# <div align="center"><strong>torch-sparse-0.6.13</strong></div>
## 简介
torch-sparse是PyTorch的一个扩展库，用于处理稀疏数据。它提供了一些功能强大的稀疏矩阵操作，以及能够高效执行稀疏计算的函数和工具。

## 依赖安装
+ pytorch1.10或者pytorch1.13 以及对应的torchvision（建议dtk-22.04.2、dtk-23.04与dtk-23.10）
+ python 3.7-3.10

### 1、使用源码编译方式安装

#### 编译环境准备
提供2种环境准备方式：

1. 基于光源pytorch基础镜像环境：镜像下载地址：[https://sourcefind.cn/#/image/dcu/pytorch](https://sourcefind.cn/#/image/dcu/pytorch)，根据pytorch、python、dtk及系统下载对应的镜像版本。

2. 基于现有python环境：安装pytorch和torchvision，whl包下载目录：[https://cancon.hpccube.com:65024/4/main/pytorch](https://cancon.hpccube.com:65024/4/main/pytorch)，[https://cancon.hpccube.com:65024/4/main/vision](https://cancon.hpccube.com:65024/4/main/vision)，根据python、dtk版本,下载对应pytorch和torchvision的whl包。安装命令如下：
```shell
pip install torch* (下载的torch的whl包)
pip install torchvision* (下载的torchvision的whl包)
pip install setuptools==59.5.0 wheel
```

#### 源码编译安装
- 代码下载
```shell
git clone http://developer.hpccube.com/codes/aicomponent/torch-sparce # 根据编译需要切换分支
```
- 源码编译（进入torch-sparse目录）：
```
export C_INCLUDE_PATH=/public/software/apps/DeepLearning/PyTorch_Lib/gflags-2.1.2-build/include:$C_INCLUDE_PATH
export CPLUS_INCLUDE_PATH=/public/software/apps/DeepLearning/PyTorch_Lib/gflags-2.1.2-build/include:$CPLUS_INCLUDE_PATH
export C_INCLUDE_PATH=/public/software/apps/DeepLearning/PyTorch_Lib/glog-build/include:$C_INCLUDE_PATH
export CPLUS_INCLUDE_PATH=/public/software/apps/DeepLearning/PyTorch_Lib/glog-build/include:$CPLUS_INCLUDE_PATH
export C_INCLUDE_PATH=$ROCM_PATH/rocrand/include:$C_INCLUDE_PATH
export CPLUS_INCLUDE_PATH=$ROCM_PATH/rocrand/include:$CPLUS_INCLUDE_PATH
export LD_LIBRARY_PATH=$ROCM_PATH/rocrand/lib:$LD_LIBRARY_PATH
export FORCE_ONLY_HIP=1
export CC=hipcc
export CXX=hipcc

python setup.py install
```
#### 注意事项
+ 若使用pip install下载安装过慢，可添加pypi清华源：-i https://pypi.tuna.tsinghua.edu.cn/simple/
+ ROCM_PATH为dtk的路径，默认为/opt/dtk

## 验证

```python
import torch
from torch_sparse import coalesce

index = torch.tensor([[1, 0, 1, 0, 2, 1],
                      [0, 1, 1, 1, 0, 0]])
value = torch.Tensor([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]])

index, value = coalesce(index, value, m=3, n=2)
```

```
print(index)
tensor([[0, 1, 1, 2],
        [1, 0, 1, 0]])
print(value)
tensor([[6.0, 8.0],
        [7.0, 9.0],
        [3.0, 4.0],
        [5.0, 6.0]])
```

## Known Issue
- 该库没有基于cpu环境修改，仅支持dcu，请在有dcu卡的环境运行。
- 如需完整使用所有pyg功能，请pip install torch-geometric

## 参考资料
- [README_ORIGIN](README_ORIGIN.md)
- [https://pypi.org/project/torch-sparse/0.6.13/](https://pypi.org/project/torch-sparse/0.6.13/)