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Segmentation fault (core dumped) when passing empty Tensors to pack_padded_sequence #20529

JamieCT opened this issue May 15, 2019 · 5 comments


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@JamieCT JamieCT commented May 15, 2019

Passing an empty tensor (so with shape (0,n,m)) to pack_padded_sequence causes a "segmentation fault (core dumped)"

Produce the error:

import torch
from torch.nn.utils.rnn import pack_padded_sequence
#bs, max_sequence_len, emb_dim
x = torch.zeros([16,10,20])
length = torch.zeros([16])
mask = [length != 0]
masked_x = x[mask]
masked_length = length[mask]
print(masked_x.shape, masked_length.shape)
pack_padded_sequence(masked_x, masked_length, batch_first = True)

Expected behavior:
An exception raised stating that the input tensor must not be empty.

Environments created on:
-PyTorch 1.0, Windows (installed via conda), CUDA (9.0)
-PyTorch 1.0, Linux (installed via pip), CUDA ('9.0.176')


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@ezyang ezyang commented Jun 4, 2019

Reproduced on 5fcd37b, this should be fixed.

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@t-vi t-vi commented Jun 6, 2019

I'll take a stab at fixing this.
@JamieCT thank you for reporting this and the reproduction script. This is very useful!

t-vi added a commit to t-vi/pytorch that referenced this issue Jun 6, 2019
Fixes: pytorch#20529

Thank you, @JamieCT for the bug report with reproducing script.
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@LeviViana LeviViana commented Jun 10, 2019

@t-vi I saw your great video where you fix this bug, thanks for that BTW. But, I noticed something that might improve the error report. Indeed, in the following line we assume that input has at least 2 dimensions:

I was wandering if it could be useful to insert something like:

TORCH_CHECK(input.dim() > 1, "The input must have at least 2 dimensions.");

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@t-vi t-vi commented Jun 10, 2019

@LeviViana sounds like a good addition, the IndexError currently thrown certainly isn't optimal. More to your point, it might be worth going over all the functions in torch.nn.utils.rnn / PackedSequence.cpp and seeing how well they check their inputs. Do ping me If you want to put up a PR. (I don't think you need to file a separate issue report.)

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@LeviViana LeviViana commented Sep 24, 2019

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6 participants