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