Comments (2)
head_label = torch.zeros(len(data), self.num_ent)
tail_label = torch.zeros(len(data), self.num_ent)
请问label设置成[128,14541]的话,KBAT的解码器不是convKB吗,最后如何eval的?
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在filter protocol情况下,label用来标记当前三元组中所有正确的头实体或尾实体。
目前NeuralKG支持link predication task,详细的eval过程请参照eval_task模块下的link_prediction.py
此外您也可以通过Translating Embeddings for Modeling Multi-relational Data论文了解模型是如何进行链接预测的。
希望这可以帮到您。
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Related Issues (20)
- 关于自定义训练、测试模块的问题 HOT 4
- 关于ConvE模型性能的问题 HOT 1
- 怎么提取embedding呢? HOT 2
- Trying CompGCN on pharmkg dataset HOT 3
- demo问题,验证结果,杭州市rank为9 与 readme中不同? HOT 2
- NeuralKG中是否提供与原始论文中一样的TransE模型? HOT 1
- 如何在训练过程中进行调试和修改? HOT 1
- 按照指示配置完所需库,但无法执行demo.py HOT 10
- 超参数优化 HOT 6
- 您好我是一名初学者,请问我在colab上使用自己的数据训练完TransH模型后,如何获得相应的embedding?文档中并无详细描述,感谢您的帮助 HOT 1
- use_weight的功能 HOT 2
- 运行demo报错 HOT 2
- 保存预测三元组 HOT 1
- where is the parameter of epoch HOT 3
- colab示例demo无法运行 HOT 2
- can‘t run main.py successfully HOT 1
- 模型是否存在early stop HOT 1
- 你好,这个会有jvm api 出来吗?例如Scala api,和pytorch能配合使用吗 HOT 1
- lmdb.MemoryError: dataset/CCKS_train_subgraph: Cannot allocate memory HOT 1
- windows平台上CPU占用和磁盘读写异常 HOT 1
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