torchaudio.info returns incorrect result for num_frames when input is a video

[lematt1991]

🐛 Describe the bug

If the input is a video, torchaudio.info(<path>).num_frames returns the incorrect result. For example:

import torchaudio
from subprocess import check_call

url = "https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/NASAs_Most_Scientifically_Complex_Space_Observatory_Requires_Precision-MP4_small.mp4"
check_call(["wget", url, "-O", "sample_video.mp4"])

path = "sample_video.mp4"

wav, sr = torchaudio.load(path)
print(wav.shape)
print(torchaudio.info(path).num_frames)

Prints torch.Size([2, 9889792]) for wav.shape, but prints 9659 for torchaudio.info(path).num_frames. I'm guessing it's returning the number of video frames instead?

Versions

Collecting environment information...
PyTorch version: 2.1.0
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.27.7
Libc version: glibc-2.31

Python version: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-1048-aws-x86_64-with-glibc2.31
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: 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
Byte Order:                         Little Endian
Address sizes:                      46 bits physical, 48 bits virtual
CPU(s):                             96
On-line CPU(s) list:                0-95
Thread(s) per core:                 2
Core(s) per socket:                 24
Socket(s):                          2
NUMA node(s):                       2
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              85
Model name:                         Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
Stepping:                           7
CPU MHz:                            2499.998
BogoMIPS:                           4999.99
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          1.5 MiB
L1i cache:                          1.5 MiB
L2 cache:                           48 MiB
L3 cache:                           71.5 MiB
NUMA node0 CPU(s):                  0-23,48-71
NUMA node1 CPU(s):                  24-47,72-95
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
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 arch_perfmon rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.23.5
[pip3] perceiver-pytorch==0.8.8
[pip3] pytorch-lightning==2.1.2
[pip3] torch==2.1.0
[pip3] torch-fidelity==0.3.0
[pip3] torchaudio==2.1.0
[pip3] torchdiffeq==0.2.3
[pip3] torchlibrosa==0.1.0
[pip3] torchmetrics==1.2.0
[pip3] torchvision==0.16.0
[pip3] triton==2.1.0
[conda] blas                      2.116                       mkl  
[conda] blas-devel                3.9.0            16_linux64_mkl  
[conda] libblas                   3.9.0            16_linux64_mkl  
[conda] libcblas                  3.9.0            16_linux64_mkl  
[conda] liblapack                 3.9.0            16_linux64_mkl  
[conda] liblapacke                3.9.0            16_linux64_mkl  
[conda] mkl                       2022.1.0           h84fe81f_915  
[conda] mkl-devel                 2022.1.0           ha770c72_916  
[conda] mkl-include               2022.1.0           h84fe81f_915  
[conda] numpy                     1.23.5                   pypi_0    pypi
[conda] perceiver-pytorch         0.8.8                    pypi_0    pypi
[conda] pytorch                   2.1.0           aws_py3.10_cuda11.8_cudnn8.7.0_0  
[conda] pytorch-cuda              11.8                 h7e8668a_3  
[conda] pytorch-lightning         2.1.2                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda  
[conda] torch-fidelity            0.3.0                    pypi_0    pypi
[conda] torchaudio                2.1.0               py310_cu118  
[conda] torchdiffeq               0.2.3                    pypi_0    pypi
[conda] torchlibrosa              0.1.0                    pypi_0    pypi
[conda] torchmetrics              1.2.0                    pypi_0    pypi
[conda] torchtriton               2.1.0                     py310  
[conda] torchvision               0.16.0              py310_cu118 

[grazder]

I've got the same