Help needed using a molecular dataset

Hello together,

I have created a molecular dataset using:

dataset_train.load_smiles(Strain,targets={"property":Ytrain_full})

Now, when I want to create an Engine from a defined task:

task = tasks.PropertyPrediction(model, task=dataset_train.tasks,
criterion="bce", metric=("auprc", "auroc"),num_class=3)
optimizer = torch.optim.Adam(task.parameters(), lr=1e-3)
solver = core.Engine(task, train_set, valid_set, test_set, optimizer, batch_size=1024)

I receive the following error:

'MoleculeDataset' object has no attribute 'config_dict'

How can I set the config dict using a user defined dataset?

[bananenpampe]

Hello,

for me this fix worked, I assume ther is something wrong eith this wrapper:

from torchdrug.core import Registry as R


@R.register("datasets.Solvation")
class mymoldataset(data.MoleculeDataset):
    def __init__(self,*args,**kwargs):
        super().__init__(*args,**kwargs)

[bananenpampe]

nice!