Open t-kimber opened 3 years ago
I believe this is the place to report updates with issues in the experiments/001_example-ligand-only-graph-subset.py
, please correct me if I'm wrong and I can raise a new issue if needed.
When trying to build and run the mode I'm facing the current issue:
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AttributeError Traceback (most recent call last)
Cell In[10], line 8
6 a_dataloader = dataloaders[next(iter(dataloaders.keys()))]["train"]
7 x_sample, _ = next(iter(a_dataloader))
----> 8 MODEL_KWARGS["input_shape"] = ModelCls.estimate_input_shape(x_sample)
10 nn_model = ModelCls(**MODEL_KWARGS)
12 optimizer = import_object(OPTIMIZER)(nn_model.parameters(), **OPTIMIZER_KWARGS)
File ~/workdir/repos/kinoml/kinoml/ml/torch_geometric_models.py:34, in GraphConvolutionNeuralNetwork.estimate_input_shape(input_sample)
31 @staticmethod
32 def estimate_input_shape(input_sample):
33 # Take the first batch [0]
---> 34 return input_sample[0].num_node_features
AttributeError: 'Tensor' object has no attribute 'num_node_features'
Which seems to suggest that it's expecting a torch.geometric.Data
object instead of a Tensor
one.
Ligand-based model
Graph
Featurization:
Model: