Windows下torch_geometric的CPU版本安装

学习GNN的时候尝试在线安装torch_geometric ，自己安装过程中出现了挺多问题，找到官网后按照其指示最后成功在线安装（官网链接：torch-geometric · PyPI )

以下是我的安装流程：

先激活环境：

conda activate py37

由于我安装的是：PyTorch 1.10.0，故需要执行以下的操作：

pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+cpu.html
pip install torch-sparse -f https://data.pyg.org/whl/torch-1.10.0+cpu.html
pip install torch-geometric

按照官网上的说明，以下为选择性安装部分(torch-cluster和torch-spline-conv)：

pip install torch-cluster -f https://data.pyg.org/whl/torch-1.10.0+cpu.html
pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.10.0+cpu.html

 

 

最后我们测试一下是否成功安装：

测试代码如下：（直接利用官网上提供的测试代码）

import torch
from torch import Tensor
from torch.nn import Sequential, Linear, ReLU
from torch_geometric.nn import MessagePassing

class EdgeConv(MessagePassing):
    def __init__(self, in_channels, out_channels):
        super().__init__(aggr="max")  # "Max" aggregation.
        self.mlp = Sequential(
            Linear(2 * in_channels, out_channels),
            ReLU(),
            Linear(out_channels, out_channels),
        )

    def forward(self, x: Tensor, edge_index: Tensor) -> Tensor:
        # x: Node feature matrix of shape [num_nodes, in_channels]
        # edge_index: Graph connectivity matrix of shape [2, num_edges]
        return self.propagate(edge_index, x=x)  # shape [num_nodes, out_channels]

    def message(self, x_j: Tensor, x_i: Tensor) -> Tensor:
        # x_j: Source node features of shape [num_edges, in_channels]
        # x_i: Target node features of shape [num_edges, in_channels]
        edge_features = torch.cat([x_i, x_j - x_i], dim=-1)
        return self.mlp(edge_features)  # shape [num_edges, out_channels]

运行结果如下：

Bingo!