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Weizhi-Zhong / IP_LAP

CVPR2023 talking face implementation for Identity-Preserving Talking Face Generation With Landmark and Appearance Priors
Apache License 2.0
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video renderer speed is slow #20

Open huangxin168 opened 1 year ago

huangxin168 commented 1 year ago

Thank you for your open source. I tried the CUDA_VISIBLE_DEVICES=0 python inference_single.py and got the result ./test_result/129result_N_25_Nl_15.mp4 every thing goes fine, except the inference speed is slow(only got around 5.0it/s using RTX4090) Is there any suggestion for optimizing the speed?

komilaria commented 1 year ago

C:\Users\USER\miniconda3\envs\ip-lab\lib\site-packages\torch\nn\modules\module.py:1130: UserWarning: FALLBACK path has been taken inside: torch::jit::fuser::cuda::runCudaFusionGroup. This is an indication that codegen Failed for some reason. To debug try disable codegen fallback path via setting the env variable export PYTORCH_NVFUSER_DISABLE=fallback (Triggered internally at C:\cb\pytorch_1000000000000\work\torch\csrc\jit\codegen\cuda\manager.cpp:334.) return forward_call(*input, **kwargs) 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 528/528 [03:24<00:00, 2.58it/s] the same issue

komilaria commented 1 year ago

Thank you for your open source. I tried the CUDA_VISIBLE_DEVICES=0 python inference_single.py and got the result ./test_result/129result_N_25_Nl_15.mp4 every thing goes fine, except the inference speed is slow(only got around 5.0it/s using RTX4090) Is there any suggestion for optimizing the speed?

did you get result?