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文档环境安装上手
This commit is contained in:
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docs/zh/Pipeline_Usage/Setup_NPU_doc.md
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55
docs/zh/Pipeline_Usage/Setup_NPU_doc.md
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# 安装依赖
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从源码安装(推荐):
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```
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git clone https://github.com/modelscope/DiffSynth-Studio.git
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cd DiffSynth-Studio
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pip install -e .
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```
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从 pypi 安装(存在版本更新延迟,如需使用最新功能,请从源码安装)
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```
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pip install diffsynth
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```
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## GPU/NPU 支持
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* NVIDIA GPU
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按照以上方式安装即可。
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* AMD GPU
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需安装支持 ROCm 的 `torch` 包,以 ROCm 6.4(本文更新于 2025 年 12 月 15 日)、Linux 系统为例,请运行以下命令
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```shell
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pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm6.4
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```
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* Ascend NPU
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1. 通过官方文档安装[CANN](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/softwareinst/instg/instg_quick.html?Mode=PmIns&InstallType=local&OS=openEuler&Software=cannToolKit)
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2. 根据[安装依赖](#安装依赖)安装diffsynth仓
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3. 安装torch-npu仓。Ascend NPU 通过 `torch-npu` 包提供支持,以 `2.7.1` 版本(本文更新于 2025 年 12 月 15 日)为例,请运行以下命令
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```shell
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# aarch64/ARM
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pip install torch-npu==2.7.1 torchvision==0.22.1
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# x86
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pip install torch==2.7.1+cpu torchvision==0.22.1+cpu --extra-index-url "https://download.pytorch.org/whl/cpu"
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pip install torch-npu==2.7.1
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```
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使用 Ascend NPU 时,请将 Python 代码中的 `"cuda"` 改为 `"npu"`,详见[NPU 支持](/docs/zh/Pipeline_Usage/GPU_support.md#ascend-npu)。
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## 其他安装问题
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如果在安装过程中遇到问题,可能是由上游依赖包导致的,请参考这些包的文档:
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* [torch](https://pytorch.org/get-started/locally/)
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* [Ascend/pytorch](https://github.com/Ascend/pytorch)
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* [sentencepiece](https://github.com/google/sentencepiece)
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* [cmake](https://cmake.org)
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56
docs/zh/Pipeline_Usage/Setup_NPU_pip.md
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56
docs/zh/Pipeline_Usage/Setup_NPU_pip.md
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@@ -0,0 +1,56 @@
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# 安装依赖
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从源码安装(推荐):
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```
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git clone https://github.com/modelscope/DiffSynth-Studio.git
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cd DiffSynth-Studio
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pip install -e .
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```
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从 pypi 安装(存在版本更新延迟,如需使用最新功能,请从源码安装)
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```
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pip install diffsynth
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```
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## GPU/NPU 支持
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* NVIDIA GPU
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按照以上方式安装即可。
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* AMD GPU
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需安装支持 ROCm 的 `torch` 包,以 ROCm 6.4(本文更新于 2025 年 12 月 15 日)、Linux 系统为例,请运行以下命令
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```shell
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pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm6.4
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```
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* Ascend NPU
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1. 通过官方文档安装[CANN](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/softwareinst/instg/instg_quick.html?Mode=PmIns&InstallType=local&OS=openEuler&Software=cannToolKit)
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2. 从源码安装
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```shell
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git clone https://github.com/modelscope/DiffSynth-Studio.git
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cd DiffSynth-Studio
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# aarch64/ARM
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pip install -e .[npu_aarch64] --extra-index-url "https://download.pytorch.org/whl/cpu"
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# x86
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pip install -e .[npu]
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```
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使用 Ascend NPU 时,请将 Python 代码中的 `"cuda"` 改为 `"npu"`,详见[NPU 支持](/docs/zh/Pipeline_Usage/GPU_support.md#ascend-npu)。
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## 其他安装问题
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如果在安装过程中遇到问题,可能是由上游依赖包导致的,请参考这些包的文档:
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* [torch](https://pytorch.org/get-started/locally/)
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* [Ascend/pytorch](https://github.com/Ascend/pytorch)
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* [sentencepiece](https://github.com/google/sentencepiece)
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* [cmake](https://cmake.org)
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@@ -10,8 +10,6 @@ authors = [{name = "ModelScope Team"}]
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license = {text = "Apache-2.0"}
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license = {text = "Apache-2.0"}
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requires-python = ">=3.10"
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requires-python = ">=3.10"
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dependencies = [
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dependencies = [
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"torch>=2.0.0",
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"torchvision",
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"transformers",
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"transformers",
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"imageio",
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"imageio",
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"imageio[ffmpeg]",
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"imageio[ffmpeg]",
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"Operating System :: OS Independent",
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"Operating System :: OS Independent",
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]
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]
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[project.optional-dependencies]
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gpu = [
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"torch>=2.0.0",
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"torchvision"
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]
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npu_aarch64 = [
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"torch==2.7.1",
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"torch-npu==2.7.1",
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"torchvision==0.22.1"
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]
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npu = [
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"torch==2.7.1+cpu",
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"torch-npu==2.7.1",
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"torchvision==0.22.1+cpu"
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]
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[tool.setuptools.packages.find]
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[tool.setuptools.packages.find]
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[tool.setuptools]
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[tool.setuptools]
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