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Exam DP-100 topic 3 question 101 discussion

Actual exam question from Microsoft's DP-100

Question #: 101
Topic #: 3

You use the following code to define the steps for a pipeline: from azureml.core import Workspace, Experiment, Run from azureml.pipeline.core import Pipeline from azureml.pipeline.steps import PythonScriptStep ws = Workspace.from_config()
. . .
step1 = PythonScriptStep(name="step1", ...)
step2 = PythonScriptsStep(name="step2", ...)
pipeline_steps = [step1, step2]
You need to add code to run the steps.
Which two code segments can you use to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. experiment = Experiment(workspace=ws, name='pipeline-experiment') run = experiment.submit(config=pipeline_steps)
B. run = Run(pipeline_steps)
C. pipeline = Pipeline(workspace=ws, steps=pipeline_steps) experiment = Experiment(workspace=ws, name='pipeline-experiment') run = experiment.submit(pipeline)
D. pipeline = Pipeline(workspace=ws, steps=pipeline_steps) run = pipeline.submit(experiment_name='pipeline-experiment')

Show Suggested Answer

Suggested Answer: CD 🗳️

by ranjsi01 at Jan. 19, 2022, 4:36 p.m.

Comments

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pancman

Highly Voted 2 years, 10 months ago

The given answer of C & D is correct. Some people commented that they think it should be A & C. Don't let this confuse you as answer A is certainly wrong. You can't use [step1, step2] as a config to experiment submit, as given in the answer A. You need to create a pipeline object and provide it as the config. Refer to experiment class for proof: https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.experiment(class)?view=azure-ml-py#azureml-core-experiment-submit

upvoted 20 times

Matt2000

12 months ago

References: https://learn.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipeline(class)?view=azure-ml-py https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.core.experiment(class)?view=azure-ml-py#azureml-core-experiment-submit

upvoted 1 times

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azurelearner666

2 years, 10 months ago

Thanks for clarifying!

upvoted 2 times

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avinyc

Most Recent 7 months, 1 week ago

Selected Answer: CD

Options C and D

upvoted 1 times

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haby

1 year, 1 month ago

Selected Answer: C

C for me. For A, you can't submit [step1, step2] parameters only; For D, you can't submit a string name only. Correct way is to submit Pipeline Obj or RunConfig Obj, not a list or string.

upvoted 1 times

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PI_Team

1 year, 2 months ago

Selected Answer: C

Only option C is correct Options A and B are incorrect because they either submit the steps directly to the experiment without creating a Pipeline object (Option A), or try to create a Run object directly from the steps without creating a Pipeline or Experiment object (Option B). Both of these approaches will result in errors. Option D correctly creates a Pipeline object and then submits the pipeline with the experiment name. However, please note that the submit method of the Pipeline class does not take an experiment_name argument. Instead, it takes an Experiment object. So, the correct code should be: pipeline = Pipeline(workspace=ws, steps=pipeline_steps) experiment = Experiment(workspace=ws, name='pipeline-experiment') run = pipeline.submit(experiment)

upvoted 1 times

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james2033

1 year, 3 months ago

Selected Answer: CD

Constructor azurelm.pipeline.core.pipeline.Pipeline() https://learn.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipeline.pipeline?view=azure-ml-py#constructor Pipeline(workspace, steps, ...)

upvoted 1 times

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Tommo565

1 year, 10 months ago

Selected Answer: CD

CD is correct

upvoted 1 times

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AzureJobsTillRetire

1 year, 11 months ago

Selected Answer: AC

The correct command for pipeline run is as below experiment.submit() Only A and C has this command. D has command pipeline.submit(), which is incorrect

upvoted 1 times

AzureJobsTillRetire

1 year, 11 months ago

An Azure Machine Learning experiment represent the collection of trials used to validate a user's hypothesis. In Azure Machine Learning, an experiment is represented by the Experiment class and a trial is represented by the Run class. An Azure Machine Learning pipeline is an independently executable workflow of a complete machine learning task. In an experiment, we execute a pipeline, and this is why we use experiment.submit(pipeline) It is not that in a pipeline, we execute an experiment, and that is why pipeline.submit(experiment) is wrong

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Arend78

2 years, 1 month ago

I also think it's A & C: In the Azure documentations, I have only found examples of run = experiment.submit(pipeline) and no examples of run = pipeline.submit(experiment_name='pipeline-experiment') Please reply if you don't agree

upvoted 1 times

AzureJobsTillRetire

1 year, 11 months ago

I think so too. Also there is no definition of the experiment 'pipeline-experiment' in the code

upvoted 1 times

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zehraoneexam

2 years, 10 months ago

correct answer.

upvoted 2 times

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Sjefen

2 years, 11 months ago

I think A & C as well

upvoted 1 times

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synapse

2 years, 11 months ago

Selected Answer: CD

C and are correct. As per below. A is not correct because the submit() expects a Pipeline object. not a list. https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.experiment.experiment?view=azure-ml-py#azureml-core-experiment-experiment-submit

upvoted 1 times

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ranjsi01

3 years ago

sorry i think it should be A and C

upvoted 2 times

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ranjsi01

3 years ago

correct

upvoted 1 times

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