Custom Dataset class in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the Dataset class from PyTorch.

PyTorch

from torch.utils.data import [1]

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

ADataset

BDataLoader

CTensor

DModule

Attempts:

3 left

💡 Hint

Common Mistakes

Importing DataLoader instead of Dataset

Trying to import Dataset from torch instead of torch.utils.data

The Dataset class is imported from torch.utils.data to create custom datasets.

2fill in blank

medium

Complete the code to define the __len__ method that returns the dataset size.

PyTorch

def __len__(self):
    return [1]

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

Aself.data.size()

Bself.data.shape

Clen(self.data)

Dself.length

Attempts:

3 left

💡 Hint

Common Mistakes

Using self.data.size() which is not valid for lists

Returning self.length without defining it

The __len__ method should return the number of samples, which is the length of the data list.

3fill in blank

hard

Fix the error in the __getitem__ method to return the correct sample.

PyTorch

def __getitem__(self, idx):
    sample = self.data[[1]]
    return sample

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

A0

Bidx + 1

Cself.idx

Didx

Attempts:

3 left

💡 Hint

Common Mistakes

Adding 1 to idx causing index out of range

Using self.idx which is undefined

The index idx should be used directly to access the data at that position.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths for words longer than 3 characters.

PyTorch

lengths = {word: [1] for word in words if [2]

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

Alen(word)

Blen(word) > 3

Cword != ''

Dword.isalpha()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word instead of len(word) as value

Using wrong condition like word != '' which does not filter by length

The dictionary comprehension maps each word to its length using len(word), filtering words longer than 3 characters with len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths for words longer than 4 characters.

PyTorch

result = [1]: [2] for word in words if [3]

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

Aword.upper()

Blen(word)

Clen(word) > 4

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.lower() instead of word.upper() for keys

Filtering with wrong length condition

The comprehension maps the uppercase version of each word to its length, filtering words longer than 4 characters.