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Update Readme for lcm

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  1. README.md +31 -11
README.md CHANGED
@@ -7,6 +7,7 @@ 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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  - tensorrt
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  - text-to-image
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  ---
@@ -15,12 +16,10 @@ tags:
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  ## Introduction
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- This repository hosts the TensorRT versions 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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- Usage instructions for the LCM version of sdxl [here](lcm/README.md)
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-
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  ![examples](./examples.jpg)
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@@ -50,18 +49,25 @@ Usage instructions for the LCM version of sdxl [here](lcm/README.md)
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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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  ## Usage Example
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- 1. Following the [setup instructions](https://github.com/rajeevsrao/TensorRT/blob/release/8.6/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/8.6
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- docker run --rm -it --gpus all -v $PWD:/workspace nvcr.io/nvidia/pytorch:23.06-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
@@ -72,14 +78,13 @@ cd ..
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  3. Install libraries and requirements
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  ```shell
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- python3 -m pip install --upgrade pip
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- python3 -m pip install --upgrade tensorrt
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-
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  cd demo/Diffusion
 
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  pip3 install -r requirements.txt
 
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  ```
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- 4. Perform TensorRT optimized inference
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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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  ```
@@ -93,4 +98,19 @@ python3 demo_txt2img_xl.py \
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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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  - 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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  ## 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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  ![examples](./examples.jpg)
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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 LCM version for 4 steps at 1024x1024
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+
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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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+
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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 LCM 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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  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 for the 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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  --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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+
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+ 4. Perform TensorRT optimized inference for the sdxl Latent Consistency Model (LCM) version
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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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  ```