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## 简介
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**PyTorch3D** 是一个用于深度学习中处理**3D数据**的库。它提供了一系列功能,方便处理和操作三维数据。详细内容请查看[README_ORIGIN.md](README_ORIGIN.md)
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## 安装
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组件支持:
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* Python 3.8,3.9 or 3.10
- dtk-23.10
- pytorch-2.1
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### 1. pip安装
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可以在[光合开发者社区](https://developer.hpccube.com/tool/#sdk) AI 生态包中获取  `pytorch3d` 安装包,注意dtk以及pytorch版本对应。
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```shell
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python -m pip install pytorch3d*.whl
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```

### 2. 源码编译安装

#### 环境准备
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若未安装dtk、torch,可参考以下安装
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*[光合开发者社区](https://developer.hpccube.com/tool/#sdk) DCU Toolkit 中下载 DTK-23.10 解压至 /opt/ 路径下,并建立软链接
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  ```plaintext
  cd /opt && ln -s dtk-23.10 dtk
  ```
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*[光合开发者社区](https://developer.hpccube.com/tool/#sdk) AI 生态包中获取对应的 pytorch-2.1版本(需对应 DCU Toolkit 版本)
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  ```shell
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  cd path/to/torch
  python3 -m pip install torch*
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  ```
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* 导入环境变量以及安装必要依赖库
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  ```shell
  source /opt/dtk/env.sh
  pip3 install wheel -i https://pypi.tuna.tsinghua.edu.cn/simple --trusted-host pypi.tuna.tsinghua.edu.cn
  ```
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#### 编译安装
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* 若使用 `GPU` 支持,需要设置环境变量`FORCE_CUDA`为1
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  ```shell
  export FORCE_CUDA=1
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  # DCU环境下添加以下环境变量
  export HIPCC_COMPILE_FLAGS_APPEND="--gpu-max-threads-per-block=1024"
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  ```
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- 执行编译命令
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  ```shell
  cd path/to/pytorch3d
  pip install -e .
  ```
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#### 注意事项

当出现错误时,参考以下说明:

* 报错提示缺少 `intel-mkl` 相关库,应安装 `intel-mkl` 或 添加库的路径到环境变量

  ```shell
  #安装
  yum-config-manager --add-repo https://yum.repos.intel.com/mkl/setup/intel-mkl.repo
  yum install intel-mkl-2020.0-088 -y --nogpgchec
  
  # 将库路径添加到环境变量中
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/mkl/lib/intel64
  ```

* 缺少 `magma`时,安装对应库或添加环境变量

  ```shell
  # 默认dtk安装路径为 /opt/dtk
  cd /opt/dtk
  
  #安装
  wget http://10.6.10.68:8000/debug/pytorch/third_party/magma_v2.7.2-hip_nfs3.2_DTK23.10_intel-2020.1.217_07Oct2023.tar.gz
  tar -zxf magma_v2.7.2-hip_nfs3.2_DTK23.10_intel-2020.1.217_07Oct2023.tar.gz
  mv magma_v2.7.2-hip_nfs3.2_DTK23.10_intel-2020.1.217_07Oct2023 magma
  
  # 添加环境变量
  export LD_LIBRARY_PATH=${ROCM_PATH}/magma/lib:$LD_LIBRARY_PATH
  ```

## 验证

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* `python -c "import pytorch3d; print(pytorch3d.__version__)"`,版本号与官方版本同步,查询该软件的版本号。
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