Loading deepchem/models/torch_models/attentivefp.py +1 −1 Original line number Diff line number Diff line Loading @@ -308,7 +308,7 @@ class AttentiveFPModel(TorchModel): ([], labels, weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights deepchem/models/torch_models/gat.py +1 −1 Original line number Diff line number Diff line Loading @@ -369,7 +369,7 @@ class GATModel(TorchModel): weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights deepchem/models/torch_models/mpnn.py +1 −1 Original line number Diff line number Diff line Loading @@ -307,7 +307,7 @@ class MPNNModel(TorchModel): weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights Loading
deepchem/models/torch_models/attentivefp.py +1 −1 Original line number Diff line number Diff line Loading @@ -308,7 +308,7 @@ class AttentiveFPModel(TorchModel): ([], labels, weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights
deepchem/models/torch_models/gat.py +1 −1 Original line number Diff line number Diff line Loading @@ -369,7 +369,7 @@ class GATModel(TorchModel): weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights
deepchem/models/torch_models/mpnn.py +1 −1 Original line number Diff line number Diff line Loading @@ -307,7 +307,7 @@ class MPNNModel(TorchModel): weights)) # torch.nn.CrossEntropy expects the last dimension of labels to be non-singleton if labels[0].shape[-1] == 1: if labels[0].shape[-1] == 1 and self.model.mode == 'classification': labels = [lbl.squeeze(-1) for lbl in labels] return inputs, labels, weights
