Open zzpmiracle opened 1 year ago
pipeine | model | img size | unet-pytorch | unet-disc | e2e-pytorch | e2e-disc |
---|---|---|---|---|---|---|
stableDiffusionPipeline | stabilityai/stable-diffusion-2-1 | 768*768 | 119.81ms | 60.08ms | 6.21s | 3.14s |
StableDiffusionImg2ImgPipeline | runwayml/stable-diffusion-v1-5 | 768*512 | 66.22ms | 29.49ms | 3.25s | 1.30s |
StableDiffusionDepth2ImgPipeline | stabilityai/stable-diffusion-2-depth | 480*640 | 44.33ms | 19.89ms | 2.08s | 0.89s |
StableDiffusionInpaintPipeline | runwayml/stable-diffusion-inpainting | 512*512 | 37.52ms | 19.17ms | 2.63s | 1.10s |
AltDiffusionPipeline | BAAI/AltDiffusion | 512*512 | 37.93ms | 18.74ms | 2.65s | 1.08s |
How about the e2e latency run with TensorRT/AIT?
pipeine model img size unet-pytorch unet-disc e2e-pytorch e2e-disc stableDiffusionPipeline stabilityai/stable-diffusion-2-1 768768 119.81ms 60.08ms 6.21s 3.14s StableDiffusionImg2ImgPipeline runwayml/stable-diffusion-v1-5 768512 66.22ms 29.49ms 3.25s 1.30s StableDiffusionDepth2ImgPipeline stabilityai/stable-diffusion-2-depth 480640 44.33ms 19.89ms 2.08s 0.89s StableDiffusionInpaintPipeline runwayml/stable-diffusion-inpainting 512512 37.52ms 19.17ms 2.63s 1.10s AltDiffusionPipeline BAAI/AltDiffusion 512*512 37.93ms 18.74ms 2.65s 1.08s
Can you share the scripts to run these benchmarks?
@zzpmiracle Where I can find scripts to run this benchmarks? i've tried using it on the latest diffusers version, and it can't trace the components...
@zzpmiracle Where I can find scripts to run this benchmarks? i've tried using it on the latest diffusers version, and it can't trace the components...
maybe we can use docker images in this zhihu article https://zhuanlan.zhihu.com/p/631461489
@zzpmiracle Where I can find scripts to run this benchmarks? i've tried using it on the latest diffusers version, and it can't trace the components...
maybe we can use docker images in this zhihu article https://zhuanlan.zhihu.com/p/631461489
@zzpmiracle hi, do you have an example of Hires.fix ?
We have support diffusers in https://github.com/alibaba/BladeDISC/issues/867 . This issue tracks performance of all the diffuser pipelines. For the concern of performance, we use BlaDNN to tuning models during runtime. The following pipelines would be tested: