kevinkwl / aoareader Goto Github PK

Traceback (most recent call last):
File "train.py", line 224, in
main()
File "train.py", line 221, in main
trainModel(model, train_dataset, valid_dataset, optimizer)
File "train.py", line 152, in trainModel
train_loss, train_acc = trainEpoch(epoch)
File "train.py", line 117, in trainEpoch
pred_answers, answer_probs = model(batch_docs, batch_docs_len, doc_mask, batch_querys, batch_querys_len, query_mask,answers=batch_answers, candidates=candidates)
File "-/ulti3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 224, in call
result = self.forward(*input, **kwargs)
File "-/-/a-o-a/AoAReader/aoareader/AoAReader.py", line 91, in forward
alpha = softmax_mask(M, M_mask, axis=1)
File "-/-/a-o-a/AoAReader/aoareader/AoAReader.py", line 22, in softmax_mask
shift = shift.expand_as(input).cuda()
File "-/ulti3/lib/python3.5/site-packages/torch/autograd/variable.py", line 725, in expand_as
return Expand.apply(self, (tensor.size(),))
File "-/ulti3/lib/python3.5/site-packages/torch/autograd/_functions/tensor.py", line 111, in forward
result = i.expand(*new_size)
RuntimeError: The expanded size of the tensor (832) must match the existing size (64) at non-singleton dimension 1. at /pytorch/torch/lib/THC/generic/THCTensor.c:323

python3
Python 3.5.2 (default, Nov 17 2016, 17:05:23)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.

import torch
torch.version
'0.2.0+8262920'

mldl@mldlUB1604:~/ub16_prj/AoAReader$ python3 train.py 2>&1 | tee yknote---train---log
Namespace(batch_size=32, dict='data/dict.pt', dropout=0.1, embed_size=384, epochs=13, gpu=0, gru_size=384, learning_rate=0.001, log_interval=50, save_model='model', start_epoch=1, train_from='', traindata='data/train.txt.pt', validdata='data/dev.txt.pt', weight_decay=0.0001)
Loading dictrionary from data/dict.pt
Loading train data from data/train.txt.pt
Loading valid data from data/dev.txt.pt

• vocabulary size = 53183
• number of training samples. 120769
• maximum batch size. 32
  Building model...
• number of parameters: 22196352
  AoAReader (
  (embedding): Embedding(53183, 384, padding_idx=0)
  (gru): GRU(384, 384, batch_first=True, dropout=0.1, bidirectional=True)
  )

Epoch 1, 1/ 3775; avg loss: 5.61; acc: 25.00; 16 s elapsed
Epoch 1, 51/ 3775; avg loss: 4.83; acc: 29.38; 879 s elapsed
Epoch 1, 101/ 3775; avg loss: 3.99; acc: 27.44; 1757 s elapsed
Traceback (most recent call last):
File "train.py", line 224, in
main()
File "train.py", line 221, in main
trainModel(model, train_dataset, valid_dataset, optimizer)
File "train.py", line 152, in trainModel
train_loss, train_acc = trainEpoch(epoch)
File "train.py", line 121, in trainEpoch
loss.backward()
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/variable.py", line 156, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, retain_variables)
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/init.py", line 98, in backward
variables, grad_variables, retain_graph)
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/function.py", line 91, in apply
return self._forward_cls.backward(self, *args)
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/_functions/reduce.py", line 26, in backward
return grad_output.expand(ctx.input_size), None, None
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/variable.py", line 722, in expand
return Expand.apply(self, sizes)
File "/usr/local/lib/python3.5/dist-packages/torch/autograd/_functions/tensor.py", line 111, in forward
result = i.expand(*new_size)
RuntimeError: invalid argument 1: the number of sizes provided must be greater or equal to the number of dimensions in the tensor at /home/mldl/pytorch/torch/lib/THC/generic/THCTensor.c:309
mldl@mldlUB1604:~/ub16_prj/AoAReader$