Segmentation Fault on 16 Channel WAV #1145
Description
🐛 Describe the bug
Loading a 16 channel wav file causes a segmentation fault. (Converting to an ogg file with ffmpeg and then loading works, for whatever reason).
#!/bin/sh
ffmpeg -f lavfi -i "sine=frequency=10000:duration=5" sine.wav
ffmpeg -i sine.wav -i sine.wav -i sine.wav -i sine.wav \
-i sine.wav -i sine.wav -i sine.wav -i sine.wav \
-i sine.wav -i sine.wav -i sine.wav -i sine.wav \
-i sine.wav -i sine.wav -i sine.wav -i sine.wav \
-filter_complex "[0:a][1:a][2:a][3:a][4:a][5:a][6:a][7:a][8:a][9:a][10:a][11:a][12:a][13:a][14:a][15:a]amerge=inputs=16[a]" \
-map "[a]" -c:a pcm_s16le 16ch.wav
ffprobe 16ch.wav
# ... Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 44100 Hz, 16 channels, s16, 11289 kb/s
python3 -c "from torchcodec.decoders import AudioDecoder; dec=AudioDecoder('16ch.wav'); dec.get_all_samples()"
# Segmentation fault (core dumped)
ffmpeg -i 16ch.wav 16ch.ogg
ffprobe 16ch.ogg
# ... Stream #0:0: Audio: vorbis, 44100 Hz, 16 channels, fltp, 1280 kb/s ...
python3 -c "from torchcodec.decoders import AudioDecoder; dec=AudioDecoder('16ch.ogg'); print(dec.get_all_samples())"
# AudioSamples:
# data (shape): torch.Size([16, 220736])
# pts_seconds: 0.0
# duration_seconds: 5.005351473922903
# sample_rate: 44100
Versions
PyTorch version: 2.9.1+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.3 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: 3.12.8 | packaged by Anaconda, Inc. | (main, Dec 11 2024, 16:31:09) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-86-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3060
Nvidia driver version: 550.54.15
cuDNN version: Could not collect
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 4
On-line CPU(s) list: 0-3
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i5-7500 CPU @ 3.40GHz
CPU family: 6
Model: 158
Thread(s) per core: 1
Core(s) per socket: 4
Socket(s): 1
Stepping: 9
CPU max MHz: 3800.0000
CPU min MHz: 800.0000
BogoMIPS: 6799.81
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 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 128 KiB (4 instances)
L1i cache: 128 KiB (4 instances)
L2 cache: 1 MiB (4 instances)
L3 cache: 6 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-3
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT disabled
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT disabled
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT disabled
Vulnerability Retbleed: Mitigation; 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; IBRS, IBPB conditional, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Mitigation; Microcode
Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] numpy==2.3.5
[pip3] numpy-minmax==0.5.0
[pip3] numpy-rms==0.6.0
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn==8.2.0.51
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] onnx==1.19.1
[pip3] onnxruntime-gpu==1.23.2
[pip3] optree==0.17.0
[pip3] torch==2.9.1
[pip3] torchaudio==2.9.1
[pip3] torchcodec==0.8.1
[pip3] triton==3.5.1
[conda] numpy 1.25.0 pypi_0 pypi