Comments (4)
315930399
commented on June 25, 2024
dkt模型测试时不会出现该问题
from pykt-toolkit.
315930399
commented on June 25, 2024
Namespace(atkt_pad=0, save_dir='saved_model/peiyou_akt_qid_saved_model_3407_0_0.2_256_512_8_4_0.0001_0_1', test_filename='pykt_test.csv', train_ratio=0.5, use_pred=0, use_wandb=0)
Start predicting model: akt, embtype: qid, save_dir: saved_model/peiyou_akt_qid_saved_model_3407_0_0.2_256_512_8_4_0.0001_0_1, dataset_name: peiyou
model_config: {'dropout': 0.2, 'd_model': 256, 'd_ff': 512, 'num_attn_heads': 8, 'n_blocks': 4}
data_config: {'dpath': '../data/peiyou', 'num_q': 7652, 'num_c': 865, 'input_type': ['questions', 'concepts'], 'max_concepts': 6, 'min_seq_len': 3, 'maxlen': 200, 'emb_path': '', 'train_valid_file': 'train_valid_sequences.csv', 'folds': [0, 1, 2, 3, 4]}
Start predict use_pred: False, ratio: 0.5...
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Traceback (most recent call last):
File "wandb_eval.py", line 74, in <module>
main(params)
File "wandb_eval.py", line 55, in main
dfinal = evaluate_splitpred_question(model, data_config, testf, model_name, save_test_path, use_pred, ratio, atkt_pad)
File "/media/sda2/yueying/pykt-toolkit/pykt/models/evaluate_model.py", line 611, in evaluate_splitpred_question
qidxs, ctrues, cpreds = predict_each_group2(dtotal, dcur, dforget, curdforget, is_repeat, qidx, uid, idx, model_name, model, t, end, fout, atkt_pad)
File "/media/sda2/yueying/pykt-toolkit/pykt/models/evaluate_model.py", line 1034, in predict_each_group2
y, reg_loss = model(ccc.long(), ccr.long(), ccq.long())
File "/media/sda1/yueying/miniconda3/pkgs/envs/pykt/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/media/sda2/yueying/pykt-toolkit/pykt/models/akt.py", line 108, in forward
d_output = self.model(q_embed_data, qa_embed_data, pid_embed_data)
File "/media/sda1/yueying/miniconda3/pkgs/envs/pykt/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/media/sda2/yueying/pykt-toolkit/pykt/models/akt.py", line 158, in forward
y = block(mask=1, query=y, key=y, values=y, pdiff=pid_embed_data) # yt^
File "/media/sda1/yueying/miniconda3/pkgs/envs/pykt/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/media/sda2/yueying/pykt-toolkit/pykt/models/akt.py", line 213, in forward
src_mask = (torch.from_numpy(nopeek_mask) == 0).to(device)
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
这是在cuda上运行时的报错信息，一楼的是在cpu上
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Liu-lqq
commented on June 25, 2024
该问题是因为比赛测试集待预测部分response为-1，导致编码时超出范围（0，1）所报错，已修复，可重新拉取最新代码尝试～
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315930399
commented on June 25, 2024
可以正常运行了，感谢！
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Related Issues (20)
- 关于一题多知识点的数据集 HOT 1
- 关于运行多个模型都出现‘RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! ’的报错
- 关于Hyper parameter tunning results的问题 HOT 2
- The config file is not in the direct directory of save_model, but in the newly generated file under save_model after I trained the model.
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- SAINT model has incorrect defaults HOT 2
- Incredibly slow training / randomly stuck in when training wandb_saint_train.py on assist2012
- Could you please provide guidance on obtaining the correct datasets? HOT 6
- Help on setting up pykt HOT 1
- 请问后续是否考虑添加 MAN 模型，这个模型AUC和ACC非常高，而且有开源 HOT 1
- train_model.py中函数model_forward关于dkvmn的问题
- texts for questions, knowledge components, and students answers in the datasets
- AKT Information Leakage HOT 3
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