First PyTorch computation - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a tensor with values [1, 2, 3].

PyTorch

import torch
x = torch.[1]([1, 2, 3])
print(x)

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

Atensor

Barray

Cmatrix

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'array' instead of 'tensor' causes an error because PyTorch does not have torch.array.

Using 'list' or 'matrix' are not valid PyTorch functions.

The torch.tensor function creates a tensor from a list of numbers.

2fill in blank

medium

Complete the code to add two tensors x and y.

PyTorch

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

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A-

B*

C+

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '-' subtracts instead of adds.

Using '*' multiplies instead of adds.

Using '/' divides instead of adds.

The plus sign + adds two tensors element-wise.

3fill in blank

hard

Fix the error in the code to multiply tensor x by 2.

PyTorch

import torch
x = torch.tensor([1, 2, 3])
y = x [1] 2
print(y)

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

A+

Badd

Cmultiply

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'add' or 'multiply' as operators causes syntax errors.

Using '+' adds instead of multiplies.

The * operator multiplies each element of the tensor by 2.

4fill in blank

hard

Fill both blanks to create a tensor of zeros with shape (2, 3) and print its shape.

PyTorch

import torch
zeros_tensor = torch.[1]((2, 3))
print(zeros_tensor.[2])

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Azeros

Bsize

Cshape

Dempty

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'empty' creates uninitialized values, not zeros.

Using 'size' instead of 'shape' is incorrect in PyTorch.

torch.zeros creates a tensor filled with zeros. The shape attribute shows its dimensions.

5fill in blank

hard

Fill all three blanks to create a tensor from a list, convert it to float type, and print its data type.

PyTorch

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

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Ato

Btorch.float32

Cdtype

Dfloat

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'float' instead of 'torch.float32' causes errors.

Using 'float' as a method or attribute is incorrect.

Using 'dtype' as a method instead of attribute causes errors.

The to method converts the tensor to a new type. torch.float32 is the float type. The dtype attribute shows the tensor's data type.