Tensor math operations in TensorFlow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a tensor filled with zeros of shape (3, 3).

TensorFlow

import tensorflow as tf
zero_tensor = tf.[1](shape=(3, 3))
print(zero_tensor)

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

Aones

Bzeros

Crandom_uniform

Dconstant

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.ones instead of tf.zeros

Forgetting to specify the shape argument

The tf.zeros function creates a tensor filled with zeros of the specified shape.

2fill in blank

medium

Complete the code to add two tensors element-wise.

TensorFlow

import tensorflow as tf
x = tf.constant([1, 2, 3])
y = tf.constant([4, 5, 6])
sum_tensor = tf.[1](x, y)
print(sum_tensor)

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Aadd

Bsubtract

Cmultiply

Ddivide

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.multiply instead of tf.add

Using the '+' operator instead of tf.add (which also works but here we want the function)

The tf.add function adds two tensors element-wise.

3fill in blank

hard

Fix the error in the code to compute the matrix multiplication of two tensors.

TensorFlow

import tensorflow as tf
A = tf.constant([[1, 2], [3, 4]])
B = tf.constant([[5, 6], [7, 8]])
result = tf.[1](A, B)
print(result)

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Amatmul

Bmultiply

Cadd

Dsubtract

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.multiply which does element-wise multiplication

Using tf.add which adds tensors

The tf.matmul function performs matrix multiplication between two tensors.

4fill in blank

hard

Fill both blanks to create a tensor of shape (2, 3) filled with ones and then multiply it by 5.

TensorFlow

import tensorflow as tf
ones_tensor = tf.[1](shape=(2, 3))
scaled_tensor = ones_tensor [2] 5
print(scaled_tensor)

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Aones

B*

C+

Dzeros

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.zeros instead of tf.ones

Using '+' instead of '*' for scaling

tf.ones creates a tensor filled with ones. Multiplying by 5 scales all elements by 5.

5fill in blank

hard

Fill both blanks to compute its square, and then find the mean of the squared values.

TensorFlow

import tensorflow as tf
x = tf.constant([1, 2, 3, 4])
squared = tf.math.[1](x)
mean_val = tf.reduce_[2](squared)
print(mean_val.numpy())  # Output the mean as a number

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Asquare

Bmean

Csum

Dabs

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.math.abs instead of tf.math.square

Using tf.reduce_sum instead of tf.reduce_mean

tf.math.square squares each element. tf.reduce_mean computes the average of all elements.