Update README.md

README_.md

+# <div align="center"><strong>torch-spline-conv-1.2.1</strong></div>
+## 简介
+torch-spline-conv是基于PyTorch框架的一个软件包，用于实现图卷积神经网络中的Spline卷积操作。图卷积神经网络是一种能够在图结构数据上进行深度学习的模型，适用于节点分类、图分类和图生成等任务。
+
+## 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-spline-conv # 根据编译需要切换分支
+```
+- 源码编译（进入torch-spline-conv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_spline_conv import spline_conv
+
+x = torch.rand((4, 2), dtype=torch.float)  # 4 nodes with 2 features each
+edge_index = torch.tensor([[0, 1, 1, 2, 2, 3], [1, 0, 2, 1, 3, 2]])  # 6 edges
+pseudo = torch.rand((6, 2), dtype=torch.float)  # two-dimensional edge attributes
+weight = torch.rand((25, 2, 4), dtype=torch.float)  # 25 parameters for in_channels x out_channels
+kernel_size = torch.tensor([5, 5])  # 5 parameters in each edge dimension
+is_open_spline = torch.tensor([1, 1], dtype=torch.uint8)  # only use open B-splines
+degree = 1  # B-spline degree of 1
+norm = True  # Normalize output by node degree.
+root_weight = torch.rand((2, 4), dtype=torch.float)  # separately weight root nodes
+bias = None  # do not apply an additional bias
+
+out = spline_conv(x, edge_index, pseudo, weight, kernel_size,
+                  is_open_spline, degree, norm, root_weight, bias)
+
+print(out.size())
+torch.Size([4, 4])  # 4 nodes with 4 features each
+```
+
+## 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/)

README_HIP.md

-**编译安装步骤**
-
-
-- 1. 安装与dtk版本对应的pytorch torchvision whl（可在光合社区下载https://developer.hpccube.com/tool/）以及其他依赖库
-    
-
-    例如：
-  
-    pip install https://cancon.hpccube.com:65024/directlink/4/pytorch/dtk22.10/torch-1.10.0a0+git2040069.dtk2210-cp38-cp38-manylinux2014_x86_64.whl
-  
-    pip install https://cancon.hpccube.com:65024/directlink/4/vision/dtk22.10/torchvision-0.10.0a0+e04d001.dtk2210-cp38-cp38-manylinux2014_x86_64.whl
-    
-    pip install -r requirements.txt
-
-- 2. 添加编译时的conda环境及部分库的环境变量
-    
-    - 2.1 激活对应的conda环境：
-
- 
-      source ~/miniconda3/etc/profile.d/conda.sh
-
-      conda activate torch1.10_py39_dtk22.10
-
-    - 2.2 加载对应的module，包括dtk：
-
- 
-      module purge
-
-      module load compiler/devtoolset/7.3.1 mpi/hpcx/gcc-7.3.1 compiler/dtk/22.10.1
-
-      module list
-
-    - 2.3 加载所需的依赖库的环境变量（根据各集群实际路径调整）：
-
- 
-      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
-
-    - 2.4 修改编译器环境变量：
-  
-
-      export FORCE_ONLY_HIP=1
-
-      export CC=hipcc
-
-      export CXX=hipcc
-
-- 3. 编译安装
-  
-
-      python setup.py install