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stabilityai / stable-diffusion-xl-1.0-tensorrt
Model's Last Updated: December 29 2023
text-to-image
Introduction of stable-diffusion-xl-1.0-tensorrt
Model Details of stable-diffusion-xl-1.0-tensorrt
Stable Diffusion XL 1.0 TensorRT
Introduction
This repository hosts the TensorRT versions(sdxl, sdxl-lcm, sdxl-lcmlora) of Stable Diffusion XL 1.0 created in collaboration with NVIDIA . The optimized versions give substantial improvements in speed and efficiency.
See the usage instructions for how to run the SDXL pipeline with the ONNX files hosted in this repository.
Model Description
- Developed by: Stability AI
- Model type: Diffusion-based text-to-image generative model
- License: CreativeML Open RAIL++-M License
- Model Description: This is a conversion of the SDXL base 1.0 and SDXL refiner 1.0 models for NVIDIA TensorRT optimized inference
Performance Comparison
Timings for 30 steps at 1024x1024
| Accelerator | Baseline (non-optimized) | NVIDIA TensorRT (optimized) | Percentage improvement |
|---|---|---|---|
| A10 | 9399 ms | 8160 ms | ~13% |
| A100 | 3704 ms | 2742 ms | ~26% |
| H100 | 2496 ms | 1471 ms | ~41% |
Image throughput for 30 steps at 1024x1024
| Accelerator | Baseline (non-optimized) | NVIDIA TensorRT (optimized) | Percentage improvement |
|---|---|---|---|
| A10 | 0.10 images/sec | 0.12 images/sec | ~20% |
| A100 | 0.27 images/sec | 0.36 images/sec | ~33% |
| H100 | 0.40 images/sec | 0.68 images/sec | ~70% |
Timings for Latent Consistency Model(LCM) version for 4 steps at 1024x1024
| Accelerator | CLIP | Unet | VAE | Total |
|---|---|---|---|---|
| A100 | 1.08 ms | 192.02 ms | 228.34 ms | 426.16 ms |
| H100 | 0.78 ms | 102.8 ms | 126.95 ms | 234.22 ms |
Usage Example
- Following the setup instructions on launching a TensorRT NGC container.
git clone https://github.com/rajeevsrao/TensorRT.git
cd TensorRT
git checkout release/9.2
docker run --rm -it --gpus all -v $PWD:/workspace nvcr.io/nvidia/pytorch:23.11-py3 /bin/bash
- Download the SDXL TensorRT files from this repo
git lfs install
git clone https://huggingface.co/stabilityai/stable-diffusion-xl-1.0-tensorrt
cd stable-diffusion-xl-1.0-tensorrt
git lfs pull
cd ..
- Install libraries and requirements
cd demo/Diffusion
python3 -m pip install --upgrade pip
pip3 install -r requirements.txt
python3 -m pip install --pre --upgrade --extra-index-url https://pypi.nvidia.com tensorrt
- Perform TensorRT optimized inference:
-
SDXL
The first invocation produces plan files in
engine_xl_baseandengine_xl_refinerspecific to the accelerator being run on and are reused for later invocations.python3 demo_txt2img_xl.py \ "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" \ --build-static-batch \ --use-cuda-graph \ --num-warmup-runs 1 \ --width 1024 \ --height 1024 \ --denoising-steps 30 \ --onnx-base-dir /workspace/stable-diffusion-xl-1.0-tensorrt/sdxl-1.0-base \ --onnx-refiner-dir /workspace/stable-diffusion-xl-1.0-tensorrt/sdxl-1.0-refiner -
SDXL-LCM
The first invocation produces plan files in --engine-dir specific to the accelerator being run on and are reused for later invocations.
python3 demo_txt2img_xl.py \ ""Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"" \ --version=xl-1.0 \ --onnx-dir /workspace/stable-diffusion-xl-1.0-tensorrt/lcm \ --engine-dir /workspace/stable-diffusion-xl-1.0-tensorrt/lcm/engine-sdxl-lcm-nocfg \ --scheduler LCM \ --denoising-steps 4 \ --guidance-scale 0.0 \ --seed 42 -
SDXL-LCMLORA
The first invocation produces plan files in --engine-dir specific to the accelerator being run on and are reused for later invocations.
python3 demo_txt2img_xl.py \ ""Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"" \ --version=xl-1.0 \ --onnx-dir /workspace/stable-diffusion-xl-1.0-tensorrt/lcmlora \ --engine-dir /workspace/stable-diffusion-xl-1.0-tensorrt/lcm/engine-sdxl-lcmlora-nocfg \ --scheduler LCM \ --lora-path latent-consistency/lcm-lora-sdxl \ --lora-scale 1.0 \ --denoising-steps 4 \ --guidance-scale 0.0 \ --seed 42
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