8000 Aborted (core dumped) in `slow_conv_transpose3d` · Issue #142457 · pytorch/pytorch · GitHub
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LongZE666 opened this issue Dec 10, 2024 · 1 comment · May be fixed by #148620
Open

Aborted (core dumped) in slow_conv_transpose3d #142457

LongZE666 opened this issue Dec 10, 2024 · 1 comment · May be fixed by #148620
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actionable module: convolution Problems related to convolutions (THNN, THCUNN, CuDNN) module: crash Problem manifests as a hard crash, as opposed to a RuntimeError module: edge cases Adversarial inputs unlikely to occur in practice module: error checking Bugs related to incorrect/lacking error checking module: nn Related to torch.nn triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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@LongZE666
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LongZE666 commented Dec 10, 2024 •
edited by pytorch-bot bot
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🐛 Describe the bug

Under specific inputs, slow_conv_transpose3d triggered a crash.

import torch

self = torch.full((1, 2, 4, 5, 4,), 0.5, dtype=torch.double)
weight = torch.full((2, 3, 2, 3, 2,), 0.5, dtype=torch.double)
kernel_size = [1, 1, 1]
bias = torch.full((3,), 0.5, dtype=torch.double)
stride = [1, 1, 1]
padding = [2, 2, 2]
output_padding = [2, 2, 2]
dilation = [1879048192, 1879048192, 1879048192]
torch.ops.aten.slow_conv_transpose3d(self, weight, kernel_size, bias, stride, padding, output_padding, dilation)

Output

double free or corruption (!prev)
Aborted (core dumped)

Versions

PyTorch version: 2.5.0a0+git32f585d
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.13.0 | packaged by Anaconda, Inc. | (main, Oct 7 2024, 21:29:38) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 80
On-line CPU(s) list: 0-79
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Gold 5218R CPU @ 2.10GHz
CPU family: 6
Model: 85
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 2
Stepping: 7
CPU max MHz: 4000.0000
CPU min MHz: 800.0000
BogoMIPS: 4200.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 1.3 MiB (40 instances)
L1i cache: 1.3 MiB (40 instances)
L2 cache: 40 MiB (40 instances)
L3 cache: 55 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78
NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries:
[pip3] numpy==2.1.3
[pip3] torch==2.5.0a0+git32f585d
[conda] numpy 2.1.3 pypi_0 pypi
[conda] torch 2.5.0a0+git32f585d pypi_0 pypi

cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @malfet
@jbschlosser jbschlosser added module: crash Problem manifests as a hard crash, as opposed to a RuntimeError module: nn Related to torch.nn module: error checking Bugs related to incorrect/lacking error checking module: convolution Problems related to convolutions (THNN, THCUNN, CuDNN) triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module labels Dec 11, 2024
@albanD albanD added the module: edge cases Adversarial inputs unlikely to occur in practice label Dec 11, 2024
@mikaylagawarecki
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mikaylagawarecki commented Dec 13, 2024 •
edited
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We would accept a PR that adds single TORCH_CHECK in the appropriate place that prevents this abort

@AmalDevHaridevan AmalDevHaridevan linked a pull request Mar 5, 2025 that will close this issue
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actionable module: convolution Problems related to convolutions (THNN, THCUNN, CuDNN) module: crash Problem manifests as a hard crash, as opposed to a RuntimeError module: edge cases Adversarial inputs unlikely to occur in practice module: error checking Bugs related to incorrect/lacking error checking module: nn Related to torch.nn triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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