Hardware and framework version tracking in MLOps - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to print the current GPU hardware version using the NVIDIA System Management Interface.

MLOps

import subprocess
result = subprocess.run(['nvidia-smi', '--query-gpu=hardware_version', '--format=csv,noheader'], capture_output=True, text=True)
print(result.[1])

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

Areturncode

Bstdout

Cstderr

Dargs

Attempts:

3 left

💡 Hint

Common Mistakes

Using stderr instead of stdout to get output.

The stdout attribute contains the output of the command, which includes the hardware version.

2fill in blank

medium

Complete the code to get the installed TensorFlow version.

MLOps

import tensorflow as tf
print(tf.[1])

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

A__version__

Bversion

Cget_version

DVERSION

Attempts:

3 left

💡 Hint

Common Mistakes

Using version or get_version which do not exist.

The TensorFlow version is accessed via the __version__ attribute.

3fill in blank

hard

Fix the error in the code to correctly log hardware and framework versions to a file.

MLOps

with open('version_log.txt', 'w') as f:
    f.write('GPU Version: ' + gpu_version + '\n')
    f.write('TensorFlow Version: ' + [1] + '\n')

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

Atf.__version__

Btf.version

Ctensorflow.version

Dtensorflow.__version__

Attempts:

3 left

💡 Hint

Common Mistakes

Using tf.version which is not a string.

The correct attribute to get TensorFlow version is tf.__version__. The others are incorrect or do not exist.

4fill in blank

hard

Fill both blanks to create a dictionary that maps hardware and framework versions for tracking.

MLOps

version_info = {
    'gpu': [1],
    'framework': [2]
}

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Agpu_version

Btf.__version__

C'unknown'

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Putting string literals instead of variables.

The dictionary keys should map to the variables holding GPU and TensorFlow versions respectively.

5fill in blank

hard

Fill all three blanks to write a function that returns hardware and framework versions as a dictionary.

MLOps

def get_versions():
    gpu = [1]
    framework = [2]
    return [3]

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

Agpu_version

Btf.__version__

C{'gpu': gpu, 'framework': framework}

Dversion_info

Attempts:

3 left

💡 Hint

Common Mistakes

Returning a variable that is not defined inside the function.

The function assigns the GPU and framework versions to variables and returns a dictionary with those values.