zjunlp / knn-kg Goto Github PK

Traceback (most recent call last):
File "main.py", line 141, in
main()
File "main.py", line 123, in main
trainer.fit(lit_model, datamodule=data)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 458, in fit
self._run(model)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 756, in _run
self.dispatch()
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 797, in dispatch
self.accelerator.start_training(self)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 96, in start_training
self.training_type_plugin.start_training(trainer)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 144, in start_training
self._results = trainer.run_stage()
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 807, in run_stage
return self.run_train()
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 869, in run_train
self.train_loop.run_training_epoch()
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 490, in run_training_epoch
batch_output = self.run_training_batch(batch, batch_idx, dataloader_idx)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 731, in run_training_batch
self.optimizer_step(optimizer, opt_idx, batch_idx, train_step_and_backward_closure)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 432, in optimizer_step
using_lbfgs=is_lbfgs,
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/core/lightning.py", line 1403, in optimizer_step
optimizer.step(closure=optimizer_closure)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/core/optimizer.py", line 214, in step
self.__optimizer_step(*args, closure=closure, profiler_name=profiler_name, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/core/optimizer.py", line 134, in __optimizer_step
trainer.accelerator.optimizer_step(optimizer, self._optimizer_idx, lambda_closure=closure, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 329, in optimizer_step
self.run_optimizer_step(optimizer, opt_idx, lambda_closure, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 336, in run_optimizer_step
self.training_type_plugin.optimizer_step(optimizer, lambda_closure=lambda_closure, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 193, in optimizer_step
optimizer.step(closure=lambda_closure, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/torch/optim/lr_scheduler.py", line 65, in wrapper
return wrapped(*args, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/torch/optim/optimizer.py", line 89, in wrapper
return func(*args, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/torch/optim/adamw.py", line 65, in step
loss = closure()
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 726, in train_step_and_backward_closure
split_batch, batch_idx, opt_idx, optimizer, self.trainer.hiddens
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 814, in training_step_and_backward
result = self.training_step(split_batch, batch_idx, opt_idx, hiddens)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 280, in training_step
training_step_output = self.trainer.accelerator.training_step(args)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 204, in training_step
return self.training_type_plugin.training_step(*args)
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 155, in training_step
return self.lightning_module.training_step(*args, **kwargs)
File "/rainbow/weiguoying/code/KNN-KG/lit_models/transformer.py", line 74, in training_step
logits = self.model(**batch, return_dict=True).logits
File "/rainbow/miniconda3/envs/knnkg/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
TypeError: forward() got an unexpected keyword argument 'en'

你好，我在复现您KNN代码中遇到一些问题，麻烦您看一下可以吗。就是第三阶段跑的是training里面version几 ，我这里有好几个version 而且每个version下还有多个文件

您好，可以麻烦您补充一下文件吗

Dear professor,
Thank you for reading my message.

I have read your paper, which name is Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings, and I already run your code, and got result similar with yours.

My question is about how to get the output like table 4 of the part 3.4 analysis. I do not know how to output entities with their probability like table 4 shown.

Could your provide some ideas and method about my question?

If you could provide more specific information, I would be well grateful. Looking forward to your reply.

Kind regards,
Doupi

pytorch_lightning.utilities.exceptions.MisconfigurationException: You requested GPUs: [1]
But your machine only has: []
这是什么导致的？

Would you mind open-sourcing the code drawn by Figure 6?

Can you share the plot code ?

您好，又缺文件了
我感觉可能test的也没有
还有WN18RR可能文件也不全
谢谢

您好，最近在阅读您的论文，运行代码时发现在进行Entity Embedding Initialization时，Epoch 0 进行到50%的时候，出现KeyError: 'label'，查看了代码后发现是data_module.py的DataCollatorForSeq2Seq类的__init__方法中features处理问题，当lables不存在的时候会产生错误，我尝试了多种方法，依然无法运行，想询问您如何去解决这个问题

Could you please tell me how to obtain the description file of entities? It seems that the download FB15k-237 zip file does not have this description file.