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根据提示,不支持auto download,需要自行下载到本地 下载的数据为rawdata 然后进行raw_to_mid变换得到middata 所以更新框架,如下: run_edustudio( dataset='ASSIST_1516', cfg_file_name=None, traintpl_cfg_dict={'cls': 'GeneralTrainTPL','device': 'cpu'}, datatpl_cfg_dict={ 'cls': 'KTInterCptUnfoldDataTPL', 'load_data_from': 'rawdata', 'raw2mid_op': 'R2M_ASSIST_1516' }, modeltpl_cfg_dict={'cls': 'AKT',}, evaltpl_cfg_dict={'clses': ['PredictionEvalTPL'],} ) 但是经过测试,1213的数据集可以正常启动训练 但是1516的数据集会出现报错,如下: unique_cpt_seq = df_exer['cpt_seq:token_seq'].explode().unique() TypeError: 'NoneType' object is not subscriptable 分析得:1516数据集rawdata明显缺少信息 以1213的rawdata为例,包含start_time等缺失了的信息 解决方法: 检查datatpl框架,或许可以修改选取项M2C_BuildSeqInterFeats
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意识到是数据模板不匹配的问题,我和上面的同学查看了当前框架下的各个数据模板。但未能找到适配ASSISTment_2015-2016的数据模板。 由于ASSISTment_2015-2016数据集本身栏目较少,经过其r2m协议,只生成了一张inter.csv表,而当前框架下的数据模板似乎都是要求有stu.csv和exer.csv的。
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是否需要添加专门的数据模板,或该数据集项目缺少Knowledge Tracing所需要的基本栏目,暂时废弃(因为看到了R2M_ASSIST1516协议有许多代码被注释了)
感谢反馈!ASSIST1516数据集貌似需要基于ASSIST1213数据集的数据来构建知识点等信息,R2M_ASSIST1516的代码需要重写,后续我们处理下
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根据提示,不支持auto download,需要自行下载到本地
下载的数据为rawdata
然后进行raw_to_mid变换得到middata
所以更新框架,如下:
run_edustudio(
dataset='ASSIST_1516',
cfg_file_name=None,
traintpl_cfg_dict={'cls': 'GeneralTrainTPL','device': 'cpu'},
datatpl_cfg_dict={
'cls': 'KTInterCptUnfoldDataTPL',
'load_data_from': 'rawdata',
'raw2mid_op': 'R2M_ASSIST_1516'
},
modeltpl_cfg_dict={'cls': 'AKT',},
evaltpl_cfg_dict={'clses': ['PredictionEvalTPL'],}
)
但是经过测试,1213的数据集可以正常启动训练
但是1516的数据集会出现报错,如下:
unique_cpt_seq = df_exer['cpt_seq:token_seq'].explode().unique()
TypeError: 'NoneType' object is not subscriptable
分析得:1516数据集rawdata明显缺少信息
以1213的rawdata为例,包含start_time等缺失了的信息
解决方法:
检查datatpl框架,或许可以修改选取项M2C_BuildSeqInterFeats
The text was updated successfully, but these errors were encountered: