no_grad context manager in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to disable gradient calculation during inference.

PyTorch

with torch.[1]():
    output = model(input_tensor)

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

Ano_grad

Bgrad_enabled

Cenable_grad

Dset_grad_enabled

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'enable_grad' instead of 'no_grad' will enable gradients, not disable them.

Forgetting to use a context manager and calculating gradients unnecessarily.

The no_grad context manager disables gradient calculation, which saves memory and computations during inference.

2fill in blank

medium

Complete the code to prevent gradient tracking for the tensor operation.

PyTorch

with torch.no_grad():
    result = tensor.[1](2)

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

Adetach

Bbackward

Crequires_grad_

Dpow

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'backward' which computes gradients, not a tensor operation.

Using 'detach' which returns a tensor without gradient tracking but is not an operation raising to a power.

The pow method raises the tensor to a power. Inside no_grad, this operation won't track gradients.

3fill in blank

hard

Fix the error in the code to correctly disable gradient calculation.

PyTorch

with torch.no_grad[1]:
    prediction = model(data)

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

A[]

B{}

C()

D.

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting parentheses causes a syntax error.

Using square brackets or braces instead of parentheses.

The no_grad context manager must be called with parentheses () to work properly.

4fill in blank

hard

Fill both blanks to create a dictionary of squared values without tracking gradients.

PyTorch

with torch.[1]():
    squares = {x: x[2]2 for x in range(1, 6)}

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

Ano_grad

B**

C*

Denable_grad

Attempts:

3 left

💡 Hint

Common Mistakes

Using '*' instead of '**' for squaring.

Using 'enable_grad' which enables gradients instead of disabling.

Use no_grad to disable gradients and ** to square numbers.

5fill in blank

hard

Fill all three blanks to compute model output without gradients and convert it to a numpy array.

PyTorch

with torch.[1]():
    output = model(input_tensor)
    numpy_output = output.[2]().cpu().[3]()

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

Ano_grad

Bdetach

Cnumpy

Drequires_grad_

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to detach before converting to numpy causes errors.

Using 'requires_grad_' which changes gradient tracking but is not for detaching.

Use no_grad to disable gradients, detach() to get a tensor without gradient tracking, and numpy() to convert to a numpy array.