GPU decode error

[Mdaughter]

I run the code in docker container and its image is pytorch/pytorch:1.7.1-cuda11.0-cudnn8-devel.
I follow the example and build successfully, but something wrong happen

from decord import VideoReader
from decord import cpu, gpu
video='/data/Celeb-DF-v2/YouTube-real/00000.mp4'
vr = VideoReader(video, ctx=gpu(0))
frames = vr.get_batch([1, 3, 5, 7, 9])

The error pops out like:

CUDA error 3000 at line 341 in file /workspace/decord/src/video/nvcodec/cuda_threaded_decoder.cc: Traceback (most recent call last):
  File "/workspace/decord/python/test.py", line 5, in <module>
    x = vr[1]
  File "/workspace/decord/python/decord/video_reader.py", line 104, in __getitem__
    self.seek_accurate(idx)
  File "/workspace/decord/python/decord/video_reader.py", line 232, in seek_accurate
    success = _CAPI_VideoReaderSeekAccurate(self._handle, pos)
  File "/workspace/decord/python/decord/_ffi/_ctypes/function.py", line 174, in __call__
    check_call(_LIB.DECORDFuncCall(
  File "/workspace/decord/python/decord/_ffi/base.py", line 78, in check_call
    raise DECORDError(err_str)
decord._ffi.base.DECORDError: [11:17:09] /workspace/decord/src/video/nvcodec/cuda_threaded_decoder.cc:270: Check failed: run_.load():

Env:ffmpeg 4.3.2,cuda 11.0,RTX 2080 Ti,Ubuntu 18.04

[trifle]

Hi, I don't have very specific solutions but a few general observations that are always useful:

• Ensure you have an up-to-date version of docker and nvidia-docker
• Ensure your system drivers are new enough to support the version of CUDA you're running
• !! Make sure your system (not docker image) has the required drivers installed, especially nvcuvid - these are not present in the container, they are linked in!
• make sure to expose all gpu capabilities and the correct gpus to the container when running
• make sure there is no version mismatch between the CUDA libraries installed in the container and those required by your python libraries

If in doubt, there's a new Dockerfile in this repo that has been provided by levan92. You can try to use that as a baseline and install torch from within that.

[sandcobainer]

I see the same issue with ctx=cpu(0), so I doubt if it's anything to do with the GPU

[zxf864823150]

I also meet this problem. when I just
from decord import VideoReader
from decord import cpu, gpu
vr = VideoReader(video, ctx=gpu(0))
all is ok, the len(vr)can be read,in my case,len(vr) =811.
however,when I do
frames = vr.get_batch([1, 3, 5, 7, 9])
this error coming
DECORDError: [01:55:24] /mnt/zxf/decord_gpu/decord/src/video/nvcodec/cuda_threaded_decoder.cc:270: Check failed: run_.load()

[jbohnslav]

I have the same issue on one of my videos-- CPU only.

I then tried vr.next() and got a more specific error message:

/github/workspace/src/video/ffmpeg/threaded_decoder.cc:292: [12:57:23] /github/workspace/src/video/ffmpeg
/threaded_decoder.cc:218: Check failed: avcodec_send_packet(dec_ctx_.get(), pkt.get()) >= 0 (-22 vs. 0) 
Thread worker: Error sending packet.

[mbanani]

I am facing a similar bug where the first N frames will be okay, but anything after frame N will result in those errors (sending packets and run_.load(). Did any one figure this out?

I am not sure if it's related to this issue regarding corrupt frames or pertaining to videos coming from specific cameras.

[schmidtdominik]

I am facing a similar bug where the first N frames will be okay, but anything after frame N will result in those errors

I'm having this exact issue too when decoding on the CPU. It's not related to corrupt files because the problem doesn't occur if I install decord from source and use it on the GPU.

[sanjayss34]

I've run into this issue as well (on cpu) -- does anyone have a fix?

[2000ZRL]

I also met the same problem.

[Leo-yang-1020]

It stil exists now, not fixed. Hope to see more solutions

[btekin]

Setting num_threads=1 in VideoReader resolves the issue for me.

[m4a1carbin4]

Setting num_threads=1 in VideoReader resolves the issue for me.

Thanks! it's work for me

[azuredsky]

does anyone solve it?