediction: 66%|██████████████████████████████████▎ Moment_retrieval Prediction: 69%|████████████████████████████████████ Moment_retrieval Prediction: 72%|█████████████████████████████████████▋ Moment_retrieval Prediction: 76%|███████████████████████████████████████▎ Moment_retrieval Prediction: 79%|█████████████████████████████████████████ Moment_retrieval Prediction: 82%|██████████████████████████████████████████▋ Moment_retrieval Prediction: 85%|████████████████████████████████████████████▎ Moment_retrieval Prediction: 88%|██████████████████████████████████████████████Moment_retrieval Prediction: 92%|██████████████████████████████████████████████Moment_retrieval Prediction: 95%|██████████████████████████████████████████████Moment_retrieval Prediction: 98%|██████████████████████████████████████████████Moment_retrieval Prediction: 100%|████████████████████████████████████████████████████| 156/156 [00:04<00:00, 35.54it/s] moment_segmentation <torch.utils.data.dataloader.DataLoader object at 0x7f9a56397a30> Moment_segmentation Prediction: 0it [00:00, ?it/s] Traceback (most recent call last): File "/hy-tmp/HiREST/run.py", line 903, in <module> main_worker(0, args) File "/hy-tmp/HiREST/run.py", line 854, in main_worker trainer.train() File "/hy-tmp/HiREST/run.py", line 497, in train test_moment_segmentation_results = self.evaluate(self.test_moment_segmentation_loader, has_target=False) File "/hy-tmp/HiREST/run.py", line 840, in evaluate results = self.predict(loader, has_target=has_target) File "/hy-tmp/HiREST/run.py", line 687, in predict assert len(results['tasks']) == len(results['video_fnames']) == len(results['prompts']) \ KeyError: 'video_fnames'
it seems like there is a closed issue similar to mine. I have tried that method, but it didn't work
The text was updated successfully, but these errors were encountered:
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I followed the readme to run the training scripts
And I could run the
it could train and predict but in the last epoch after saving and loading the best kept
it do a more evaluation and will have the following error
it seems like there is a closed issue similar to mine.
I have tried that method, but it didn't work
The text was updated successfully, but these errors were encountered: