Tensor creation (torch.tensor, zeros, ones, rand) in PyTorch - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a tensor from a list of numbers.

PyTorch

import torch

my_tensor = torch.[1]([1, 2, 3, 4])
print(my_tensor)

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

Aones

Bzeros

Ctensor

Drand

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.zeros or torch.ones instead of torch.tensor.

Trying to call torch.rand with a list argument.

The torch.tensor function creates a tensor from a Python list or array.

2fill in blank

medium

Complete the code to create a 3x3 tensor filled with zeros.

PyTorch

import torch

zero_tensor = torch.[1]((3, 3))
print(zero_tensor)

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

Azeros

Bones

Ctensor

Drand

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.ones instead of torch.zeros.

Passing a list instead of a tuple for the shape.

torch.zeros creates a tensor filled with zeros of the given shape.

3fill in blank

hard

Fix the error in the code to create a 2x4 tensor filled with ones.

PyTorch

import torch

one_tensor = torch.[1]([2, 4])
print(one_tensor)

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

Aones

Btensor

Czeros

Drand

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.tensor instead of torch.ones.

Using torch.zeros which creates zeros instead of ones.

torch.ones creates a tensor filled with ones. The shape must be passed as a tuple, but a list also works here.

4fill in blank

hard

Fill both blanks to create a 4x2 tensor with random values between 0 and 1.

PyTorch

import torch

random_tensor = torch.[1]([2])
print(random_tensor)

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

Arand

B(4, 2)

C[4, 2]

Dones

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.ones instead of torch.rand.

Passing the shape as a list instead of a tuple.

torch.rand creates a tensor with random values between 0 and 1. The shape must be a tuple like (4, 2).

5fill in blank

hard

Fill all three blanks to create a tensor from a list, then create zeros and ones tensors with the same shape.

PyTorch

import torch

base_tensor = torch.[1]([5, 6, 7])
zeros_tensor = torch.[2](base_tensor.[3])
ones_tensor = torch.ones(base_tensor.shape)

print(base_tensor)
print(zeros_tensor)
print(ones_tensor)

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

Atensor

Bzeros

Cshape

Drand

Attempts:

3 left

💡 Hint

Common Mistakes

Using torch.ones instead of torch.zeros for the zeros tensor.

Using .size() instead of .shape (both work but .shape is more common).

Using torch.rand instead of torch.tensor for the base tensor.

First, torch.tensor creates a tensor from a list. Then torch.zeros creates a zeros tensor with the same shape accessed by shape.

Practice

1. Which PyTorch function creates a tensor filled with zeros of a specified shape?

easy

A. torch.zeros()

B. torch.ones()

C. torch.rand()

D. torch.tensor()

Solution

1. Step 1: Understand the purpose of each function

   torch.zeros() creates a tensor filled with zeros, torch.ones() creates ones, torch.rand() creates random values, and torch.tensor() converts data to tensor.

2. Step 2: Match function to requirement

   Since the question asks for a tensor filled with zeros, torch.zeros() is the correct choice.

3. Final Answer:

   torch.zeros() -> Option A

4. Quick Check:

   Zeros tensor = torch.zeros() [OK]

Hint: Zeros tensor? Use torch.zeros() [OK]

Common Mistakes:

• Confusing torch.ones() with zeros
• Using torch.tensor() without data
• Thinking torch.rand() creates zeros

2. Which of the following is the correct syntax to create a 2x3 tensor of ones in PyTorch?

easy

A. torch.ones{2, 3}

B. torch.ones([2 3])

C. torch.ones(2, 3)

D. torch.ones((2 3))

Solution

1. Step 1: Check valid argument types for torch.ones()

   PyTorch accepts shape as separate ints or tuple/list. torch.ones(2, 3) uses separate ints (valid). torch.ones([2 3]) missing comma (syntax error). torch.ones{2, 3} invalid braces. torch.ones((2 3)) missing comma (syntax error).

2. Step 2: Identify syntax errors

   Only torch.ones(2, 3) is valid Python syntax.

3. Final Answer:

   torch.ones(2, 3) -> Option C

4. Quick Check:

   Separate args syntax = torch.ones(2, 3) [OK]

Hint: Separate dimensions with commas: torch.ones(2, 3) [OK]

Common Mistakes:

• Using curly braces instead of parentheses
• Confusing list and tuple syntax
• Missing commas between shape dimensions

3. What is the output shape and type of the tensor created by torch.rand(3, 2)?

medium

A. A tensor of shape (3, 2) filled with zeros

B. A tensor of shape (2, 3) with random integer values

C. A tensor of shape (3, 2) filled with ones

D. A tensor of shape (3, 2) with random float values between 0 and 1

Solution

1. Step 1: Understand torch.rand() behavior

   torch.rand(3, 2) creates a tensor with shape (3, 2) filled with random floats between 0 and 1.

2. Step 2: Compare options to expected output

   A tensor of shape (3, 2) with random float values between 0 and 1 matches the shape and value type. Options A, B, and D are incorrect because they describe wrong shapes or values.

3. Final Answer:

   A tensor of shape (3, 2) with random float values between 0 and 1 -> Option D

4. Quick Check:

   torch.rand() = random floats [OK]

Hint: torch.rand(shape) = random floats in [0,1) [OK]

Common Mistakes:

• Thinking torch.rand() creates integers
• Mixing up shape dimensions
• Assuming torch.rand() creates zeros or ones

4. Identify the error in this code snippet:

import torch
t = torch.zeros(2 3)

medium

A. Missing comma between dimensions in torch.zeros()

B. torch.zeros() cannot create 2D tensors

C. torch.zeros() requires a list, not separate arguments

D. torch.zeros() needs dtype argument

Solution

1. Step 1: Check syntax of torch.zeros() arguments

   The code uses torch.zeros(2 3) missing a comma between 2 and 3, which is a syntax error.

2. Step 2: Validate other options

   torch.zeros() can create 2D tensors and accepts multiple int arguments or a tuple/list. dtype is optional.

3. Final Answer:

   Missing comma between dimensions in torch.zeros() -> Option A

4. Quick Check:

   Comma separates dimensions [OK]

Hint: Separate dimensions with commas: torch.zeros(2, 3) [OK]

Common Mistakes:

• Omitting commas between shape dimensions
• Thinking dtype is mandatory
• Believing torch.zeros() can't create 2D tensors

5. You want to create a tensor from a Python list [[1,2], [3,4]] and then create a tensor of the same shape filled with ones. Which code correctly does this?

hard

A. import torch
list_data = [[1,2], [3,4]]
t1 = torch.ones(list_data)
t2 = torch.tensor(t1.shape)

B. import torch
list_data = [[1,2], [3,4]]
t1 = torch.tensor(list_data)
t2 = torch.ones(t1.shape)

C. import torch
list_data = [[1,2], [3,4]]
t1 = torch.tensor(list_data)
t2 = torch.ones(len(t1))

D. import torch
list_data = [[1,2], [3,4]]
t1 = torch.ones(len(list_data))
t2 = torch.tensor(t1.shape)

Solution

1. Step 1: Create tensor from list

   torch.tensor(list_data) correctly converts the nested Python list to a (2,2) tensor.

2. Step 2: Create tensor of ones with same shape

   torch.ones(t1.shape) creates a tensor filled with ones matching the shape of t1 ((2,2)).

3. Step 3: Check other options for correctness

   import torch
   list_data = [[1,2], [3,4]]
   t1 = torch.ones(list_data)
   t2 = torch.tensor(t1.shape)

   misuses torch.ones() with nested list (ValueError),

   import torch
   list_data = [[1,2], [3,4]]
   t1 = torch.tensor(list_data)
   t2 = torch.ones(len(t1))

   uses length=2 instead of shape (creates (2,) not (2,2)),

   import torch
   list_data = [[1,2], [3,4]]
   t1 = torch.ones(len(list_data))
   t2 = torch.tensor(t1.shape)

   creates t1 wrong (ones not data) and t2 not ones tensor.

4. Final Answer:

   Correctly create tensor and ones tensor with matching shape -> Option B

5. Quick Check:

   Use tensor.shape for shape in torch.ones() [OK]

Hint: Use tensor.shape to match shape in torch.ones() [OK]

Common Mistakes:

• Passing nested list directly to torch.ones()
• Using len() instead of shape for multi-dim tensors
• Confusing torch.tensor() and torch.ones() usage