KeyError: 'graph' in Tutorials :Property Prediction

[Yongrui-Wang]

When running the following code

from torchdrug import utils
from torch.nn import functional as F
samples = []
categories = set()
for sample in valid_set:
    sample.pop("graph")
    category = tuple(sample.values())
    if category not in categories:
        categories.add(category)
        samples.append(sample)
samples = data.graph_collate(samples)
samples = utils.cuda(samples)

preds = F.sigmoid(task.predict(samples))
targets = task.target(samples)

titles = []
for pred, target in zip(preds, targets):
    pred = ", ".join(["%.2f" % p for p in pred])
    target = ", ".join(["%d" % t for t in target])
    titles.append("predict: %s\ntarget: %s" % (pred, target))
graph = samples["graph"]
graph.visualize(titles, figure_size=(3, 3.5), num_row=1)

The following error occurred：

Traceback (most recent call last):
  File "/home/ibmc-2/Projects/MNIST/mnist_data/5-2.py", line 46, in <module>
    preds = F.sigmoid(task.predict(samples))
  File "/home/ibmc-2/anaconda3/envs/td/lib/python3.8/site-packages/torchdrug-0.1.0-py3.8.egg/torchdrug/tasks/property_prediction.py", line 104, in predict
    graph = batch["graph"]
KeyError: 'graph'

Since I'm just getting started, the question may be absurd. Thank you

[KiddoZhu]

Hi! I think the reason is due to the line sample.pop("graph"). You may try to remove this line and run it again.

We will also check this and update the tutorial accordingly.

[Yongrui-Wang]

Thank you, we can copy the 'sample' dictionary 'sample_1', and using sample_1.pop("graph") to filter, but the dict "samples" which will be predicted add a complete "sample" with graph information

for sample in valid_set:
    sample_1 = sample.copy()
    sample_1.pop("graph")
    category = tuple(sample_1.values())
    if category not in categories:
        categories.add(category)
        samples.append(sample)

[KiddoZhu]

Yes. That's a good idea. We will update this part in the tutorial.

[KiddoZhu]

Fixed in a12bbd3.