visproduction 283 Posted February 10 Posted February 10 Related with posted solution? https://stackoverflow.com/questions/78256694/cant-convert-video-with-cuda-after-updating-ffmpeg
studzik5521 3 Posted February 12 Author Posted February 12 On 2/10/2025 at 3:50 PM, visproduction said: Related with posted solution? https://stackoverflow.com/questions/78256694/cant-convert-video-with-cuda-after-updating-ffmpeg This thread is of no help, there is no solution there, only a workaround by changing the ffmpeg version - there is no option to change the version in emby. The logs below are from the docker emby container root@1a62b45efc16:/IPTV/Testowe# ffmpeg -y -init_hw_device "cuda=cuda:0" -hwaccel cuda -hwaccel_output_format cuda -i "Shameless_HEVC_EAC3.mkv" -filter_complex "[0:v]scale_cuda=w=640:h=360:format=yuv420p,setsar=sar=1[vout]" -map "[vout]" -map 0:a:0 -c:v h264_nvenc -b:v 464k -maxrate 464k -bufsize 928k -g 75 -keyint_min 75 -r 25 -profile:v high -c:a libmp3lame -b:a 192k -ac 2 -metadata:s:a:0 language=eng -filter:a "volume=3" -max_delay 5000000 -avoid_negative_ts disabled -f mp4 "output.mp4" ffmpeg version 6.1.1-3ubuntu5 Copyright (c) 2000-2023 the FFmpeg developers built with gcc 13 (Ubuntu 13.2.0-23ubuntu3) configuration: --prefix=/usr --extra-version=3ubuntu5 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --disable-omx --enable-gnutls --enable-libaom --enable-libass --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libdav1d --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libglslang --enable-libgme --enable-libgsm --enable-libharfbuzz --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzimg --enable-openal --enable-opencl --enable-opengl --disable-sndio --enable-libvpl --disable-libmfx --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-ladspa --enable-libbluray --enable-libjack --enable-libpulse --enable-librabbitmq --enable-librist --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libx264 --enable-libzmq --enable-libzvbi --enable-lv2 --enable-sdl2 --enable-libplacebo --enable-librav1e --enable-pocketsphinx --enable-librsvg --enable-libjxl --enable-shared libavutil 58. 29.100 / 58. 29.100 libavcodec 60. 31.102 / 60. 31.102 libavformat 60. 16.100 / 60. 16.100 libavdevice 60. 3.100 / 60. 3.100 libavfilter 9. 12.100 / 9. 12.100 libswscale 7. 5.100 / 7. 5.100 libswresample 4. 12.100 / 4. 12.100 libpostproc 57. 3.100 / 57. 3.100 Input #0, matroska,webm, from 'Shameless_HEVC_EAC3.mkv': Metadata: title : Witajcie W Chicago encoder : libebml v1.3.6 + libmatroska v1.4.9 creation_time : 2024-06-17T11:06:53.000000Z DESCRIPTION : W premierowym odcinku sezonu Gallagherowie dostosowują swoje życie do pandemii. Duration: 00:52:11.01, start: 0.000000, bitrate: 1454 kb/s Stream #0:0: Video: hevc (Main 10), yuv420p10le(tv, bt709), 1280x720 [SAR 1:1 DAR 16:9], 25 fps, 25 tbr, 1k tbn (default) Stream #0:1(eng): Audio: eac3, 48000 Hz, 5.1(side), fltp, 256 kb/s Stream #0:2(pol): Audio: eac3, 48000 Hz, stereo, fltp, 128 kb/s (default) Stream #0:3(eng): Subtitle: subrip (default) Stream #0:4(pol): Subtitle: subrip Stream #0:5: Video: png, rgb24(pc, gbr/unknown/unknown), 3840x2160 [SAR 6614:6614 DAR 16:9], 90k tbr, 90k tbn (attached pic) Metadata: filename : cover.png mimetype : image/png Stream mapping: Stream #0:0 (hevc) -> scale_cuda:default (graph 0) setsar:default (graph 0) -> Stream #0:0 (h264_nvenc) Stream #0:1 -> #0:1 (eac3 (native) -> mp3 (libmp3lame)) Press [q] to stop, [?] for help Output #0, mp4, to 'output.mp4': Metadata: title : Witajcie W Chicago DESCRIPTION : W premierowym odcinku sezonu Gallagherowie dostosowują swoje życie do pandemii. encoder : Lavf60.16.100 Stream #0:0: Video: h264 (High) (avc1 / 0x31637661), cuda(tv, bt709, progressive), 640x360 [SAR 1:1 DAR 16:9], q=2-31, 464 kb/s, 25 fps, 12800 tbn Metadata: encoder : Lavc60.31.102 h264_nvenc Side data: cpb: bitrate max/min/avg: 464000/0/464000 buffer size: 928000 vbv_delay: N/A Stream #0:1(eng): Audio: mp3 (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 192 kb/s Metadata: encoder : Lavc60.31.102 libmp3lame frame= 5921 fps=356 q=35.0 size= 18432kB time=00:03:58.20 bitrate= 633.9kbits/s speed=14.3x [q] command received. Exiting. [out#0/mp4 @ 0x5b0750de8240] video:13086kB audio:5620kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.883045% frame= 5975 fps=354 q=33.0 Lsize= 18871kB time=00:03:59.73 bitrate= 644.8kbits/s speed=14.2x root@1a62b45efc16:/IPTV/Testowe# nvidia-smi Wed Feb 12 16:06:00 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 570.86.15 Driver Version: 570.86.15 CUDA Version: 12.8 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce GTX 1050 On | 00000000:02:00.0 On | N/A | | 31% 38C P5 N/A / 65W | 11MiB / 2048MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+ root@1a62b45efc16:/IPTV/Testowe# ls -la /dev/dri /dev/nvi* crw-rw-rw- 1 root root 195, 254 Feb 12 15:16 /dev/nvidia-modeset crw-rw-rw- 1 root root 234, 0 Feb 11 01:09 /dev/nvidia-uvm crw-rw-rw- 1 root root 234, 1 Feb 11 01:09 /dev/nvidia-uvm-tools crw-rw-rw- 1 root root 195, 0 Feb 11 01:09 /dev/nvidia0 crw-rw-rw- 1 root root 195, 255 Feb 11 01:09 /dev/nvidiactl /dev/dri: total 0 drwxr-xr-x 2 root root 80 Feb 12 15:16 . drwxr-xr-x 8 root root 540 Feb 12 15:16 .. crw-rw---- 1 root video 226, 1 Feb 12 15:16 card1 crw-rw---- 1 root videopsuh 226, 128 Feb 12 15:16 renderD128 /dev/nvidia-caps: total 0 drwxr-xr-x 2 root root 80 Feb 12 15:16 . drwxr-xr-x 8 root root 540 Feb 12 15:16 .. cr-------- 1 root root 237, 1 Feb 12 15:16 nvidia-cap1 cr--r--r-- 1 root root 237, 2 Feb 12 15:16 nvidia-cap2 It seems there is a problem with the ffmpeg version on emby. I am also attaching current logs emby from the same video, because I changed a lot in LXC and Docker and maybe something has changed. embyserver (18).txtffmpeg-transcode-5a2e108b-6a1f-4d44-b84c-1eaa5d402a33_1.txthardware_detection-63874974109.txtffmpeg-transcode-e8f42b36-180a-473c-aa74-08722b1db3c4_1.txtffmpeg-transcode-c69bc159-b017-4968-9005-6c13373bd541_1.txt
studzik5521 3 Posted February 13 Author Posted February 13 (edited) I did an additional test with tensorflow, and this test shows that tensorflow works -> "Created device /device:GPU:0 with 1709 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:02:00.0, compute capability: 6.1" [+] Running 1/1 ✔ Container docker_compose-test-1 Created 0.1s Attaching to test-1 test-1 | Adding groups to root test-1 | usermod: group 'render' does not exist test-1 | Thu Feb 13 08:57:41 2025 test-1 | +-----------------------------------------------------------------------------------------+ test-1 | | NVIDIA-SMI 570.86.15 Driver Version: 570.86.15 CUDA Version: 12.8 | test-1 | |-----------------------------------------+------------------------+----------------------+ test-1 | | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | test-1 | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | test-1 | | | | MIG M. | test-1 | |=========================================+========================+======================| test-1 | | 0 NVIDIA GeForce GTX 1050 On | 00000000:02:00.0 On | N/A | test-1 | | 31% 33C P8 N/A / 65W | 11MiB / 2048MiB | 0% Default | test-1 | | | | N/A | test-1 | +-----------------------------------------+------------------------+----------------------+ test-1 | test-1 | +-----------------------------------------------------------------------------------------+ test-1 | | Processes: | test-1 | | GPU GI CI PID Type Process name GPU Memory | test-1 | | ID ID Usage | test-1 | |=========================================================================================| test-1 | | No running processes found | test-1 | +-----------------------------------------------------------------------------------------+ test-1 | crw-rw-rw- 1 root root 195, 254 Feb 11 01:09 /dev/nvidia-modeset test-1 | crw-rw-rw- 1 root root 234, 0 Feb 11 01:09 /dev/nvidia-uvm test-1 | crw-rw-rw- 1 root root 234, 1 Feb 11 01:09 /dev/nvidia-uvm-tools test-1 | crw-rw-rw- 1 root root 195, 0 Feb 11 01:09 /dev/nvidia0 test-1 | crw-rw-rw- 1 root root 195, 255 Feb 11 01:09 /dev/nvidiactl test-1 | test-1 | /dev/dri: test-1 | total 0 test-1 | drwxr-xr-x 2 root root 80 Feb 13 08:57 . test-1 | drwxr-xr-x 8 root root 540 Feb 13 08:57 .. test-1 | crw-rw---- 1 root video 226, 1 Feb 13 08:57 card1 test-1 | crw-rw---- 1 root messagebus 226, 128 Feb 13 08:57 renderD128 test-1 | test-1 | /dev/nvidia-caps: test-1 | total 0 test-1 | drwxr-xr-x 2 root root 80 Feb 13 08:57 . test-1 | drwxr-xr-x 8 root root 540 Feb 13 08:57 .. test-1 | cr-------- 1 root root 237, 1 Feb 13 08:57 nvidia-cap1 test-1 | cr--r--r-- 1 root root 237, 2 Feb 13 08:57 nvidia-cap2 test-1 | 2025-02-13 08:57:42.564114: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered test-1 | 2025-02-13 08:57:42.564207: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered test-1 | 2025-02-13 08:57:42.564296: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered test-1 | 2025-02-13 08:57:42.584028: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. test-1 | To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. test-1 | 2025-02-13 08:57:47.103531: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1886] Created device /device:GPU:0 with 1709 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:02:00.0, compute capability: 6.1 test-1 | Test ended test-1 | Checking user groups test-1 | root test-1 | uid=0(root) gid=0(root) groups=0(root),44(video),104(messagebus) test-1 | id: ‘asd’: no such user test-1 | 2025-02-13 08:57:48.549313: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered test-1 | 2025-02-13 08:57:48.549383: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered test-1 | 2025-02-13 08:57:48.549469: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered test-1 | 2025-02-13 08:57:48.568846: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. test-1 | To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. test-1 | 2025-02-13 08:57:52.947286: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1886] Created device /device:GPU:0 with 1709 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:02:00.0, compute capability: 6.1 test-1 | [name: "/device:CPU:0" test-1 | device_type: "CPU" test-1 | memory_limit: 268435456 test-1 | locality { test-1 | } test-1 | incarnation: 17319742619020076593 test-1 | xla_global_id: -1 test-1 | , name: "/device:GPU:0" test-1 | device_type: "GPU" test-1 | memory_limit: 1792868352 test-1 | locality { test-1 | bus_id: 1 test-1 | links { test-1 | } test-1 | } test-1 | incarnation: 2310164362109010218 test-1 | physical_device_desc: "device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:02:00.0, compute capability: 6.1" test-1 | xla_global_id: 416903419 test-1 | ] test-1 | test-1 | Done docker: services: test: image: tensorflow/tensorflow:2.14.0-gpu #command: python -c "import tensorflow as tf;tf.test.gpu_device_name()" #command: nvidia-smi #command: ls -la /dev/dri /dev/nvi* command: sh -c "/root/postup.sh && tail -f /dev/null" privileged: true #runtime: nvidia deploy: resources: reservations: devices: - capabilities: [gpu] count: 1 driver: nvidia volumes: - ./test.sh:/root/postup.sh environment: - NVIDIA_VISIBLE_DEVICES=all - NVIDIA_DRIVER_CAPABILITIES=compute,compat32,graphics,utility,video,display script: #!/bin/sh echo "Adding groups to root" usermod -aG video root usermod -aG render root usermod -aG messagebus root nvidia-smi ls -la /dev/dri /dev/nvi* #pip install tensorflow[and-cuda] python -c "import tensorflow as tf;tf.test.gpu_device_name()" echo "Test ended" echo "Checking user groups" whoami id root id asd python -c "from tensorflow.python.client import device_lib; print(device_lib.list_local_devices())" echo "\nDone" exit 0 Edited February 13 by studzik5521
studzik5521 3 Posted February 13 Author Posted February 13 On 2/8/2025 at 1:06 AM, Luke said: Hi, can you please perform the same test using the native package? Thanks. I didn't notice your post earlier Here is the same test on a native application in LXC on Debian 12. hardware_detection-63875050823.txtffmpeg-transcode-d78f6499-de05-466d-bedb-cbf566c0dc8c_1.txtffmpeg-transcode-d8f6b027-2ad7-4a7c-8caa-caee83a4f8d8_1.txtffmpeg-transcode-91a2507d-db8f-42fb-97db-058405bfa6be_1.txtembyserver (21).txt
Solution studzik5521 3 Posted February 17 Author Solution Posted February 17 Problem "solved" - I switched from proxmox to truenas. 1
visproduction 283 Posted February 17 Posted February 17 Might be of interest. Nvidia GTX 1050 fix for poxmox: https://github.com/sk1080/nvidia-kvm-patcher
studzik5521 3 Posted February 24 Author Posted February 24 (edited) Switching to another system helped. So the problem is gone. Thank you guys. Edited February 24 by studzik5521
Luke 40096 Posted March 1 Posted March 1 On 2/7/2025 at 9:16 PM, softworkz said: Thanks a lot for the logs. Unfortunately this doesn't give any further hint, other than that it confirms that it happens when initializing the CUDA filter. It's not like anything I've seen before. It could be anything from hardware to OS, to drivers, to Proxmox (host). Here are some things you can try to hopefully get a hint in the right direction. I would focus on CUDA functionality: You could try a rather older version of drivers - like from 2022 or 2023 You can download the Nvidia CUDA toolkit. There are a number of demos you can compile and run And there's a tool included named "deviceQuery" which you can try to run You can watch Linux logs (like dmesg - IIRC) Trying a regular ffmpeg (with Nvidia HWA) might also be worth a try, but our HWA support for Nvidia on Linux is very stable and issue reports are rare Finally you can try to contact Nvidia support, but I would try some of the things above before, so that you can provide useful information Please let us know about your progress. Thanks @studzik5521are you able to try this?
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