Dataset and Code Error

[good-demo]

Thank you for sharing your work，i am currently facing issues with the dataset
About SoftCLT + TS2Vec Semi-supervised Classification
The data preparation was not specified，is there a relevant script to handle this segmented data？

Transfer Learning
Source dataset: SleepEEG this data preparation was also not specified

[good-demo]

Use SleepEDF as Source dataset
Traceback (most recent call last):
File "main_pretrain_TL.py", line 102, in
Trainer_wo_DTW_wo_val(args, model, temporal_contr_model, model_optimizer,
File "/mnt/share/yxd/softclt-main/softclt_catcc/trainer/trainer.py", line 228, in Trainer_wo_DTW_wo_val
train_loss, train_acc = model_train_wo_DTW(dist_func, args.dist, args.tau_inst, model, temporal_contr_model, model_optimizer, temp_cont_optimizer,
File "/mnt/share/yxd/softclt-main/softclt_catcc/trainer/train_utils.py", line 123, in model_train_wo_DTW
_, _, features1, features2, final_loss = model(aug1, aug2, dist_mat_batch)
File "/mnt/share/yxd/envs/order/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in call_impl
return forward_call(*args, **kwargs)
File "/mnt/share/yxd/softclt-main/softclt_catcc/models/model.py", line 63, in forward
temporal_loss += (1-self.lambda) * temp_CL_soft(aug1, aug2, timelag_L, timelag_R)
File "/mnt/share/yxd/softclt-main/softclt_catcc/models/soft_losses.py", line 47, in temp_CL_soft
loss = torch.sum(logits[:,t]*timelag_L)
RuntimeError: The size of tensor a (63) must match the size of tensor b (3001) at non-singleton dimension 2

[good-demo]

Is it due to incorrect data or code errors

[WUT-YYN]

使用 SleepEDF 作为源数据 集回溯（最近一次调用最后一次）： 文件“main_pretrain_TL.py”，第 102 行，在 Trainer_wo_DTW_wo_val(args, model, temporary_contr_model, model_optimizer, 文件“/mnt/share/yxd/softclt-main/softclt_catcc/trainer/trainer.py”，第 228 行，在 Trainer_wo_DTW_wo_val train_loss, train_acc = model_train_wo_DTW(dist_func, args.dist, args.tau_inst, model, temporary_contr_model, model_optimizer, temp_cont_optimizer, 文件“/mnt/share/yxd/softclt-main/softclt_catcc/trainer/train_utils.py”，第 123 行，在 model_train_wo_DTW _, , features1, features2, final_loss =模型（aug1、aug2、dist_mat_batch） 文件“/mnt/share/yxd/envs/order/lib/python3.8/site-packages/torch/nn/modules/module.py”，第 1501 行，在_call_impl中 返回 forward_call（*args，**kwargs） 文件“/mnt/share/yxd/softclt-main/softclt_catcc/models/model.py”，第 63 行，在前向 temporary_loss +=（1-self.lambda）* temp_CL_soft（aug1、aug2、timelag_L、timelag_R） 文件“/mnt/share/yxd/softclt-main/softclt_catcc/models/soft_losses.py”，第 47 行，在 temp_CL_soft 中 loss = torch.sum（logits[:,t]*timelag_L） RuntimeError：大小张量 a (63) 必须与非单维 2 上的张量 b (3001) 的大小匹配

I also encountered this problem, has it been solved? Thank you