mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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Zhongjie Duan
GitHub
@@ -140,6 +140,8 @@ graph LR;
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|[PAI/Wan2.2-Fun-A14B-Control-Camera](https://modelscope.cn/models/PAI/Wan2.2-Fun-A14B-Control-Camera)|`control_camera_video`, `input_image`|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_inference/Wan2.2-Fun-A14B-Control-Camera.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/full/Wan2.2-Fun-A14B-Control-Camera.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_full/Wan2.2-Fun-A14B-Control-Camera.py)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/lora/Wan2.2-Fun-A14B-Control-Camera.sh)|[code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_lora/Wan2.2-Fun-A14B-Control-Camera.py)|
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| [openmoss/MOVA-360p](https://modelscope.cn/models/openmoss/MOVA-360p) | `input_image` | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_inference/MOVA-360p-I2AV.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/full/MOVA-360P-I2AV.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/validate_full/MOVA-360p-I2AV.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/lora/MOVA-360P-I2AV.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/validate_lora/MOVA-360p-I2AV.py) |
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| [openmoss/MOVA-720p](https://modelscope.cn/models/openmoss/MOVA-720p) | `input_image` | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_inference/MOVA-720p-I2AV.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/full/MOVA-720P-I2AV.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/validate_full/MOVA-720p-I2AV.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/lora/MOVA-720P-I2AV.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/mova/model_training/validate_lora/MOVA-720p-I2AV.py) |
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| [Wan-AI/WanToDance-14B (global model)](https://modelscope.cn/models/Wan-AI/WanToDance-14B) | `wantodance_music_path`, `wantodance_reference_image`, `wantodance_fps`, `wantodance_keyframes`, `wantodance_keyframes_mask` | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_inference/WanToDance-14B-global.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/full/WanToDance-14B-global.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_full/WanToDance-14B-global.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/lora/WanToDance-14B-global.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_lora/WanToDance-14B-global.py) |
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| [Wan-AI/WanToDance-14B (local model)](https://modelscope.cn/models/Wan-AI/WanToDance-14B) | `wantodance_music_path`, `wantodance_reference_image`, `wantodance_fps`, `wantodance_keyframes`, `wantodance_keyframes_mask` | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_inference/WanToDance-14B-local.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/full/WanToDance-14B-local.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_full/WanToDance-14B-local.py) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/lora/WanToDance-14B-local.sh) | [code](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/validate_lora/WanToDance-14B-local.py) |
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* FP8 精度训练：[doc](../Training/FP8_Precision.md)、[code](https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/wanvideo/model_training/special/fp8_training/)
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* 两阶段拆分训练：[doc](../Training/Split_Training.md)、[code](https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/wanvideo/model_training/special/split_training/)
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@@ -204,6 +206,50 @@ DeepSpeed ZeRO 3 训练：Wan 系列模型支持 DeepSpeed ZeRO 3 训练，将
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如果显存不足，请开启[显存管理](../Pipeline_Usage/VRAM_management.md)，我们在示例代码中提供了每个模型推荐的低显存配置，详见前文"模型总览"中的表格。
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### 多卡并行加速
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如需开启多卡并行加速，请先安装 `flash_attn` 与 `xfuser`：
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```shell
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pip install flash-attn --no-build-isolation
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pip install xfuser
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```
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对代码进行如下修改（[样例代码](https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/wanvideo/acceleration/unified_sequence_parallel.py)）：
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```diff
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import torch
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from PIL import Image
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from diffsynth.utils.data import save_video, VideoData
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from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
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+ import torch.distributed as dist
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pipe = WanVideoPipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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+ use_usp=True,
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model_configs=[
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ModelConfig(model_id="Wan-AI/Wan2.1-T2V-14B", origin_file_pattern="diffusion_pytorch_model*.safetensors"),
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ModelConfig(model_id="Wan-AI/Wan2.1-T2V-14B", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth"),
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ModelConfig(model_id="Wan-AI/Wan2.1-T2V-14B", origin_file_pattern="Wan2.1_VAE.pth"),
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],
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tokenizer_config=ModelConfig(model_id="Wan-AI/Wan2.1-T2V-1.3B", origin_file_pattern="google/umt5-xxl/"),
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)
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video = pipe(
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prompt="一名宇航员身穿太空服，面朝镜头骑着一匹机械马在火星表面驰骋。红色的荒凉地表延伸至远方，点缀着巨大的陨石坑和奇特的岩石结构。机械马的步伐稳健，扬起微弱的尘埃，展现出未来科技与原始探索的完美结合。宇航员手持操控装置，目光坚定，仿佛正在开辟人类的新疆域。背景是深邃的宇宙和蔚蓝的地球，画面既科幻又充满希望，让人不禁畅想未来的星际生活。",
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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",
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seed=0, tiled=True,
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)
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+ if dist.get_rank() == 0:
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+ save_video(video, "video1.mp4", fps=15, quality=5)
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```
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运行多卡并行推理时，请使用 `torchrun` 运行，其中 `--nproc_per_node` 为 GPU 数量：
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```shell
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torchrun --nproc_per_node=8 examples/wanvideo/acceleration/unified_sequence_parallel.py
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```
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## 模型训练
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Wan 系列模型统一通过 [`examples/wanvideo/model_training/train.py`](https://github.com/modelscope/DiffSynth-Studio/blob/main/examples/wanvideo/model_training/train.py) 进行训练，脚本的参数包括：
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