119 lines
		
	
	
	
		
			4.3 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
			
		
		
	
	
			119 lines
		
	
	
	
		
			4.3 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
# Stable Diffusion
 | 
						|
In this directory, you will find examples on how to run StableDiffusion models on [Intel GPUs](../README.md).
 | 
						|
 | 
						|
### 1. Installation
 | 
						|
#### 1.1 Install IPEX-LLM
 | 
						|
Follow the instructions in IPEX-GPU installation guides ([Linux Guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html), [Windows Guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html)) according to your system to install IPEX-LLM. After the installation, you should have created a conda environment, named diffusion for instance. 
 | 
						|
 | 
						|
#### 1.2 Install dependencies for Stable Diffusion
 | 
						|
Assume you have created a conda environment named diffusion with ipex-llm installed. Run below commands to install dependencies for running Stable Diffusion.
 | 
						|
```bash
 | 
						|
conda activate diffusion
 | 
						|
pip install diffusers["torch"] transformers
 | 
						|
pip install -U PEFT transformers
 | 
						|
```
 | 
						|
 | 
						|
### 2. Configures OneAPI environment variables for Linux
 | 
						|
 | 
						|
> [!NOTE]
 | 
						|
> Skip this step if you are running on Windows.
 | 
						|
 | 
						|
This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI.
 | 
						|
 | 
						|
```bash
 | 
						|
source /opt/intel/oneapi/setvars.sh
 | 
						|
```
 | 
						|
 | 
						|
### 3. Runtime Configurations
 | 
						|
For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
 | 
						|
#### 3.1 Configurations for Linux
 | 
						|
<details>
 | 
						|
 | 
						|
<summary>For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series</summary>
 | 
						|
 | 
						|
```bash
 | 
						|
export USE_XETLA=OFF
 | 
						|
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
 | 
						|
export SYCL_CACHE_PERSISTENT=1
 | 
						|
```
 | 
						|
 | 
						|
</details>
 | 
						|
 | 
						|
<details>
 | 
						|
 | 
						|
<summary>For Intel Data Center GPU Max Series</summary>
 | 
						|
 | 
						|
```bash
 | 
						|
export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
 | 
						|
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
 | 
						|
export SYCL_CACHE_PERSISTENT=1
 | 
						|
export ENABLE_SDP_FUSION=1
 | 
						|
```
 | 
						|
</details>
 | 
						|
 | 
						|
<details>
 | 
						|
 | 
						|
<summary>For Intel iGPU</summary>
 | 
						|
 | 
						|
```bash
 | 
						|
export SYCL_CACHE_PERSISTENT=1
 | 
						|
export BIGDL_LLM_XMX_DISABLED=1
 | 
						|
```
 | 
						|
 | 
						|
</details>
 | 
						|
 | 
						|
#### 3.2 Configurations for Windows
 | 
						|
<details>
 | 
						|
 | 
						|
<summary>For Intel iGPU</summary>
 | 
						|
 | 
						|
```cmd
 | 
						|
set SYCL_CACHE_PERSISTENT=1
 | 
						|
set BIGDL_LLM_XMX_DISABLED=1
 | 
						|
```
 | 
						|
 | 
						|
</details>
 | 
						|
 | 
						|
<details>
 | 
						|
 | 
						|
<summary>For Intel Arc™ A-Series Graphics</summary>
 | 
						|
 | 
						|
```cmd
 | 
						|
set SYCL_CACHE_PERSISTENT=1
 | 
						|
```
 | 
						|
 | 
						|
</details>
 | 
						|
 | 
						|
> [!NOTE]
 | 
						|
> For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile.
 | 
						|
 | 
						|
### 4. Examples
 | 
						|
 | 
						|
#### 4.1 StableDiffusion XL Example
 | 
						|
The example shows how to run StableDiffusion XL example on Intel GPU.
 | 
						|
```bash
 | 
						|
python ./sdxl.py
 | 
						|
```
 | 
						|
 | 
						|
Arguments info:
 | 
						|
- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the stable diffusion xl model (e.g. `stabilityai/stable-diffusion-xl-base-1.0`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'stabilityai/stable-diffusion-xl-base-1.0'`.
 | 
						|
- `--prompt PROMPT`: argument defining the prompt to be infered. It is default to be `'An astronaut in the forest, detailed, 8k'`.
 | 
						|
- `--save-path`: argument defining the path to save the generated figure. It is default to be `sdxl-gpu.png`.
 | 
						|
- `--num-steps`: argument defining the number of inference steps. It is default to be `20`. 
 | 
						|
 | 
						|
 | 
						|
The sample output image looks like below. 
 | 
						|

 | 
						|
 | 
						|
#### 4.2 LCM-LoRA Example
 | 
						|
The example shows how to performing inference with LCM-LoRA on Intel GPU.
 | 
						|
```bash
 | 
						|
python ./lora-lcm.py
 | 
						|
```
 | 
						|
 | 
						|
Arguments info:
 | 
						|
- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the stable diffusion xl model (e.g. `stabilityai/stable-diffusion-xl-base-1.0`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'stabilityai/stable-diffusion-xl-base-1.0'`.
 | 
						|
- `--lora-weights-path`: argument defining the huggingface repo id for the LCM-LoRA model (e.g. `latent-consistency/lcm-lora-sdxl`) to be downloaded, or the path to huggingface checkpoint folder. It is default to be `'latent-consistency/lcm-lora-sdxl'`. 
 | 
						|
- `--prompt PROMPT`: argument defining the prompt to be infered. It is default to be `'A lovely dog on the table, detailed, 8k'`.
 | 
						|
- `--save-path`: argument defining the path to save the generated figure. It is default to be `lcm-lora-sdxl-gpu.png`.
 | 
						|
- `--num-steps`: argument defining the number of inference steps. It is default to be `4`.
 |