TensorFlow architecture (eager vs graph execution) - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to enable eager execution in TensorFlow.

TensorFlow

import tensorflow as tf

tf.config.run_functions_eagerly([1])

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

AFalse

BNone

CTrue

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using False disables eager execution.

Passing None or 0 will not enable eager execution.

Setting run_functions_eagerly(True) enables eager execution mode in TensorFlow, which runs operations immediately.

2fill in blank

medium

Complete the code to create a TensorFlow function that runs as a graph.

TensorFlow

import tensorflow as tf

@tf.function
def add(a, b):
    return a [1] b

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

A*

B+

C-

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using subtraction or multiplication instead of addition.

Forgetting the decorator to create a graph function.

The @tf.function decorator compiles the function into a graph. The function adds two tensors using the + operator.

3fill in blank

hard

Fix the error in the code to print the result of a TensorFlow tensor in eager mode.

TensorFlow

import tensorflow as tf

a = tf.constant(5)
print([1])

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

Aa.numpy()

Ba.eval()

Ca.value()

Da.data()

Attempts:

3 left

💡 Hint

Common Mistakes

Using eval() which requires a session in graph mode.

Trying to use non-existent methods like value() or data().

In eager mode, use tensor.numpy() to get the value as a NumPy array for printing.

4fill in blank

hard

Fill both blanks to create a TensorFlow graph function that multiplies and then adds two tensors.

TensorFlow

import tensorflow as tf

@tf.function
def compute(x, y):
    mul = x [1] y
    return mul [2] y

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

A*

B+

C-

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up the order of operations.

Using subtraction or division instead of addition.

The function multiplies x and y first, then adds y to the result.

5fill in blank

hard

Fill all three blanks to create a TensorFlow function that subtracts, divides, and then multiplies two tensors.

TensorFlow

import tensorflow as tf

@tf.function
def complex_op(a, b):
    sub = a [1] b
    div = sub [2] b
    return div [3] a

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

A-

B/

C*

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition instead of subtraction.

Mixing up division and multiplication operators.

The function subtracts b from a, divides the result by b, then multiplies by a.