torch_geometric.transforms 中的 AttributeError

Posted 2023-03-12

【中文标题】torch_geometric.transforms 中的 AttributeError

【英文标题】：AttributeError in torch_geometric.transforms

【发布时间】：2021-07-07 21:02:57

【问题描述】：

我有一个我无法理解的问题：即使模块“torch_geometric.transforms”根据documentation 具有属性“AddTrainValTestMask”，我也无法导入它。我不断收到错误AttributeError: module 'torch_geometric.transforms' has no attribute 'AddTrainValTestMask

我的 Pytorch 版本是 1.7.1

我从here获取代码

最小可重现示例：

import os.path as osp

import torch
import torch.nn.functional as F
from torch_geometric.datasets import Planetoid
import torch_geometric.transforms as T
from torch_geometric.nn import SplineConv

dataset = 'Cora'
transform = T.Compose([
    T.AddTrainValTestMask('train_rest', num_val=500, num_test=500),
    T.TargetIndegree(),
])
path = osp.join(osp.dirname(osp.realpath(__file__)), '..', 'data', dataset)
dataset = Planetoid(path, dataset, transform=transform)
data = dataset[0]


class Net(torch.nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = SplineConv(dataset.num_features, 16, dim=1, kernel_size=2)
        self.conv2 = SplineConv(16, dataset.num_classes, dim=1, kernel_size=2)

    def forward(self):
        x, edge_index, edge_attr = data.x, data.edge_index, data.edge_attr
        x = F.dropout(x, training=self.training)
        x = F.elu(self.conv1(x, edge_index, edge_attr))
        x = F.dropout(x, training=self.training)
        x = self.conv2(x, edge_index, edge_attr)
        return F.log_softmax(x, dim=1)


device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model, data = Net().to(device), data.to(device)
optimizer = torch.optim.Adam(model.parameters(), lr=0.01, weight_decay=5e-3)


def train():
    model.train()
    optimizer.zero_grad()
    F.nll_loss(model()[data.train_mask], data.y[data.train_mask]).backward()
    optimizer.step()


def test():
    model.eval()
    log_probs, accs = model(), []
    for _, mask in data('train_mask', 'test_mask'):
        pred = log_probs[mask].max(1)[1]
        acc = pred.eq(data.y[mask]).sum().item() / mask.sum().item()
        accs.append(acc)
    return accs


for epoch in range(1, 201):
    train()
    log = 'Epoch: :03d, Train: :.4f, Test: :.4f'
    print(log.format(epoch, *test()))

谁能给我解释一下这个问题？

【问题讨论】：

你能添加整个错误回溯吗？

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-57-3f3a1b763433> in <module> 9 dataset = 'Cora' 10 transform = T.Compose([ ---> 11 T.AddTrainValTestMask('train_rest', num_val=500, num_test=500), 12 T.TargetIndegree(), 13 ]) AttributeError: module 'torch_geometric.transforms' has no attribute 'AddTrainValTestMask'

【参考方案1】：

在最新版本的 torch_geometric 中已将其重命名为 RandomNodeSplit。可以直接用RandomNodeSplit替换。