Hi all,
I’ve been using LongTensor for my batches. and I transformed my list into Longtensor directly which gives me
Variable containing:
1.4000e+01  1.4000e+01  1.5300e+02  …   6.1000e+01  6.8000e+01  1.0700e+02
3.0160e+03  5.5880e+03  1.7000e+01  …   6.0000e+00  2.7514e+04  1.5000e+01
4.8000e+01  1.7000e+01  3.0000e+00  …   6.9000e+01  9.5000e+01  1.0000e+00
…                   ⋱                   …
0.0000e+00  0.0000e+00  0.0000e+00  …   4.0980e+03  0.0000e+00  1.0830e+03
0.0000e+00  0.0000e+00  0.0000e+00  …   1.6600e+03  0.0000e+00  0.0000e+00
0.0000e+00  0.0000e+00  0.0000e+00  …   0.0000e+00  0.0000e+00  0.0000e+00
[torch.LongTensor of size 17x64]
I only have three batches that has scientific notation while others that processed in a same way remain normal(in the way I want):
Variable containing:
662    231  47893  …     231   1465     61
1   5766     17  …       8      2    742
17     54    106  …     102  15417     25
…            ⋱           …
585     30     18  …       0      0      0
301      3    225  …       0      0      0
557   1755  28629  …       0      0      0
[torch.LongTensor of size 17x64]
And it seems that the first notation influence my embedding process, which throws me error as:
RuntimeError                              Traceback (most recent call last)
 in ()
8 embed = nn.Embedding(len(s_index2word), 128)
9 print(input_var)
—> 10 embedded = embed(input_var)
/home/wenyanli/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
222         for hook in self._forward_pre_hooks.values():
223             hook(self, input)
–> 224         result = self.forward(*input, **kwargs)
225         for hook in self._forward_hooks.values():
226             hook_result = hook(self, input, result)
/home/wenyanli/anaconda3/lib/python3.6/site-packages/torch/nn/modules/sparse.py in forward(self, input)
92             input, self.weight,
93             padding_idx, self.max_norm, self.norm_type,
—> 94             self.scale_grad_by_freq, self.sparse
95         )
96
/home/wenyanli/anaconda3/lib/python3.6/site-packages/torch/nn/_functions/thnn/sparse.py in forward(cls, ctx, indices, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
51             output = torch.index_select(weight, 0, indices)
52         else:
—> 53             output = torch.index_select(weight, 0, indices.view(-1))
54             output = output.view(indices.size(0), indices.size(1), weight.size(1))
55
RuntimeError: index out of range at /opt/conda/conda-bld/pytorch_1503965122592/work/torch/lib/TH/generic/THTensorMath.c:277
I’ve tried for several hours and still can’t fix this. Please help. Thx!