From 18903ad807c4405f303166bacc6b68822a42a6af Mon Sep 17 00:00:00 2001
From: chengjiaxiang <chengjiaxiang@bytedance.com>
Date: Sun, 31 Mar 2024 14:43:17 +0800
Subject: [PATCH] Add quick tutorial

---
 quicktour.py | 35 +++++++++++++++++++++++++++++++++++
 1 file changed, 35 insertions(+)
 create mode 100644 quicktour.py

diff --git a/quicktour.py b/quicktour.py
new file mode 100644
index 0000000..1199cb9
--- /dev/null
+++ b/quicktour.py
@@ -0,0 +1,35 @@
+import torch
+from torchvision.utils import save_image
+from safetensors.torch import load_file
+from huggingface_hub import hf_hub_download
+from diffusers import AutoPipelineForText2Image, DPMSolverMultistepScheduler, StableDiffusionPipeline
+
+generator = torch.manual_seed(0)
+prompt = "portrait photo of muscular bearded guy in a worn mech suit, light bokeh, intricate, steel metal, elegant, sharp focus, soft lighting, vibrant colors"
+n_prompt = "ugly, deformed, noisy, blurry, nsfw, low contrast, text, BadDream, 3d, cgi, render, fake, anime, open mouth, big forehead, long neck"
+width, height = 640, 384
+
+# Load baseline pipe
+model_name = "lykon-models/dreamshaper-xl-1-0"
+pipe = AutoPipelineForText2Image.from_pretrained(model_name, torch_dtype=torch.float16, variant="fp16").to("cuda")
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++")
+
+# Inference baseline pipe
+image = pipe(prompt, negative_prompt=n_prompt, width=width, height=height, num_inference_steps=25, num_images_per_prompt=4, output_type="pt").images
+save_image(image, f"image_baseline.png", normalize=True, padding=0)
+
+# Load resadapter for baseline
+resadapter_model_name = "resadapter_v1_sdxl"
+pipe.load_lora_weights(
+    hf_hub_download(repo_id="jiaxiangc/res-adapter", subfolder=resadapter_model_name, filename="pytorch_lora_weights.safetensors"), 
+    adapter_name="res_adapter",
+    ) # load lora weights
+pipe.set_adapters(["res_adapter"], adapter_weights=[1.0])
+pipe.unet.load_state_dict(
+    load_file(hf_hub_download(repo_id="jiaxiangc/res-adapter", subfolder=resadapter_model_name, filename="diffusion_pytorch_model.safetensors")),
+    strict=False,
+    ) # load norm weights
+
+# Inference resadapter pipe
+image = pipe(prompt, negative_prompt=n_prompt, width=width, height=height, num_inference_steps=25, num_images_per_prompt=4, output_type="pt").images
+save_image(image, f"image_resadapter.png", normalize=True, padding=0)
\ No newline at end of file