deactivate autograd during validation (#560)

examples/nnp_training.py

@@ -294,6 +294,8 @@ def validate():
     mse_sum = torch.nn.MSELoss(reduction='sum')
     total_mse = 0.0
     count = 0
+    model.train(False)
+    with torch.no_grad():
         for properties in validation:
             species = properties['species'].to(device)
             coordinates = properties['coordinates'].to(device).float()
@@ -301,6 +303,7 @@ def validate():
             _, predicted_energies = model((species, coordinates))
             total_mse += mse_sum(predicted_energies, true_energies).item()
             count += predicted_energies.shape[0]
+    model.train(True)
     return hartree2kcalmol(math.sqrt(total_mse / count))
 
 

examples/nnp_training_force.py

@@ -208,6 +208,8 @@ def validate():
     mse_sum = torch.nn.MSELoss(reduction='sum')
     total_mse = 0.0
     count = 0
+    model.train(False)
+    with torch.no_grad():
         for properties in validation:
             species = properties['species'].to(device)
             coordinates = properties['coordinates'].to(device).float()
@@ -215,6 +217,7 @@ def validate():
             _, predicted_energies = model((species, coordinates))
             total_mse += mse_sum(predicted_energies, true_energies).item()
             count += predicted_energies.shape[0]
+    model.train(True)
     return hartree2kcalmol(math.sqrt(total_mse / count))