Question

我遇到属性错误，但是即使查看了多个以前的帖子，也无法弄清楚原因。

import math
import time
import random
import os, sys
import os.path as osp
from itertools import chain
from shutil import copy
import copy as cp
from tqdm import tqdm
import pdb

import numpy as np
from sklearn.metrics import roc_auc_score
import scipy.sparse as ssp
import torch
import torch.nn.functional as F
from torch.nn import BCEWithLogitsLoss
from torch.nn import ModuleList, Linear, Conv1d, MaxPool1d, Embedding
from torch.utils.data import DataLoader

from torch_sparse import coalesce
from torch_scatter import scatter_min
import torch_geometric.transforms as T
from torch_geometric.nn import GCNConv, SAGEConv, global_sort_pool, global_add_pool
from torch_geometric.data import Data, Dataset, InMemoryDataset, DataLoader
from torch_geometric.utils import (negative_sampling, add_self_loops,
                                   train_test_split_edges, to_networkx, 
                                   to_scipy_sparse_matrix, to_undirected)

import warnings
from scipy.sparse import SparseEfficiencyWarning
warnings.simplefilter('ignore',SparseEfficiencyWarning)

from enclosing_subgraph import *

class WLDynamicDataset(Dataset):
    def __init__(self, root, data, split_edge, num_hops, percent=100, split='train', 
                 use_coalesce=False, node_label='drnl', ratio_per_hop=1.0, 
                 max_nodes_per_hop=None, **kwargs):
        self.data = data
        self.split_edge = split_edge
        self.num_hops = num_hops
        self.percent = percent
        self.use_coalesce = use_coalesce
        self.node_label = node_label
        self.ratio_per_hop = ratio_per_hop
        self.max_nodes_per_hop = max_nodes_per_hop
        super(WLDynamicDataset, self).__init__(root)

        pos_edge, neg_edge = get_pos_neg_edges(split, self.split_edge, 
                                               self.data.edge_index, 
                                               self.data.num_nodes, 
                                               self.percent)
        self.links = torch.cat([pos_edge, neg_edge], 1).t().tolist()
        self.labels = [1] * pos_edge.size(1) + [0] * neg_edge.size(1)
        
        if self.use_coalesce:  # compress mutli-edge into edge with weight
            self.data.edge_index, self.data.edge_weight = coalesce(
                self.data.edge_index, self.data.edge_weight, 
                self.data.num_nodes, self.data.num_nodes)

        if 'edge_weight' in self.data:
            edge_weight = self.data.edge_weight.view(-1)
        else:
            edge_weight = torch.ones(self.data.edge_index.size(1), dtype=int)
        self.A = ssp.csr_matrix(
            (edge_weight, (self.data.edge_index[0], self.data.edge_index[1])), 
            shape=(self.data.num_nodes, self.data.num_nodes)
        )
        
    def __len__(self):
        return len(self.links)

    def process(self):
        for idx in range(len(self.links)):
            src, dst = self.links[idx]

            if self.labels[idx]: status = "pos"
            else: status = "neg"

            tmp = k_hop_subgraph(src, dst, self.num_hops, self.A, status, self.ratio_per_hop, 
                                 self.max_nodes_per_hop, node_features=self.data.x)
            data = construct_pyg_graph(*tmp, self.node_label)

            torch.save(data, osp.join(self.processed_dir, 'data_{}.pt'.format(idx)))

    def get(self, idx):
        data = torch.load(osp.join(self.processed_dir, 'data_{}.pt'.format(idx)))
        return data

我收到此错误：

Traceback (most recent call last):
  File "/path/to/run.py", line 302, in <module>
    main()
  File "/path/to/run.py", line 79, in main
    max_nodes_per_hop=args.max_nodes_per_hop,
  File "/path/to/DataSet.py", line 106, in __init__
    super(WLDynamicDataset, self).__init__(root)
  File "/n/home01/vym1/.local/lib/python3.7/site-packages/torch_geometric/data/dataset.py", line 92, in __init__
    self._process()
  File "/n/home01/vym1/.local/lib/python3.7/site-packages/torch_geometric/data/dataset.py", line 165, in _process
    self.process()
  File "/path/to/DataSet.py", line 137, in process
    for idx in range(len(self.links)):
AttributeError: 'WLDynamicDataset' object has no attribute 'links'

我在类的开头（即self.links）中明确定义了它。不知道为什么它不会显示。有人知道为什么吗？

更新：添加了导入和完整的追溯。 run.py是我运行的脚本，该脚本称为DataSet.py

Answer 1

TL; DR：

更改您的process方法的名称。或者，如果您有意覆盖它，请确保在调用self.links之前在__init__中定义了super()。

您已覆盖__init__的{{1}}内部正在调用的方法。您的DataSet的简化版本是：

__init__

现在，从追溯开始，您将拥有以下从class WLDynamicDataset(Dataset): def __init__(...): ... super(WLDynamicDataset, self).__init__(root) ... self.links = torch.cat([pos_edge, neg_edge], 1).t().tolist()调用开始的堆栈：

super()

然后您在WLDynamicDataset.__init__ --> super(WLDynamicDataset, self).__init__(root) => Dataset.__init__ --> self._process() => Dataset._process --> self.process() => WLDynamicDataset.process --> self.links中定义之前在self.links中引用process。

对象没有属性？

1 个答案:

TL; DR：