或者,根据你的PyTorch版本和CUDA版本,你可能需要从PyTorch Geometric的官方GitHub页面下载对应的whl文件并手动安装。 检查Python环境和库版本兼容性: 如果你已经安装了torch_geometric但仍然无法导入GCNConv,可能是因为你的Python环境或库版本不兼容。请确保你的PyTorch版本与torch_geometric版本兼容。你可以查看torch_geometric...
将上面例子中的torch.nn.Linear替换成torch_geometric.nn.GCNConv,我们就可以得到一个GCN图神经网络,如下方代码所示: from torch_geometric.nn import GCNConv class GCN(torch.nn.Module): def __init__(self, hidden_channels): super(GCN, self).__init__() torch.manual_seed(12345) self.conv1 = GCN...
from torch_geometric.nn import GCNConvimport torch.nn.functional as Fclass GCN(torch.nn.Module): def __init__(self): super().__init__() self.conv1 = GCNConv(dataset.num_node_features, 16) self.conv2 = GCNConv(16, dataset.num_classes) def forward(self, data): ...
import torch from torch_geometric.nn import MessagePassing from torch_geometric.utils import add_self_loops, degree class GCNConv(MessagePassing): def __init__(self, in_channels, out_channels): super(GCNConv, self).__init__(aggr='add') self.lin = torch.nn.Linear(in_channels, out_channe...
步骤3:安装torch-geometric库一旦PyTorch和驱动程序安装完成,就可以开始安装torch-geometric库了。运行以下命令进行安装: pip install torch-geometric 步骤4:测试代码最后,为了验证安装是否成功,你可以运行以下Python代码来测试torch-geometric库是否可以正常工作: import torch from torch_geometric.nn import GCNConv, Seque...
append(nn.Sequential(nn.utils.weight_norm(conv), GeLU())) self.model = nn.ModuleList(convs) Example #24Source File: sort_pool.py From pytorch_geometric with MIT License 5 votes def __init__(self, dataset, num_layers, hidden): super(SortPool, self).__init__() self.k = 30 self...
我使用了来自负载CSV的pyG,并试图将它合并到他们的GCN实现中。我知道在最初的实现中,他们使用了相同的数据集,但我想尝试使用自定义数据(稍后加载数据集)。 使用与输入大小不同的目标大小(torch.Size(80670,1)) (torch.Size(80670))。这可能会导致广播结果不正确。请确保它们的尺寸相同。 问题出现了:打印(数据...
manual_seed(12345) conv2 = FastRGCNConv(4, 32, 4, num_bases, num_blocks) out1 = conv1(x1, edge_index, edge_type) out2 = conv2(x1, edge_index, edge_type) assert torch.allclose(out1, out2, atol=1e-6) Example #19Source File: test_agnn_conv.py From pytorch_geometric with ...
Source File: test_gcn_conv.py From pytorch_geometric with MIT License 5 votes def test_gcn_conv_with_sparse_input_feature(): x = torch.sparse_coo_tensor(indices=torch.tensor([[0, 0], [0, 1]]), values=torch.tensor([1., 1.]), size=torch.Size([4, 16])) edge_index = torch...
GCNConv (torch.geometric) (仅个人记录使用) Code from: Creating Message Passing Networkspytorch-geometric.readthedocs.io/en/latest/notes/create_gnn.html?highlight=gcn#the-messagepassing-base-class Try step by step (modified from the original code)...