When finetuning, len(train_loader)==0, ZeroDivisionError: integer division or modulo by zero in tasks/pretrain.py

I want to finetune the InternVideo2-Stage2_1B-224p-f4 on activitynet. I adjust the data in data.py.
My data is:

available_corpus["anet_ret_val"] = dict( anno_path=".../ActivityNet/anno_downstream/anet_ret_val.json", data_root=".../ActivityNet", media_type="video", is_paragraph_retrieval=True, max_txt_l = 150 ) available_corpus["anet_ret_train"] = dict( anno_path=".../ActivityNet/anno_downstream/anet_ret_train.json", data_root=".../ActivityNet", media_type="video", is_paragraph_retrieval=True, max_txt_l = 150 )

anet_ret_train.json data example:
[
{
"video": ".../ActivityNet/videos_images/v_QOlSCBRmfWY.mp4",
"caption": "A young woman is seen standing in a room and leads into her dancing.",
}
......
]

In pretrain.py I got len(train_loaders)=1, but len(train_loader)=0. So I got ZeroDivisionError: integer division or modulo by zero.
I carefully check the frame extraction, I found the frame and video are processed correctly. But MetaLoader has 1 dataloaders, 0 batches in total
Was it because I've done incorrect setting of some parameters?

Start with the ActivityNet corpus settings in data.py and follow their use into tasks/pretrain.py, focusing on MetaLoader and train_loader. Check how the supplied annotation and loader configuration produces the reported batch count. Done means the configured training loader contains batches and finetuning no longer reaches the division-by-zero error.