add Stable diffusion examples (#12418)

* add openjourney example

* add timing

* add stable diffusion to model page

* 4.1 fix

* small fix

README.md

@@ -330,6 +330,7 @@ Over 50 models have been optimized/verified on `ipex-llm`, including *LLaMA/LLaM
 | MiniCPM-V-2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/minicpm-v-2) | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-V-2) |
 | MiniCPM-Llama3-V-2_5 |  | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-Llama3-V-2_5) |
 | MiniCPM-V-2_6 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/minicpm-v-2_6) | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-V-2_6) | 
+| StableDiffusion | | [link](python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion) |
 
 ## Get Support
 - Please report a bug or raise a feature request by opening a [Github Issue](https://github.com/intel-analytics/ipex-llm/issues)

README.zh-CN.md

@@ -329,6 +329,7 @@ See the demo of running [*Text-Generation-WebUI*](https://ipex-llm.readthedocs.i
 | MiniCPM-V-2 |  | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-V-2) |
 | MiniCPM-Llama3-V-2_5 |  | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-Llama3-V-2_5) |
 | MiniCPM-V-2_6 |  | [link](python/llm/example/GPU/HuggingFace/Multimodal/MiniCPM-V-2_6) | 
+| StableDiffusion | | [link](python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion) |
 
 ## 官方支持
 - 如果遇到问题，或者请求新功能支持，请提交 [Github Issue](https://github.com/intel-analytics/ipex-llm/issues) 告诉我们

python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion/README.md

@@ -88,8 +88,19 @@ set SYCL_CACHE_PERSISTENT=1
 > 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 Openjourney Example
+The example shows how to run Openjourney example on Intel GPU.
+```bash
+python ./openjourney.py
+```
 
-#### 4.1 StableDiffusion XL Example
+Arguments info:
+- `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Openjourney model (e.g. `prompthero/openjourney`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'prompthero/openjourney'`.
+- `--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 `openjourney-gpu.png`.
+- `--num-steps`: argument defining the number of inference steps. It is default to be `20`. 
+
+#### 4.2 StableDiffusion XL Example
 The example shows how to run StableDiffusion XL example on Intel GPU.
 ```bash
 python ./sdxl.py
@@ -105,7 +116,7 @@ Arguments info:
 The sample output image looks like below. 
 ![image](https://llm-assets.readthedocs.io/en/latest/_images/sdxl-gpu.png)
 
-#### 4.2 LCM-LoRA Example
+#### 4.3 LCM-LoRA Example
 The example shows how to performing inference with LCM-LoRA on Intel GPU.
 ```bash
 python ./lora-lcm.py

python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion/lora-lcm.py

@@ -19,6 +19,7 @@ import torch
 from diffusers import DiffusionPipeline, LCMScheduler
 import ipex_llm
 import argparse
+import time
 
 
 def main(args):
@@ -34,10 +35,21 @@ def main(args):
     pipe.load_lora_weights(args.lora_weights_path)
 
     generator = torch.manual_seed(42)
-    image = pipe(
-        prompt=args.prompt, num_inference_steps=args.num_steps, generator=generator, guidance_scale=1.0
-    ).images[0]
-    image.save(args.save_path)
+
+    with torch.inference_mode():
+        # warmup
+        image = pipe(
+            prompt=args.prompt, num_inference_steps=args.num_steps, generator=generator, guidance_scale=1.0
+        ).images[0]
+
+        # start inference
+        st = time.time()
+        image = pipe(
+            prompt=args.prompt, num_inference_steps=args.num_steps, generator=generator, guidance_scale=1.0
+        ).images[0]   
+        end = time.time()
+        print(f'Inference time: {end-st} s')
+        image.save(args.save_path)
 
 if __name__=="__main__":
     parser = argparse.ArgumentParser(description="Stable Diffusion lora-lcm")

python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion/openjourney.py

@@ -0,0 +1,54 @@
+#
+# Copyright 2016 The BigDL Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# Code is adapted from https://huggingface.co/prompthero/openjourney
+
+from diffusers import StableDiffusionPipeline
+import torch
+import ipex_llm
+import argparse
+import time
+
+
+def main(args):
+    pipe = StableDiffusionPipeline.from_pretrained(
+        args.repo_id_or_model_path, 
+        torch_dtype=torch.float16, 
+        use_safetensors=True)
+    pipe = pipe.to("xpu")
+
+    with torch.inference_mode():
+        # warmup
+        image = pipe(args.prompt, num_inference_steps=args.num_steps).images[0]
+
+        # start inference
+        st = time.time()
+        image = pipe(args.prompt, num_inference_steps=args.num_steps).images[0]
+        end = time.time()
+        print(f'Inference time: {end-st} s')
+        image.save(args.save_path)
+
+if __name__=="__main__":
+    parser = argparse.ArgumentParser(description="Stable Diffusion")
+    parser.add_argument('--repo-id-or-model-path', type=str, default="prompthero/openjourney",
+                        help='The huggingface repo id for the stable diffusion model checkpoint')
+    parser.add_argument('--prompt', type=str, default="An astronaut in the forest, detailed, 8k",
+                        help='Prompt to infer')
+    parser.add_argument('--save-path',type=str,default="openjourney-gpu.png",
+                        help="Path to save the generated figure")
+    parser.add_argument('--num-steps',type=int,default=20,
+                        help="Number of inference steps")
+    args = parser.parse_args()
+    main(args)

python/llm/example/GPU/HuggingFace/Multimodal/StableDiffusion/sdxl.py

@@ -21,6 +21,7 @@ import ipex_llm
 import numpy as np
 from PIL import Image
 import argparse
+import time
 
 
 def main(args):
@@ -30,8 +31,16 @@ def main(args):
         use_safetensors=True
     ).to("xpu")
 
-    image = pipeline_text2image(prompt=args.prompt,num_inference_steps=args.num_steps).images[0]
-    image.save(args.save_path)
+    with torch.inference_mode():
+        # warmup
+        image = pipeline_text2image(prompt=args.prompt,num_inference_steps=args.num_steps).images[0]
+
+        # start inference
+        st = time.time()
+        image = pipeline_text2image(prompt=args.prompt,num_inference_steps=args.num_steps).images[0]
+        end = time.time()
+        print(f'Inference time: {end-st} s')
+        image.save(args.save_path)
 
 if __name__=="__main__":
     parser = argparse.ArgumentParser(description="Stable Diffusion")