nightly torchaudio.load cannot find sox

[subramen]

🐛 Describe the bug

The nightly version (2.1.0) appears to not find sox.

Repro on colab:

## STABLE
print(torchaudio.__version__)
# 2.0.2+cu118

print(torchaudio.utils.sox_utils.list_read_formats())
# ['aifc', 'aiffc', 'aiff', 'aif', 'al', 'au', 'snd', 'avr', 'cdda', 'cdr', 'cvsd', 'cvs', 'cvu', 'dat', 'dvms', 'vms', 'f4', 'f32', 'f8', 'f64', 'gsrt', 'hcom', 'htk', 'ima', 'la', 'lu', 'maud', 'null', 'prc', 'raw', 's1', 's8', 'sb', 's2', 's16', 'sw', 's3', 's24', 's4', 's32', 'sl', 'sf', 'ircam', 'sln', 'smp', 'sndr', 'sndt', 'sox', 'sph', 'nist', '8svx', 'txw', 'u1', 'u8', 'ub', 'sou', 'fssd', 'u2', 'u16', 'uw', 'u3', 'u24', 'u4', 'u32', 'ul', 'voc', 'vox', 'wav', 'wavpcm', 'amb', 'wve', 'xa', 'amr-nb', 'anb', 'amr-wb', 'awb', 'flac', 'gsm', 'lpc10', 'lpc', 'opus', 'vorbis', 'ogg']

print(torchaudio.backend.get_audio_backend())
# 'sox_io'

-----

## NIGHTLY
print(torchaudio.__version__)
# 2.1.0.dev20230807+cu118

print(torchaudio.utils.sox_utils.list_read_formats())
# RuntimeError: list_read_formats requires sox extension which is not available. Please refer to the stacktrace above for how to resolve this

print(torchaudio.backend.get_audio_backend())
# UserWarning: get_audio_backend's return value is irrelevant when the I/O backend dispatcher is enabled.
# ValueError: Unknown backend

Loading a wav file also errors in the nightly:

>>> torchaudio.load('audio.wav', format='wav')
RuntimeError: Couldn't find appropriate backend to handle uri .assets/bird_audio.wav and format wav

Versions

PyTorch version: 2.1.0.dev20230807+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.2 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.25.2
Libc version: glibc-2.35

Python version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.109+-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0
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):                          2
On-line CPU(s) list:             0,1
Vendor ID:                       GenuineIntel
Model name:                      Intel(R) Xeon(R) CPU @ 2.20GHz
CPU family:                      6
Model:                           79
Thread(s) per core:              2
Core(s) per socket:              1
Socket(s):                       1
Stepping:                        0
BogoMIPS:                        4400.44
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities
Hypervisor vendor:               KVM
Virtualization type:             full
L1d cache:                       32 KiB (1 instance)
L1i cache:                       32 KiB (1 instance)
L2 cache:                        256 KiB (1 instance)
L3 cache:                        55 MiB (1 instance)
NUMA node(s):                    1
NUMA node0 CPU(s):               0,1
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Mitigation; PTE Inversion
Vulnerability Mds:               Vulnerable; SMT Host state unknown
Vulnerability Meltdown:          Vulnerable
Vulnerability Mmio stale data:   Vulnerable
Vulnerability Retbleed:          Vulnerable
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1:        Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:        Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Vulnerable

Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] pytorch-triton==2.1.0+e6216047b8
[pip3] torch==2.1.0.dev20230807+cu118
[pip3] torchaudio==2.1.0.dev20230807+cu118
[pip3] torchdata==0.6.1
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.15.2
[pip3] torchvision==0.16.0.dev20230807+cu118
[pip3] triton==2.0.0
[conda] Could not collect

[mthrok]

We no longer bundle libsox to torchaudio. We ask users to install sox separately. Could you install libsox and try again?

[mthrok]

Also enabling debug log (logging.basicConfig(level=logging.DEBUG)) before import torchaudio gives more detail of what torchaudio attempts and how it fails to find libsox. If it does not work after installing libsox, please include the log.

[subramen]

Thanks @mthrok. Perhaps https://github.com/pytorch/audio/blob/main/docs/source/backend.rst#availability needs an update to reflect this change?

[sawradip]

This might be of help, before installing sox seperately with apt:

apt install libsox-dev