Full (dec+filters) ffmpeg-vaapi pipeline for Intel GPU (xpu pytorch backend)#832
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dvrogozh wants to merge 4 commits intometa-pytorch:mainfrom
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Full (dec+filters) ffmpeg-vaapi pipeline for Intel GPU (xpu pytorch backend)#832dvrogozh wants to merge 4 commits intometa-pytorch:mainfrom
dvrogozh wants to merge 4 commits intometa-pytorch:mainfrom
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FFmpeg filter graphs allow to cover a lot of use cases including cpu and gpu usages. This commit moves filter graph support out of CPU device interface which allows flexibility in usage across other contexts. Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@gmail.com>
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Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@gmail.com>
This commit enables support for Intel GPUs in torchcodec. It adds: * ffmpeg-vaapi for decoding and color space conversion from decoding output to RGBA * RGBA surface import as torch tensor (on torch xpu device) * RGBA to RGB24 tensor slicing To build torchcodec with Intel GPU support: * Install pytorch with XPU backend support. For example, with: ``` pip3 install torch --index-url https://download.pytorch.org/whl/xpu ``` * Install oneAPI development environment following https://github.com/pytorch/pytorch?tab=readme-ov-file#intel-gpu-support * Build and install FFmpeg with `--enable-vaapi` * Install torcheval (for tests): `pip3 install torcheval` * Build torchcodec with: `ENABLE_XPU=1 python3 setup.py devel` Notes: * RGB24 is not supported color format on current Intel GPUs (as it is considered to be suboptimal due to odd alignments) * Intel media and compute APIs can't seamlessly work with the memory from each other. For example, Intel computes's Unified Shared Memory pointers are not recognized by media APIs. Thus, lower level sharing via dma fds is needed. This alos makes this part of the solution OS dependent. * Color space conversion algoriths might be quite different as it happens for Intel. This requires to check PSNR values instead of per-pixel atol/rtol differences. * Installing oneAPI environment is neded due to pytorch/pytorch#149075 This commit was primary verfied on Intel Battlemage G21 (0xe20b) and Intel Data Center GPU Flex (0x56c0). Co-authored-by: Edgar Romo Montiel <edgar.romo.montiel@intel.com> Signed-off-by: Edgar Romo Montiel <edgar.romo.montiel@intel.com> Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com> Use ffmpeg-vaapi filters for color conversion in XPU interface Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@gmail.com>
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Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@gmail.com>
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Background
I submit this PR to illustrate filter graphs usage for multi-gpu support on the example of ffmpeg vaapi backend. The difference of this PR from #558 is usage of ffmpeg filters for color space conversion. Pay attention that
XpuDeviceInterfaceimplemented in the last commit of this PR can further be generalized to support any hw (and cpu) ffmpeg backend by having these 3 backend specific stuff:AVBufferRef)scalevs.scale_vaapivs.scale_cuda)AVFrame(from filters) to the tensorThe reason of this PR being a draft is that currently full (dec+filters) ffmpeg-vaapi pipeline generates worse quality output vs. pipeline in #558. Reason for that is handling of color standards in
scale_vaapifilter and Intel media driver. I believe there are some issues here in these components which needs to be reported and fixed. I will follow up.Details
This commit enables support for Intel GPUs in torchcodec. It adds:
output to RGBA
To build torchcodec with Intel GPU support:
https://github.com/pytorch/pytorch?tab=readme-ov-file#intel-gpu-support
--enable-vaapipip3 install torchevalENABLE_XPU=1 python3 setup.py developCC: @scotts @NicolasHug @eromomon