Bug when I try cifar100

[heng-yin]

Thanks for your work.
When I try your code on CIFAR100, I got this error and I dont know how to slove it.
Due to ImageNet's huge number of images, I can only do this.
PLS help.

Torch version: 1.7.1 Namespace(alpha=1, augment_epoch=10, beta=1.17, lr=0.001, train_epoch=20) Model parameters: 151,277,313 Input resolution: 224 Context length: 77 Vocab size: 49408 Load data finished. start getting text features. finish getting text features. start getting image features start saving training image features Augment time: 0 / 10 3%|▉ | 6/196 [00:03<01:45, 1.81it/s] Traceback (most recent call last): File "main.py", line 487, in <module> main() File "main.py", line 244, in main for i, (images, target) in enumerate(tqdm(train_loader)): File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/tqdm/std.py", line 1180, in __iter__ for obj in iterable: File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 435, in __next__ data = self._next_data() File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data data = self._dataset_fetcher.fetch(index) # may raise StopIteration File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/yh/.conda/envs/prompt/lib/python3.6/site-packages/torchvision/datasets/cifar.py", line 113, in __getitem__ img, target = self.data[index], self.targets[index] IndexError: list index out of range [1]+ Killed python main.py

[gaopengcuhk]

We will add scripts for new datasets in a few weeks. Stay tuned.

[ZrrSkywalker]

@heng-yin Thanks for your great patience!
We have release the code for other datasets in the repo. Maybe you can follow their configs to implement on CIFAR100.