TypeError while trying to run ./run_DGCNN.sh

While trying to run ./run_DGCNN.sh I get the same error each time I run for different datasets: TypeError: new(): data must be a sequence (got dict_values)

>> ./run_DGCNN.sh

====== begin of s2v configuration ======
| msg_average = 0
======   end of s2v configuration ======
Namespace(batch_size=50, data='DD', dropout=True, extract_features=False, feat_dim=0, fold=1, gm='DGCNN', hidden=128, latent_dim=[32, 32, 32, 1], learning_rate=1e-05, max_lv=4, mode='cpu', num_class=0, num_epochs=200, out_dim=0, printAUC=False, seed=1, sortpooling_k=0.6, test_number=0)
loading data
# classes: 2
# maximum node tag: 82
# train: 1061, # test: 117
k used in SortPooling is: 291
Initializing DGCNN
  0%|                                                                                                                                                                 | 0/21 [00:00<?, ?batch/s]Traceback (most recent call last):
  File "main.py", line 187, in <module>
    avg_loss = loop_dataset(train_graphs, classifier, train_idxes, optimizer=optimizer)
  File "main.py", line 131, in loop_dataset
    logits, loss, acc = classifier(batch_graph)
  File "/home/egorc/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "main.py", line 107, in forward
    embed = self.s2v(batch_graph, node_feat, None)
  File "/home/egorc/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/egorc/pytorch_DGCNN/DGCNN_embedding.py", line 53, in forward
    node_degs = [torch.Tensor(graph_list[i].degs) + 1 for i in range(len(graph_list))]
  File "/home/egorc/pytorch_DGCNN/DGCNN_embedding.py", line 53, in <listcomp>
    node_degs = [torch.Tensor(graph_list[i].degs) + 1 for i in range(len(graph_list))]
TypeError: new(): data must be a sequence (got dict_values)

Steps to reproduce:

• Install DGCNN:
  • Clone repository
  • unzip pytorch_structure2vec-master.zip
  • cd pytorch_structure2vec-master/s2vlib/
  • make -j4
  • cd ../..
• Change python to python3 in run_DGCNN.sh
• Change gpu_or_cpu=gpu to gpu_or_cpu=cpu in run_DGCNN.sh
• Comment import cPickle as cp
• Uncomment import _pickle as cp # python3 compatability in util.py
• Run ./run_DGCNN.sh

Environment: Distributor ID: Ubuntu Description: Ubuntu 16.04.5 LTS Release: 16.04 Codename: xenial Python version: Python 3.5.2 Packages: absl-py (0.5.0) astor (0.7.1) autokeras (0.2.18) blinker (1.3) boto (2.38.0) chardet (2.3.0) cloud-init (18.3) command-not-found (0.3) configobj (5.0.6) cryptography (1.2.3) decorator (4.3.0) gast (0.2.0) google-compute-engine (2.8.2) grpcio (1.15.0) h5py (2.8.0) idna (2.0) Jinja2 (2.8) jsonpatch (1.10) jsonpointer (1.9) Keras (2.2.2) Keras-Applications (1.0.4) Keras-Preprocessing (1.0.2) language-selector (0.1) Markdown (3.0.1) MarkupSafe (0.23) networkx (2.2) numpy (1.15.2) oauthlib (1.0.3) Pillow (5.3.0) pip (8.1.1) prettytable (0.7.2) protobuf (3.6.1) pyasn1 (0.1.9) pycurl (7.43.0) pygobject (3.20.0) PyJWT (1.3.0) pyserial (3.0.1) python-apt (1.1.0b1+ubuntu0.16.4.2) python-debian (0.1.27) python-systemd (231) PyYAML (3.13) requests (2.9.1) scikit-learn (0.20.0) scipy (1.1.0) setuptools (39.1.0) six (1.11.0) sklearn (0.0) ssh-import-id (5.5) tensorboard (1.11.0) tensorflow (1.11.0) termcolor (1.1.0) torch (0.4.1) torchvision (0.2.1) tqdm (4.25.0) ufw (0.35) unattended-upgrades (0.1) urllib3 (1.13.1) Werkzeug (0.14.1) wheel (0.32.1)

[muhanzhang]

Hi, have you tried updating your networkx to the latest version? After that, can you construct a toy graph and call “g.degree” and “g.degree()” to see what happens?

[muhanzhang]

Please change the line 51 of util.py from “self.degs = dict(g.degree).values()” to “self.degs = list(dict(g.degree).values())”. The issue is because python3 returns a dict_values type instead of list when you call dict.values().