Loading model state_dict in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the saved model weights into the model.

PyTorch

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

Drag options to blanks, or click blank then click option'

Aload_state_dict

Bsave_state_dict

Csave_weights

Dload_weights

Attempts:

3 left

💡 Hint

Common Mistakes

Using save_state_dict instead of load_state_dict

Trying to load weights with a method that doesn't exist

The method load_state_dict loads the saved weights into the model.

2fill in blank

medium

Complete the code to load the model weights onto the CPU device.

PyTorch

state_dict = torch.load('model_weights.pth', map_location=[1])
model.load_state_dict(state_dict)

Drag options to blanks, or click blank then click option'

A'cpu'

B'cuda'

C'gpu'

D'device'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'cuda' when no GPU is available

Using an invalid device string like 'gpu'

Using map_location='cpu' loads the model weights onto the CPU device.

3fill in blank

hard

Fix the error in loading the model weights by completing the code.

PyTorch

model = MyModel()
state_dict = torch.load('weights.pth')
model.[1](state_dict, strict=False)

Drag options to blanks, or click blank then click option'

Aload_weights

Bload_model

Cload_state_dict

Dload_params

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent method like load_weights

Not passing the state dictionary to the correct method

The correct method to load weights is load_state_dict, which accepts the state dictionary.

4fill in blank

hard

Fill both blanks to load the model weights and set the model to evaluation mode.

PyTorch

model = MyModel()
model.[1](torch.load('model.pth'))
model.[2]()

Drag options to blanks, or click blank then click option'

Aload_state_dict

Btrain

Ceval

Dsave_state_dict

Attempts:

3 left

💡 Hint

Common Mistakes

Calling train() instead of eval() after loading weights

Using save_state_dict instead of load_state_dict

First, load_state_dict loads the weights, then eval() sets the model to evaluation mode.

5fill in blank

hard

Fill all three blanks to load the model weights, move the model to GPU, and set it to evaluation mode.

PyTorch

model = MyModel()
model.[1](torch.load('weights.pth', map_location=[2]))
model.to([3])
model.eval()

Drag options to blanks, or click blank then click option'

Aload_state_dict

B'cpu'

C'cuda'

Dsave_state_dict

Attempts:

3 left

💡 Hint

Common Mistakes

Loading weights directly on GPU without map_location

Using save_state_dict instead of load_state_dict

Moving model to 'cpu' instead of 'cuda'

Load weights with load_state_dict, load them on CPU with map_location='cpu', then move model to GPU with to('cuda').