> > On Apr 29, 2024, at 18:29, Guo, Yejun <yejun.guo-at-intel....@ffmpeg.org>
> wrote:
> >
> >
> >
> >> -----Original Message-----
> >> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org> On Behalf Of
> Zhao
> >> Zhili
> >> Sent: Sunday, April 28, 2024 6:55 PM
> >> To: FFmpeg development discussions and patches <ffmpeg-
> >> de...@ffmpeg.org>
> >> Subject: Re: [FFmpeg-devel] [PATCH WIP 0/9] Refactor DNN
> >>
> >>
> >>
> >>> On Apr 28, 2024, at 18:34, Guo, Yejun <yejun.guo-at-
> >> intel....@ffmpeg.org> wrote:
> >>>
> >>>> -----Original Message-----
> >>>> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org
> >>>> <mailto:ffmpeg-devel-boun...@ffmpeg.org>> On Behalf Of Zhao Zhili
> >>>> Sent: Sunday, April 28, 2024 12:42 AM
> >>>> To: ffmpeg-devel@ffmpeg.org <mailto:ffmpeg-devel@ffmpeg.org>
> >>>> Cc: Zhao Zhili <zhiliz...@tencent.com
> <mailto:zhiliz...@tencent.com>>
> >>>> Subject: [FFmpeg-devel] [PATCH WIP 0/9] Refactor DNN
> >>>>
> >>>> From: Zhao Zhili <zhiliz...@tencent.com>
> >>>>
> >>>> During the refactor progress, I have found some serious issues, which
> >>>> is not resolved by the patchset:
> >>>>
> >>>> 1. Tensorflow backend is broken.
> >>>>
> >>>> I think it doesn't work since 2021 at least. For example, it destroy
> >>>> a thread and create a new thread for each frame, and it destroy an
> >>>> invalid thread at the first
> >>>> frame:
> >>>
> >>> It works from the day that code is merged, till today. It is by design
> >>> to keep the code simplicity by using the feature that pthread_join
> >>> accepts a parameter that is not a joinable thread.
> >>>
> >>> Please share more info if you experienced a real case that it does not
> work.
> >>
> >> It will abort if ASSERT_LEVEL > 1.
> >>
> >> #define ASSERT_PTHREAD_ABORT(func, ret) do {                            \
> >>    char errbuf[AV_ERROR_MAX_STRING_SIZE] = "";                         \
> >>    av_log(NULL, AV_LOG_FATAL, AV_STRINGIFY(func)                       \
> >>           " failed with error: %s\n",                                  \
> >>           av_make_error_string(errbuf, AV_ERROR_MAX_STRING_SIZE,       \
> >>                                AVERROR(ret)));                         \
> >>    abort();                                                            \
> >> } while (0)
> >>
> >> I think the check is there just to prevent call pthread_join(0, &ptr) by
> accident,
> >> so we shouldn’t do that on purpose.
> >>
> > Nice catch with configure assert level > 1, will fix, and patch also 
> > welcome,
> thanks.
> 
> If I read the code correctly, it destroy a thread and create a new thread for
> each
> frame. I think this “async” mode isn’t common in ffmpeg’s design. Create new
> thread
> for each frame can be heavy on some platforms. We use slice threading to
> improve
> parallel, and thread with command queue to improve throughput. In this
> case with
> tensorflow do the heavy lift, if it doesn’t support async operation, simple
> synchronous
> operation with tensorflow backend should be find. The “async” mode is
> unnecessary
> and use more resource  over the benefit it provides.

I think we need to keep async support.
1. Some model cannot make full use of resource. This may be caused by tensorflow
implementation or by model design. Async has benefit on this situation.
2. Async helps to build pipeline. You don't need to wait the output. If a 
"synchronous" filter
followed by another "synchronous" filter, it can be the bottle neck of the 
whole pipeline.

The benefit on these two situations will be more obvious if model is running on 
GPU.( Tensorflow
has not added device support yet.)

> 
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