Loading deepchem/models/torch_models/torch_model.py +3 −3 Original line number Diff line number Diff line Loading @@ -839,17 +839,17 @@ class TorchModel(Model): inputs = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in inputs ] inputs = [torch.as_tensor(x, device=self.device) for x in inputs] inputs = [torch.as_tensor(x, device=self.device).float() for x in inputs] if labels is not None: labels = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in labels ] labels = [torch.as_tensor(x, device=self.device) for x in labels] labels = [torch.as_tensor(x, device=self.device).float() for x in labels] if weights is not None: weights = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in weights ] weights = [torch.as_tensor(x, device=self.device) for x in weights] weights = [torch.as_tensor(x, device=self.device).float() for x in weights] return (inputs, labels, weights) Loading Loading
deepchem/models/torch_models/torch_model.py +3 −3 Original line number Diff line number Diff line Loading @@ -839,17 +839,17 @@ class TorchModel(Model): inputs = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in inputs ] inputs = [torch.as_tensor(x, device=self.device) for x in inputs] inputs = [torch.as_tensor(x, device=self.device).float() for x in inputs] if labels is not None: labels = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in labels ] labels = [torch.as_tensor(x, device=self.device) for x in labels] labels = [torch.as_tensor(x, device=self.device).float() for x in labels] if weights is not None: weights = [ x.astype(np.float32) if x.dtype == np.float64 else x for x in weights ] weights = [torch.as_tensor(x, device=self.device) for x in weights] weights = [torch.as_tensor(x, device=self.device).float() for x in weights] return (inputs, labels, weights) Loading
