Runtime error during 'python train.py'

[ramyaragh]

I successfully ran the word embedding, but while training I get this runtime error. Any suggestions?

File "train.py", line 59, in
cross_entropy, kld, coef = train_step(iteration, args.batch_size, args.use_cuda, args.dropout)
File "/pytorch_RVAE/model/rvae.py", line 104, in train
z=None)
File "/pytorch/torch/lib/python2.7/site-packages/torch/nn/modules/module.py", line 325, in call
result = self.forward(*input, **kwargs)
File "/pytorch_RVAE/model/rvae.py", line 64, in forward
encoder_input = self.embedding(encoder_word_input, encoder_character_input)
File "//pytorch/torch/lib/python2.7/site-packages/torch/nn/modules/module.py", line 325, in call
result = self.forward(*input, **kwargs)
File "/pytorch_RVAE/selfModules/embedding.py", line 47, in forward
character_input = self.TDNN(character_input)
File "/pytorch/torch/lib/python2.7/site-packages/torch/nn/modules/module.py", line 325, in call
result = self.forward(*input, **kwargs)
File "~/pytorch_RVAE/selfModules/tdnn.py", line 42, in forward
xs = [x.max(2)[0].squeeze(2) for x in xs]
RuntimeError: dimension out of range (expected to be in range of [-2, 1], but got 2)

[ruotianluo]

delete .squeeze(2)

[ramyaragh]

Does not seem to help

preprocessed data was found and loaded
Traceback (most recent call last):
File "train.py", line 59, in
cross_entropy, kld, coef = train_step(iteration, args.batch_size, args.use_cuda, args.dropout)
File "/pytorch_RVAE/model/rvae.py", line 104, in train
z=None)
File "/anaconda/lib/python3.5/site-packages/torch/nn/modules/module.py", line 325, in call
result = self.forward(*input, **kwargs)
File "/pytorch_RVAE/model/rvae.py", line 66, in forward
context = self.encoder(encoder_input)
File "/anaconda/lib/python3.5/site-packages/torch/nn/modules/module.py", line 325, in call
result = self.forward(*input, **kwargs)
File "/pytorch_RVAE/model/encoder.py", line 35, in forward
assert parameters_allocation_check(self),
File "/pytorch_RVAE/utils/functional.py", line 15, in parameters_allocation_check
return fold(f_and, parameters, True) or not fold(f_or, parameters, False)
File "/pytorch_RVAE/utils/functional.py", line 2, in fold
return a if (len(l) == 0) else fold(f, l[1:], f(a, l[0]))
File "/pytorch_RVAE/utils/functional.py", line 2, in fold
return a if (len(l) == 0) else fold(f, l[1:], f(a, l[0]))
File "~/pytorch_RVAE/utils/functional.py", line 6, in f_and
return x and y
File "/anaconda/lib/python3.5/site-packages/torch/autograd/variable.py", line 125, in bool
torch.typename(self.data) + " is ambiguous")
RuntimeError: bool value of Variable objects containing non-empty torch.FloatTensor is ambiguous

[ruotianluo]

That's a different error. What I did for this was just always return True in parameters_allocation_check function.

[SeekPoint]

@ruotianluo which version of pytorch do you working on?