xuuuluuu / position-aware-tagging-for-aste Goto Github PK

Start Training...
toal num of entity:  249
total num of prediction:  157
Dev  --  (Precision=57.32%, Recall=36.14%, FScore=44.33%) 	Time=1096.56s
�[31mSave the best model to �[0m best_model.pt
toal num of entity:  485
total num of prediction:  298
�[31mTest -- �[0m (Precision=52.68%, Recall=32.37%, FScore=40.10%) 	Time=2766.03s
�[33mIteration �[0m 0 : Obj= 4704.674016952515 	Time=5640.75s

(JET) PS C:\Users\sp\.conda\envs\JET\Position-Aware-Tagging-for-ASTE> python jet_o.py
# of original triplets:  1460
# of triplets for current setup:  601
# of original triplets:  346
# of triplets for current setup:  346
# of original triplets:  543
# of triplets for current setup:  543
Map:  {'<START>': 0, 'O': 1, 's': 2, 'b': 3, 'e': 4, 'i': 5, '<STOP>': 6}
vocab2id:  2861
vocab size:  2861
reading the pretraing embedding: data/glove.840B.300d.txt
[Info] Use the pretrained word embedding to initialize: 2861 x 300
['<START>', 'O', 's', 'b', 'e', 'i', '<STOP>']
Capacity successfully set to: [83 10  3  2  3  3  3]
The max size:  83
#instances= 487
Touching ...
..........
Toucing Completes taking  81.15600061416626  seconds.
[] tensor(-inf)
['O', '<START>'] tensor(0.5778)
['O', 'O'] tensor(1.5546)
['s', 'O'] tensor(-0.3605)
['O', 's'] tensor(-1.1066)
['<STOP>', 'O'] tensor(-1.2451)
['s', '<START>'] tensor(0.3075)
['b', '<START>'] tensor(2.9103)
['i', '<START>'] tensor(-1.8127)
['O', 'b'] tensor(-0.1694)
['O', 'e'] tensor(-0.6851)
['s', 's'] tensor(-0.1793)
['s', 'e'] tensor(0.5894)
['b', 'O'] tensor(0.6963)
['b', 's'] tensor(-0.8922)
['b', 'e'] tensor(0.0064)
['e', 'b'] tensor(-0.8084)
['e', 'i'] tensor(-0.1822)
['i', 'b'] tensor(-0.5260)
['i', 'i'] tensor(-1.2019)
['<STOP>', 's'] tensor(1.4376)
['<STOP>', 'e'] tensor(1.5863)
['e', 'O'] tensor(0.5885)
Start Training...
Traceback (most recent call last):
  File "jet_o.py", line 138, in <module>
    model.learn(train_insts, num_iter, dev_insts, test_insts, optimizer_str, batch_size)
  File "C:\Users\sp\.conda\envs\JET\Position-Aware-Tagging-for-ASTE\triplet\hypergraph\NetworkModel.py", line 257, in learn
    label_score = self.forward(gold_network)
  File "C:\Users\sp\.conda\envs\JET\Position-Aware-Tagging-for-ASTE\triplet\hypergraph\NetworkModel.py", line 409, in forward
    return network.inside()
  File "C:\Users\sp\.conda\envs\JET\Position-Aware-Tagging-for-ASTE\triplet\hypergraph\TensorNetwork.py", line 59, in inside
    for_expr = torch.sum(torch.take(self.inside_scores, childrens_stage), 2)  # this line is same as the above two lines
RuntimeError: Expected object of scalar type Long but got scalar type Int for argument #2 'index' in call to _th_take