Tensor creation (torch.tensor, zeros, ones, rand) in PyTorch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the shape of the tensor created?

Consider the following PyTorch code that creates a tensor. What will be the shape of the resulting tensor?

PyTorch

import torch
x = torch.ones((3, 4))
shape = x.shape
print(shape)

A (4, 3)

B (4,)

C (3,)

D (3, 4)

💡 Hint

Remember that torch.ones takes a tuple for the shape.

The torch.ones function creates a tensor filled with ones with the shape given by the tuple (3, 4). So the shape is (3, 4).

❓ Predict Output

intermediate

What is the output of this tensor creation?

What will be the output of the following PyTorch code?

PyTorch

import torch
x = torch.tensor([[1, 2], [3, 4]], dtype=torch.float32)
print(x)

A tensor([[1., 2.], [3., 4.]])

B tensor([[1, 2], [3, 4]])

C tensor([1., 2., 3., 4.])

D tensor([[1, 2], [3, 4]], dtype=torch.int32)

💡 Hint

Check the dtype argument and how it affects the tensor values.

The tensor is created with dtype=torch.float32, so all values are floats and printed with a decimal point.

❓ Model Choice

advanced

Which tensor creation method produces a tensor with random values between 0 and 1?

You want to create a tensor of shape (2, 3) filled with random values between 0 and 1. Which PyTorch function should you use?

A torch.zeros((2, 3))

B torch.ones((2, 3))

C torch.rand((2, 3))

D torch.tensor([[0, 1], [0, 1], [0, 1]])

💡 Hint

Think about which function generates random numbers.

torch.rand creates a tensor with random values sampled uniformly from [0, 1).

❓ Metrics

advanced

How many elements are in the tensor created by torch.zeros((4, 5, 2))?

If you create a tensor with torch.zeros((4, 5, 2)), how many total elements does this tensor contain?

A 40

B 20

C 10

D 50

💡 Hint

Multiply the dimensions to find the total number of elements.

The tensor shape is (4, 5, 2). Multiply 4 * 5 * 2 = 40 elements total.

🔧 Debug

expert

What error does this code raise?

What error will the following PyTorch code raise when executed?

PyTorch

import torch
x = torch.tensor([1, 2, 3], dtype='float64')
y = torch.ones(3, 3)
z = x + y

A TypeError: dtype must be a torch.dtype, not str

B RuntimeError: The size of tensor a (3) must match the size of tensor b (3) at non-singleton dimension 1

C No error, z is a tensor of shape (3, 3)

D ValueError: operands could not be broadcast together with shapes (3,) (3,3)

💡 Hint

Check the shapes of x and y before adding.

x has shape (3,) and y has shape (3, 3). They cannot be added because their shapes are incompatible for broadcasting.

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