KeyError: 'id' is reported when I run the pretrain.py

[GrayChan04]

excuse me，does anyone know how to deal?
batched_graph.ndata['h'] = ent_embeds[batched_graph.ndata['id']].view(-1, ent_embeds.shape[1]) File "/home/xxxx/anaconda3/envs/renet/lib/python3.6/site-packages/dgl/view.py", line 60, in __getitem__ return self._graph.get_n_repr(self._nodes)[key] KeyError: 'id'
it seems like something wrong with code
batched_graph.ndata['h'] = ent_embeds[batched_graph.ndata['id']].view(-1, ent_embeds.shape[1])
but I don‘t know how to deal with the problem

[GrayChan04]

I change GDELT to ICEWS14, however still the same problem...
according to readme.md, I configuration the environment, but i still CANNOT run the code.
do I miss something?

$ python3 pretrain.py -d ICEWS14 --gpu 0 --dropout 0.5 --n-hidden 200 --lr 1e-3 --max-epochs 20 --batch-size 1024
Using backend: pytorch
Namespace(batch_size=1024, dataset='ICEWS14', dropout=0.5, gpu=0, grad_norm=1.0, lr=0.001, max_epochs=20, maxpool=1, model=3, n_hidden=200, num_k=10, rnn_layers=1, seq_len=10)
start training...
/home/xxxx/RE-Net-cp/Aggregator.py:32: UserWarning: This overload of nonzero is deprecated:
nonzero(Tensor input, *, Tensor out)
Consider using one of the following signatures instead:
nonzero(Tensor input, *, bool as_tuple) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:766.)
num_non_zero = len(torch.nonzero(t_list))
/home/xxxx/RE-Net-cp/utils.py:290: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.
return torch.mean(torch.sum(- soft_targets * logsoftmax(pred), 1))
Traceback (most recent call last):
File "pretrain.py", line 139, in
train(args)
File "pretrain.py", line 92, in train
model.global_emb = model.get_global_emb(train_times_origin, graph_dict)
File "/home/xxxx/RE-Net-cp/global_model.py", line 67, in get_global_emb
emb, _, _ = self.predict(t, graph_dict)
File "/home/xxxx/RE-Net-cp/global_model.py", line 88, in predict
rnn_inp = self.aggregator.predict(t, self.ent_embeds, graph_dict, reverse=reverse)
File "/home/xxxx/RE-Net-cp/Aggregator.py", line 97, in predict
batched_graph.ndata['h'] = ent_embeds[batched_graph.ndata['id']].view(-1, ent_embeds.shape[1])
File "/home/xxxx/anaconda3/envs/renet/lib/python3.6/site-packages/dgl/view.py", line 60, in getitem
return self._graph.get_n_repr(self._nodes)[key]
KeyError: 'id'

[Zhai-Huichen]

batched_graph.ndata['h'] = ent_embeds[batched_graph.ndata['id']].view(-1, ent_embeds.shape[1])
应该是batched_graph在cpu上，用gpu上的东西给它赋值出错了，在出错那一行之前把batched_graph转到gpu里

[GrayChan04]

已经转到gpu了 但是还是报同样的错

[Zhai-Huichen]

你的get_history_graph.py里，方法get_data_with_t有改过吗？
x = data[np.where(data[3] == tim)].copy()改成x = data[np.where(data[:, 3] == tim)].copy()
我用的ICEWS18跑的，14好像有问题

已经转到gpu了 但是还是报同样的错

[Zhai-Huichen]

你的get_history_graph.py里，方法get_data_with_t有改过吗？
x = data[np.where(data[3] == tim)].copy()改成x = data[np.where(data[:, 3] == tim)].copy()
我用的ICEWS18跑的，14好像有问题

[GrayChan04]

你的get_history_graph.py里，方法get_data_with_t有改过吗？ x = data[np.where(data[3] == tim)].copy()改成x = data[np.where(data[:, 3] == tim)].copy() 我用的ICEWS18跑的，14好像有问题

我没有改 这里的代码我觉得没有问题

[WWWindrunner]

你的get_history_graph.py里，方法get_data_with_t有改过吗？ x = data[np.where(data[3] == tim)].copy()改成x = data[np.where(data[:, 3] == tim)].copy() 我用的ICEWS18跑的，14好像有问题

我没有改 这里的代码我觉得没有问题

这个方法你打印过中间结果吗，我之前遇到['id']报错，就是因为这里执行不对，导致batched_graph为空。
我改为了
triples = [[quad[0], quad[1], quad[2]] for quad in data if quad[3] == tim]
就ok了

[MrLiuCC]

你的get_history_graph.py里，方法get_data_with_t有改过吗？ x = data[np.where(data[3] == tim)].copy()改成x = data[np.where(data[:, 3] == tim)].copy() 我用的ICEWS18跑的，14好像有问题

ICEWS14里面没有valid.txt

[MrLiuCC]

请问这部分是这样子改的吗？

[WWWindrunner]

嗯

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[s821220]

请问最后解决了吗？？解决的方案是什么

[Young0222]

我有解决这个问题，请参考：
batched_graph.ndata['h'] = ent_embeds[batched_graph.ndata['id']].view(-1, ent_embeds.shape[1]).to('cpu')
batched_graph = batched_graph.to('cuda:0')
另外，删除move_dgl_to_cuda(batched_graph)这一行