Runtime error : Could not load libtorchcodec #1131
Description
🐛 Describe the bug
Hi TorchCodec Team!
I am trying to get torchcodec to work with pytorch for RTX 5090 but running into this error, what am I doing wrong?:
(lerobot) neel@neel-workstation:~/Projects/lerobot_drl/neel$ python - <<'PY' import subprocess, sys
import torch
print("python:", sys.version)
print("torch:", torch.version)
try:
import torchcodec
print("torchcodec:", torchcodec.version)
except Exception as e:
print("torchcodec import failed:", e)
subprocess.run(["ffmpeg", "-hide_banner", "-version"])
PYpython: 3.10.19 | packaged by conda-forge | (main, Oct 22 2025, 22:29:10) [GCC 14.3.0]
torch: 2.11.0.dev20251214+cu128
torchcodec import failed: Could not load libtorchcodec. Likely causes:
1. FFmpeg is not properly installed in your environment. We support
versions 4, 5, 6, 7, and 8. On Windows, ensure you've installed
the "full-shared" version which ships DLLs.
2. The PyTorch version (2.11.0.dev20251214+cu128) is not compatible with
this version of TorchCodec. Refer to the version compatibility
table:
https://github.com/pytorch/torchcodec?tab=readme-ov-file#installing-torchcodec.
3. Another runtime dependency; see exceptions below.
The following exceptions were raised as we tried to load libtorchcodec:[start of libtorchcodec loading traceback]
FFmpeg version 8: Could not load this library: /home/neel/miniconda3/envs/lerobot/lib/python3.10/site-packages/torchcodec/libtorchcodec_core8.so
FFmpeg version 7: Could not load this library: /home/neel/miniconda3/envs/lerobot/lib/python3.10/site-packages/torchcodec/libtorchcodec_core7.so
FFmpeg version 6: Could not load this library: /home/neel/miniconda3/envs/lerobot/lib/python3.10/site-packages/torchcodec/libtorchcodec_core6.so
FFmpeg version 5: Could not load this library: /home/neel/miniconda3/envs/lerobot/lib/python3.10/site-packages/torchcodec/libtorchcodec_core5.so
FFmpeg version 4: Could not load this library: /home/neel/miniconda3/envs/lerobot/lib/python3.10/site-packages/torchcodec/libtorchcodec_core4.so
[end of libtorchcodec loading traceback].
ffmpeg version 7.1.1 Copyright (c) 2000-2025 the FFmpeg developers
built with gcc 14.3.0 (conda-forge gcc 14.3.0-5)
configuration: --prefix=/home/neel/miniconda3/envs/lerobot --cc=/home/conda/feedstock_root/build_artifacts/ffmpeg_1758923917305/_build_env/bin/x86_64-conda-linux-gnu-cc --cxx=/home/conda/feedstock_root/build_artifacts/ffmpeg_1758923917305/_build_env/bin/x86_64-conda-linux-gnu-c++ --nm=/home/conda/feedstock_root/build_artifacts/ffmpeg_1758923917305/_build_env/bin/x86_64-conda-linux-gnu-nm --ar=/home/conda/feedstock_root/build_artifacts/ffmpeg_1758923917305/_build_env/bin/x86_64-conda-linux-gnu-ar --disable-doc --enable-openssl --enable-demuxer=dash --enable-hardcoded-tables --enable-libfreetype --enable-libharfbuzz --enable-libfontconfig --enable-libopenh264 --enable-libdav1d --disable-gnutls --enable-libvpx --enable-libass --enable-pthreads --enable-alsa --enable-libpulse --enable-vaapi --enable-libvpl --enable-libopenvino --enable-gpl --enable-libx264 --enable-libx265 --enable-libmp3lame --enable-libaom --enable-libsvtav1 --enable-libxml2 --enable-pic --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libvorbis --enable-libopus --enable-librsvg --enable-ffplay --pkg-config=/home/conda/feedstock_root/build_artifacts/ffmpeg_1758923917305/_build_env/bin/pkg-config
libavutil 59. 39.100 / 59. 39.100
libavcodec 61. 19.101 / 61. 19.101
libavformat 61. 7.100 / 61. 7.100
libavdevice 61. 3.100 / 61. 3.100
libavfilter 10. 4.100 / 10. 4.100
libswscale 8. 3.100 / 8. 3.100
libswresample 5. 3.100 / 5. 3.100
libpostproc 58. 3.100 / 58. 3.100
Versions
Collecting environment information...
PyTorch version: 2.11.0.dev20251214+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A
OS: Ubuntu 24.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.5.0-1ubuntu1~24.04) 11.5.0
Clang version: Could not collect
CMake version: version 4.1.0
Libc version: glibc-2.39
Python version: 3.10.19 | packaged by conda-forge | (main, Oct 22 2025, 22:29:10) [GCC 14.3.0] (64-bit runtime)
Python platform: Linux-6.14.0-33-generic-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: 13.0.88
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 5090
Nvidia driver version: 580.95.05
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): 32
On-line CPU(s) list: 0-31
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i9-14900KF
CPU family: 6
Model: 183
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 1
Stepping: 1
CPU(s) scaling MHz: 22%
CPU max MHz: 6000.0000
CPU min MHz: 800.0000
BogoMIPS: 6374.40
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 tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx 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 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 896 KiB (24 instances)
L1i cache: 1.3 MiB (24 instances)
L2 cache: 32 MiB (12 instances)
L3 cache: 36 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-31
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: 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: Mitigation; Clear Register File
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; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] mypy_extensions==1.1.0
[pip3] numpy==2.2.6
[pip3] nvidia-cublas==13.0.0.19
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti==13.0.48
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc==13.0.48
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime==13.0.48
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-cu13==9.13.0.50
[pip3] nvidia-cufft==12.0.0.15
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-curand==10.4.0.35
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver==12.0.3.29
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse==12.6.2.49
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cusparselt-cu13==0.8.0
[pip3] nvidia-nccl-cu12==2.28.9
[pip3] nvidia-nccl-cu13==2.27.7
[pip3] nvidia-nvjitlink==13.0.39
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvtx==13.0.39
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pytorch-triton==3.5.1+gitbfeb0668
[pip3] torch==2.11.0.dev20251214+cu128
[pip3] torchaudio==2.10.0.dev20251119+cu128
[pip3] torchcodec==0.10.0.dev20251214+cu128
[pip3] torchvision==0.25.0.dev20251214+cu128
[pip3] triton==3.6.0+git8fedd49b
[conda] libopenvino-pytorch-frontend 2025.2.0 hecca717_1 conda-forge
[conda] numpy 2.2.6 pypi_0 pypi
[conda] nvidia-cublas 13.0.0.19 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.8.4.1 pypi_0 pypi
[conda] nvidia-cuda-cupti 13.0.48 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cuda-nvrtc 13.0.48 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-cuda-runtime 13.0.48 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.10.2.21 pypi_0 pypi
[conda] nvidia-cudnn-cu13 9.13.0.50 pypi_0 pypi
[conda] nvidia-cufft 12.0.0.15 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.3.3.83 pypi_0 pypi
[conda] nvidia-curand 10.4.0.35 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.9.90 pypi_0 pypi
[conda] nvidia-cusolver 12.0.3.29 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.7.3.90 pypi_0 pypi
[conda] nvidia-cusparse 12.6.2.49 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.5.8.93 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.7.1 pypi_0 pypi
[conda] nvidia-cusparselt-cu13 0.8.0 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.28.9 pypi_0 pypi
[conda] nvidia-nccl-cu13 2.27.7 pypi_0 pypi
[conda] nvidia-nvjitlink 13.0.39 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-nvtx 13.0.39 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.8.90 pypi_0 pypi
[conda] pytorch-triton 3.5.1+gitbfeb0668 pypi_0 pypi
[conda] tbb 2022.3.0 h8d10470_1 conda-forge
[conda] torch 2.11.0.dev20251214+cu128 pypi_0 pypi
[conda] torchaudio 2.10.0.dev20251119+cu128 pypi_0 pypi
[conda] torchcodec 0.10.0.dev20251214+cu128 pypi_0 pypi
[conda] torchvision 0.25.0.dev20251214+cu128 pypi_0 pypi
[conda] triton 3.6.0+git8fedd49b pypi_0 pypi