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conv(None) -> hang or segfault #1356

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adamlerer opened this issue Apr 25, 2017 · 2 comments
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conv(None) -> hang or segfault #1356

adamlerer opened this issue Apr 25, 2017 · 2 comments
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@adamlerer
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import torch
import torch.nn as nn
from torch.autograd import Variable
c = nn.Conv2d(3, 3, 3)
c(None)

Segmentation fault: 11

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@soumith
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soumith commented Apr 25, 2017

maybe fixed by #1293 ?

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soumith commented Apr 25, 2017

oh None input is not checked, that is for double backward.

@colesbury colesbury added the bug label Apr 26, 2017
@colesbury colesbury self-assigned this Apr 26, 2017
@colesbury colesbury mentioned this issue Apr 26, 2017
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colesbury added a commit to colesbury/pytorch that referenced this issue Apr 26, 2017
@colesbury
Check for required non-None arguments in C++ autograd functions
fbb9a5b 
Fixes pytorch#1356
colesbury added a commit to colesbury/pytorch that referenced this issue May 18, 2017
@colesbury
Check for required non-None arguments in C++ autograd functions
55b397c 
Fixes pytorch#1356
@colesbury colesbury mentioned this issue May 18, 2017
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eqy pushed a commit to eqy/pytorch that referenced this issue Jan 20, 2022
@csarofeen
Collection of refactoring in nvFuser lowering (pytorch#1339)
d29fb48 
* Refactor War Sync Insertion Pass (pytorch#1339)
* Remove kir::Expr::scope_ (pytorch#1341)
* Fusion IR Refactor (pytorch#1343)
* Refactor KIR Step 1 - Remove kir::Node (pytorch#1347)
* Refactor KIR Step 2 - TMP IrUtils change (pytorch#1348)
* Refactor KIR Step 3 - Remove kir::Expr and kir::Val. (pytorch#1349)
* Refactor KIR Step 4 - Remove kir::Bool,Double,Int,NamedScalar. (pytorch#1350)
* Refactor KIR Step 5 - Remove kir::IterDomain/TensorDomain/TensorView (pytorch#1351)
* Refactor KIR Step 6 - Remove 
 kir::UnaryOp/BinaryOp/TernaryOp/ReductionOp/WelfordOp/BroadcastOp. (pytorch#1352)
* Refactor KIR Step 7 - Remove kir dispatch (pytorch#1353)
* Refactor KIR Step 8 - Clean up lower_utils (pytorch#1355)
* Refactor KIR Step 9 - lower_utils ir_utils::applyReplacements. (pytorch#1354)
* Refactor KIR Step 10 - Remove kir_printer in favor of io_stream (pytorch#1356)
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@colesbury @soumith @apaszke @adamlerer