Best model saving pattern in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to save the model's state dictionary.

PyTorch

torch.save(model.[1](), 'model.pth')

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Astate_dict

Bweights

Cparameters

Dsave_state

Attempts:

3 left

💡 Hint

Common Mistakes

Using model.parameters() instead of model.state_dict()

Trying to save the entire model object directly

In PyTorch, the recommended way to save a model is to save its state_dict(), which contains all the learned parameters.

2fill in blank

medium

Complete the code to load the saved model state dictionary.

PyTorch

model = MyModel()
model.[1](torch.load('model.pth'))

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Aload_parameters

Bload_weights

Cload_model

Dload_state_dict

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.load directly on the model

Calling a non-existent method like load_parameters

To load saved parameters into a PyTorch model, use load_state_dict() with the loaded state dictionary.

3fill in blank

hard

Fix the error in saving the best model during training.

PyTorch

if val_loss < best_loss:
    best_loss = val_loss
    torch.save(model.[1](), 'best_model.pth')

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Asave_state

Bparameters

Cstate_dict

Dweights

Attempts:

3 left

💡 Hint

Common Mistakes

Saving model.parameters() which is a generator, not a dictionary

Saving the whole model object causing large files and incompatibility

Saving the state_dict() ensures only the model parameters are saved, which is the correct way to save the best model.

4fill in blank

hard

Fill both blanks to implement a training loop that saves the best model based on validation accuracy.

PyTorch

best_acc = 0.0
for epoch in range(num_epochs):
    train()
    val_acc = validate()
    if val_acc [1] best_acc:
        best_acc = val_acc
        torch.save(model.[2](), 'best_model.pth')

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A>

B<

Cstate_dict

Dparameters

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for accuracy comparison

Saving model.parameters() instead of state_dict()

We save the model when validation accuracy improves, so the comparison is val_acc > best_acc. The model's state_dict() is saved.

5fill in blank

hard

Fill all three blanks to load the best saved model and evaluate it.

PyTorch

model = MyModel()
model.[1](torch.load('best_model.pth'))
model.[2]()
accuracy = evaluate(model, test_loader)
print(f'Best model test accuracy: [3]')

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Aload_state_dict

Beval

Caccuracy

Dtrain

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to call eval() before evaluation

Trying to print a variable not defined or misspelled

Load the saved parameters with load_state_dict(), set the model to evaluation mode with eval(), then print the accuracy variable.