Successfully inference, but unable to train

[kido1412y2y]

Hello author, I encountered this issue while training the model. Could you kindly provide me with some advice? Thank you very much.

(vac) user2@com:~/data/VAC_CSLR-main$ python main.py --work-dir ./work_dir/vac/ --config ./configs/baseline.yaml --device 0
Loading model
/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
f"The parameter '{pretrained_param}' is deprecated since 0.13 and may be removed in the future, "
/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=ResNet18_Weights.IMAGENET1K_V1. You can also use weights=ResNet18_Weights.DEFAULT to get the most up-to-date weights.
warnings.warn(msg)
Loading model finished.
Loading data
train 5671
Apply training transform.

train 5671
Apply testing transform.

dev 540
Apply testing transform.

test 629
Apply testing transform.

Loading data finished.
.git does not exist in current dir
[ Wed Jul 19 21:43:36 2023 ] Parameters:
{'work_dir': './work_dir/vac/', 'config': './configs/baseline.yaml', 'random_fix': True, 'device': '0', 'phase': 'train', 'save_interval': 5, 'random_seed': 0, 'eval_interval': 1, 'print_log': True, 'log_interval': 50, 'evaluate_tool': 'sclite', 'feeder': 'dataset.dataloader_video.BaseFeeder', 'dataset': 'phoenix14', 'dataset_info': {'dataset_root': './dataset/phoenix2014/phoenix-2014-multisigner', 'dict_path': './preprocess/phoenix2014/gloss_dict.npy', 'evaluation_dir': './evaluation/slr_eval', 'evaluation_prefix': 'phoenix2014-groundtruth'}, 'num_worker': 0, 'feeder_args': {'mode': 'test', 'datatype': 'video', 'num_gloss': -1, 'drop_ratio': 1.0, 'prefix': './dataset/phoenix2014/phoenix-2014-multisigner', 'transform_mode': False}, 'model': 'slr_network.SLRModel', 'model_args': {'num_classes': 1296, 'c2d_type': 'resnet18', 'conv_type': 2, 'use_bn': 1, 'share_classifier': False, 'weight_norm': False}, 'load_weights': None, 'load_checkpoints': None, 'decode_mode': 'beam', 'ignore_weights': [], 'batch_size': 2, 'test_batch_size': 4, 'loss_weights': {'SeqCTC': 1.0}, 'optimizer_args': {'optimizer': 'Adam', 'base_lr': 0.0001, 'step': [20, 35], 'learning_ratio': 1, 'weight_decay': 0.0001, 'start_epoch': 0, 'nesterov': False}, 'num_epoch': 40}

0%| | 0/2835 [00:00<?, ?it/s]
Traceback (most recent call last):
File "main.py", line 211, in
processor.start()
File "main.py", line 45, in start
self.device, epoch, self.recoder)
File "/home/user2/data/VAC_CSLR-main/seq_scripts.py", line 18, in seq_train
for batch_idx, data in enumerate(tqdm(loader)):
File "/opt/anaconda3/envs/vac/lib/python3.7/site-packages/tqdm/std.py", line 1178, in iter
for obj in iterable:
File "/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 628, in next
data = self._next_data()
File "/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/opt/anaconda3/envs/vac/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/user2/data/VAC_CSLR-main/dataset/dataloader_video.py", line 47, in getitem
input_data, label = self.normalize(input_data, label)
File "/home/user2/data/VAC_CSLR-main/dataset/dataloader_video.py", line 78, in normalize
video, label = self.data_aug(video, label, file_id)
File "/home/user2/data/VAC_CSLR-main/utils/video_augmentation.py", line 24, in call
image = t(image)
File "/home/user2/data/VAC_CSLR-main/utils/video_augmentation.py", line 119, in call
if isinstance(clip[0], np.ndarray):
IndexError: list index out of range

[ycmin95]

You can check here whether the data are localized.

[kido1412y2y]

You can check here whether the data are localized.

Hello, I have checked it and it is indeed empty. I found some deficiencies after data preprocessing, and after re preprocessing, the code ran smoothly. But the Dev WER after training is 40.30%. This is the corresponding log. Can you give me some advice? thanks.
dev.txt
log.txt

[ycmin95]

Duplicate of #7.