Revert "Wan refactor"

examples/wanvideo/wan_14B_flf2v.py

@@ -0,0 +1,52 @@
+import torch
+from diffsynth import ModelManager, WanVideoPipeline, save_video, VideoData
+from modelscope import snapshot_download, dataset_snapshot_download
+from PIL import Image
+
+
+# Download models
+snapshot_download("Wan-AI/Wan2.1-FLF2V-14B-720P", local_dir="models/Wan-AI/Wan2.1-FLF2V-14B-720P")
+
+# Load models
+model_manager = ModelManager(device="cpu")
+model_manager.load_models(
+    ["models/Wan-AI/Wan2.1-FLF2V-14B-720P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth"],
+    torch_dtype=torch.float32, # Image Encoder is loaded with float32
+)
+model_manager.load_models(
+    [
+        [
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00001-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00002-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00003-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00004-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00005-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00006-of-00007.safetensors",
+            "models/Wan-AI/Wan2.1-FLF2V-14B-720P/diffusion_pytorch_model-00007-of-00007.safetensors",
+        ],
+        "models/Wan-AI/Wan2.1-FLF2V-14B-720P/models_t5_umt5-xxl-enc-bf16.pth",
+        "models/Wan-AI/Wan2.1-FLF2V-14B-720P/Wan2.1_VAE.pth",
+    ],
+    torch_dtype=torch.bfloat16, # You can set `torch_dtype=torch.float8_e4m3fn` to enable FP8 quantization.
+)
+pipe = WanVideoPipeline.from_model_manager(model_manager, torch_dtype=torch.bfloat16, device="cuda")
+pipe.enable_vram_management(num_persistent_param_in_dit=None)
+
+# Download example image
+dataset_snapshot_download(
+    dataset_id="DiffSynth-Studio/examples_in_diffsynth",
+    local_dir="./",
+    allow_file_pattern=["data/examples/wan/first_frame.jpeg", "data/examples/wan/last_frame.jpeg"]
+)
+
+# First and last frame to video
+video = pipe(
+    prompt="写实风格，一个女生手持枯萎的花站在花园中，镜头逐渐拉远，记录下花园的全貌。",
+    negative_prompt="色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",
+    num_inference_steps=30,
+    input_image=Image.open("data/examples/wan/first_frame.jpeg").resize((960, 960)),
+    end_image=Image.open("data/examples/wan/last_frame.jpeg").resize((960, 960)),
+    height=960, width=960,
+    seed=1, tiled=True
+)
+save_video(video, "video.mp4", fps=15, quality=5)