I am seeing the same error. checked the data and lengths. all are bigger than zero.
ipdb> embeddings
Variable containing:
( 0  ,.,.) = 
  9.5425e-02 -9.9179e-02  1.0707e-02  ...  -7.6814e-03  1.6964e-02 -5.6413e-02
  2.3778e-02  9.7818e-02  6.4073e-02  ...   2.8708e-02 -6.0741e-02 -5.7502e-02
  8.3500e-02 -1.6935e-02  4.1593e-02  ...  -6.4133e-02  9.3276e-02  7.6222e-02
                 ...                   ⋱                   ...                
  8.3500e-02 -1.6935e-02  4.1593e-02  ...  -6.4133e-02  9.3276e-02  7.6222e-02
  1.7874e-02  6.9051e-02 -1.9213e-02  ...  -4.9683e-02  3.5582e-02 -7.3659e-03
  1.1075e-02  3.9153e-02 -8.9664e-02  ...  -5.0775e-03  2.4475e-02 -2.7899e-02

( 1  ,.,.) = 
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
                 ...                   ⋱                   ...                
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02

( 2  ,.,.) = 
  4.7567e-02 -9.2625e-02 -6.5104e-02  ...   5.4529e-03 -2.8097e-02  1.6113e-02
  7.5976e-03  6.8720e-02  6.1340e-02  ...  -3.9622e-02 -2.3815e-02 -2.0370e-02
  3.9998e-02  7.2032e-02 -1.1872e-02  ...   2.6354e-02  5.3474e-02  3.4333e-02
                 ...                   ⋱                   ...                
  3.9998e-02  7.2032e-02 -1.1872e-02  ...   2.6354e-02  5.3474e-02  3.4333e-02
  6.4244e-03  1.4605e-02  5.8494e-02  ...  -3.7417e-02  5.5668e-02 -8.0501e-02
  4.7567e-02 -9.2625e-02 -6.5104e-02  ...   5.4529e-03 -2.8097e-02  1.6113e-02
 ... 

(1428,.,.) = 
  3.1046e-02  1.8106e-02  1.9945e-02  ...   8.2633e-02  8.4120e-02 -9.7189e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
                 ...                   ⋱                   ...                
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02

(1429,.,.) = 
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
                 ...                   ⋱                   ...                
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02

(1430,.,.) = 
  8.3446e-02 -9.9876e-02 -4.1541e-02  ...  -3.1610e-02  6.2645e-03 -5.3521e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
                 ...                   ⋱                   ...                
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
 -9.1356e-02 -7.9375e-02 -1.0256e-02  ...  -7.6632e-02  8.7251e-02  8.0002e-02
[torch.cuda.FloatTensor of size 1431x20x200 (GPU 0)]

ipdb> input_lengths
Variable containing:
 1431
 1215
  936
  918
  918
  891
  873
  855
  855
  819
  810
  801
  792
  765
  747
  729
  720
  711
  693
  693
[torch.LongTensor of size 20]

ipdb> c
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-9-b888f18a64ca> in <module>()
----> 1 train(1)

<ipython-input-8-62f20437433e> in train(epoch)
     38                                                       decoder_lengths = decoder_lengths,
     39                                                       hidden = decoder_hidden,
---> 40                                                       drop_prob = drop_prob)
     41 
     42         return decoder_target, logits

<ipython-input-6-cdd22ad1dcec> in forward(self, encoder_input, encoder_lengths, decoder_input, decoder_lengths, hidden, drop_prob)
     88                 hidden = None, drop_prob = 0.5):
     89         seq_len, batch_size = encoder_input.size()
---> 90         mu, logvar = self.encode(encoder_input, encoder_lengths)
     91         z = self.sample(mu, logvar, drop_prob)
     92         logits, hidden = self.decode(decoder_input, decoder_lengths, z, hidden, drop_prob, seq_len)

<ipython-input-6-cdd22ad1dcec> in encode(self, encoder_input, input_lengths)
     43         _, batch_size, _ = embeddings.size()
     44         Tracer()()
---> 45         packed_in = nn.utils.rnn.pack_padded_sequence(embeddings, input_lengths)
     46         finalHidden = self.encoderNet(packed_in, batch_size)
     47         mu = self.muNet(finalHidden)

/usr/local/lib64/python2.7/site-packages/torch/nn/utils/rnn.pyc in pack_padded_sequence(input, lengths, batch_first)
     51     """
     52     if lengths[-1] <= 0:
---> 53         raise ValueError("length of all samples has to be greater than 0, "
     54                          "but found an element in 'lengths' that is <=0")
     55     if batch_first:

ValueError: length of all samples has to be greater than 0, but found an element in 'lengths' that is <=0

This was in pytorch 1.12. upgraded to ‘0.3.0.post4’  and the error I am getting with the same data is this:
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-13-97b62eefdc79> in <module>()
----> 1 packed_in = nn.utils.rnn.pack_padded_sequence(encoder_input, encoder_lengths)

/usr/local/lib64/python2.7/site-packages/torch/nn/utils/rnn.pyc in pack_padded_sequence(input, lengths, batch_first)
     51         a :class:`PackedSequence` object
     52     """
---> 53     if lengths[-1] <= 0:
     54         raise ValueError("length of all samples has to be greater than 0, "
     55                          "but found an element in 'lengths' that is <=0")

/usr/local/lib64/python2.7/site-packages/torch/autograd/variable.pyc in __bool__(self)
    123             return False
    124         raise RuntimeError("bool value of Variable objects containing non-empty " +
--> 125                            torch.typename(self.data) + " is ambiguous")
    126 
    127     __nonzero__ = __bool__

RuntimeError: bool value of Variable objects containing non-empty torch.ByteTensor is ambiguous


Any idea where the problem is? @smth