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🐛 Describe the bug

Occasionally, a core dump error may occur with a specific audio file as input, which a Python exception cannot capture.

This error is rare, but when it does occur, the entire Python process will be killed. It only happens with some ”special audio”. Unfortunately, I did not find out what the special was.

How to reproduce:

1. Download the numpy array that causes the core dump in my environment.

a.npy.zip

2. Run the following code:

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy
from torchaudio.io import AudioEffector, CodecConfig
import torch

module = AudioEffector(
format='ogg',
encoder='opus',
codec_config=CodecConfig(qscale=1),
pad_end=True,)


audio = numpy.load('./a.npy')


output = module.apply(torch.from_numpy(audio), 44100).numpy()

[W414 21:10:43.989426875 encode_process.cpp:179] Warning: "opus" encoder is selected. Enabling '-strict experimental'. If this is not desired, please provide "strict" encoder option with desired value. (function operator())
[1]    2613659 segmentation fault (core dumped)  python debug.py

My python and package versions:

numpy                    2.0.2
torch                    2.6.0
torch-complex            0.4.4
torchaudio               2.6.0

Versions

Collecting environment information... PyTorch version: 2.6.0+cu124 Is debug build: False CUDA used to build PyTorch: 12.4 ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.2 LTS (x86_64) GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 Clang version: Could not collect CMake version: version 3.28.3 Libc version: glibc-2.39

Python version: 3.10.16 (main, Dec 11 2024, 16:24:50) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-6.11.0-21-generic-x86_64-with-glibc2.39 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090 Nvidia driver version: 550.120 cuDNN version: Could not collect 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: 48 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 32 On-line CPU(s) list: 0-31 Vendor ID: AuthenticAMD Model name: AMD Ryzen 9 9950X 16-Core Processor CPU family: 26 Model: 68 Thread(s) per core: 2 Core(s) per socket: 16 Socket(s): 1 Stepping: 0 Frequency boost: enabled CPU(s) scaling MHz: 67% CPU max MHz: 5752.0000 CPU min MHz: 600.0000 BogoMIPS: 8599.98 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good amd_lbr_v2 nopl xtopology nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba perfmon_v2 ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local user_shstk avx_vnni avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid bus_lock_detect movdiri movdir64b overflow_recov succor smca fsrm avx512_vp2intersect flush_l1d amd_lbr_pmc_freeze Virtualization: AMD-V L1d cache: 768 KiB (16 instances) L1i cache: 512 KiB (16 instances) L2 cache: 16 MiB (16 instances) L3 cache: 64 MiB (2 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-31 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

Versions of relevant libraries: [pip3] numpy==2.0.2 [pip3] nvidia-cublas-cu12==12.4.5.8 [pip3] nvidia-cuda-cupti-cu12==12.4.127 [pip3] nvidia-cuda-nvrtc-cu12==12.4.127 [pip3] nvidia-cuda-runtime-cu12==12.4.127 [pip3] nvidia-cudnn-cu12==9.1.0.70 [pip3] nvidia-cufft-cu12==11.2.1.3 [pip3] nvidia-curand-cu12==10.3.5.147 [pip3] nvidia-cusolver-cu12==11.6.1.9 [pip3] nvidia-cusparse-cu12==12.3.1.170 [pip3] nvidia-cusparselt-cu12==0.6.2 [pip3] nvidia-nccl-cu12==2.21.5 [pip3] nvidia-nvjitlink-cu12==12.4.127 [pip3] nvidia-nvtx-cu12==12.4.127 [pip3] onnxruntime-gpu==1.21.0 [pip3] pytorch-lightning==2.5.1 [pip3] torch==2.6.0 [pip3] torch-complex==0.4.4 [pip3] torchaudio==2.6.0 [pip3] torchmetrics==1.7.1 [pip3] torchvision==0.21.0 [pip3] triton==3.2.0 [conda] numpy 2.0.2 pypi_0 pypi [conda] nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi [conda] nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi [conda] nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi [conda] nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi [conda] nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi [conda] nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi [conda] nvidia-curand-cu12 10.3.5.147 pypi_0 pypi [conda] nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi [conda] nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi [conda] nvidia-cusparselt-cu12 0.6.2 pypi_0 pypi [conda] nvidia-nccl-cu12 2.21.5 pypi_0 pypi [conda] nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi [conda] nvidia-nvtx-cu12 12.4.127 pypi_0 pypi [conda] pytorch-lightning 2.5.1 pypi_0 pypi [conda] torch 2.6.0 pypi_0 pypi [conda] torch-complex 0.4.4 pypi_0 pypi [conda] torchaudio 2.6.0 pypi_0 pypi [conda] torchmetrics 1.7.1 pypi_0 pypi [conda] torchvision 0.21.0 pypi_0 pypi [conda] triton 3.2.0 pypi_0 pypi