pytorch
Reading frames from VideoReader freezes eventually
🐛 Describe the bug
The problem only occurs under some specific conditions:
- The video backend is 'video_reader'
- The VideoReader object is initialized with raw bytes rather than a path string
- This byte buffer is loaded from an avi video file
Example code:
from torchvision.io import VideoReader
torchvision.set_video_backend('video_reader')
with open('/path/to/video.avi', 'rb') as fp:
data = fp.read()
reader = VideoReader(data)
frames = []
# this loop stops freezes after a while (usually towards the end of the video)
for data in reader:
frames.append(frame['data'])
Versions
Collecting environment information... PyTorch version: 2.1.1 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 7.5.0-6ubuntu2) 7.5.0 Clang version: Could not collect CMake version: version 3.26.4 Libc version: glibc-2.31
Python version: 3.11.6 | packaged by conda-forge | (main, Oct 3 2023, 10:40:35) [GCC 12.3.0] (64-bit runtime) Python platform: Linux-5.4.0-169-generic-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A100-PCIE-40GB GPU 1: NVIDIA A100-PCIE-40GB GPU 2: NVIDIA A100-PCIE-40GB GPU 3: NVIDIA A100-PCIE-40GB GPU 4: NVIDIA A100-PCIE-40GB GPU 5: NVIDIA A100-PCIE-40GB GPU 6: NVIDIA A100-PCIE-40GB GPU 7: NVIDIA A100-PCIE-40GB
Nvidia driver version: 525.147.05 cuDNN version: Probably one of the following: /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.0 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.0 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 Byte Order: Little Endian Address sizes: 43 bits physical, 48 bits virtual CPU(s): 128 On-line CPU(s) list: 0-127 Thread(s) per core: 2 Core(s) per socket: 32 Socket(s): 2 NUMA node(s): 2 Vendor ID: AuthenticAMD CPU family: 23 Model: 49 Model name: AMD EPYC 7452 32-Core Processor Stepping: 0 Frequency boost: enabled CPU MHz: 3272.256 CPU max MHz: 2350.0000 CPU min MHz: 1500.0000 BogoMIPS: 4700.22 Virtualization: AMD-V L1d cache: 2 MiB L1i cache: 2 MiB L2 cache: 32 MiB L3 cache: 256 MiB NUMA node0 CPU(s): 0-31,64-95 NUMA node1 CPU(s): 32-63,96-127 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 Retbleed: Vulnerable 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; Retpolines, IBPB conditional, IBRS_FW, STIBP conditional, 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 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf 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 ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip rdpid overflow_recov succor smca sme sev sev_es
Versions of relevant libraries:
[pip3] numpy==1.26.2
[pip3] numpy==1.26.2
[pip3] pytorch-lightning==2.1.2
[pip3] torch==2.1.1
[pip3] torchaudio==2.1.1
[pip3] torchdiffeq==0.2.3
[pip3] torchmetrics==1.2.1
[pip3] torchvision==0.16.1
[pip3] torchvision==0.16.1
[pip3] triton==2.1.0
[conda] blas 1.0 mkl
[conda] libblas 3.9.0 12_linux64_mkl conda-forge
[conda] libcblas 3.9.0 12_linux64_mkl conda-forge
[conda] liblapack 3.9.0 12_linux64_mkl conda-forge
[conda] mkl 2021.4.0 h06a4308_640
[conda] numpy 1.26.2 pypi_0 pypi
[conda] pytorch 2.1.1 py3.11_cuda11.8_cudnn8.7.0_0 pytorch
[conda] pytorch-cuda 11.8 h7e8668a_5 pytorch
[conda] pytorch-lightning 2.1.2 pyhd8ed1ab_0 conda-forge
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 2.1.1 dev_0
Thank you for the report @Tomsen1410 . @ahmadsharif1 curious if you have encountered this issue in your investigations already?
