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Exam DP-100 topic 2 question 95 discussion

Actual exam question from Microsoft's DP-100
Question #: 95
Topic #: 2
[All DP-100 Questions]

You manage an Azure Machine Learning workspace. The workspace includes an Azure Machine Learning Kubernetes compute target configured as an Azure Kubernetes Service (AKS) cluster named AKS1. AKS1 is configured to enable the targeting of different nodes to train workloads.

You must run a command job on AKS1 by using the Azure ML Python SDK v2. The command job must select different types of compute nodes. The compute node types must be specified by using a command parameter.

You need to configure the command parameter.

Which parameter should you use?

  • A. environment
  • B. compute
  • C. limits
  • D. instance_type
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Suggested Answer: D 🗳️
by Batman160591 at June 20, 2023, 9:59 p.m.

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Norasit
Highly Voted 1 year, 4 months ago
D. instance_type
upvoted 9 times
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LadyCasilda
Highly Voted 1 year, 2 months ago
On exam 18 August 2023
upvoted 6 times
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evangelist
Most Recent 5 months ago
Selected Answer: D
compute node type= instance type
upvoted 1 times
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sl_mslconsulting
5 months, 2 weeks ago
Selected Answer: B
AKS is the compute target you want to use. instance_type is about the size of the VM you are using. command_node.set_resources( instance_count=1, instance_type="STANDARD_D2_v2", properties={"key": "new_val"}, shm_size="3g", )
upvoted 1 times
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Plb2
8 months, 1 week ago
With the parameter 'instance_type' on the method command.set_resources the type of compute instance to run the job on can be configured. If not specified, the job will run on the default compute target. https://learn.microsoft.com/en-us/python/api/azure-ai-ml/azure.ai.ml.entities.command?view=azure-python#azure-ai-ml-entities-command-set-resources
upvoted 1 times
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NullVoider_0
9 months, 3 weeks ago
Selected Answer: B
B. compute: The 'compute' parameter is used to specify the compute target on which the job will run. In the context of Azure ML and AKS, you can use this parameter to specify different node types in your AKS cluster. This is done by referencing the specific AKS compute targets that are configured for different node types.
upvoted 1 times
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Ahmed_Gehad
1 year, 3 months ago
Selected Answer: D
The instance_type is optional, which is the type of VM used as supported by the compute target. The compute is required and is the name of the compute where the command job is executed.
upvoted 6 times
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cloud6190
1 year, 3 months ago
Selected Answer: B
B. Compute is the right answer.
upvoted 2 times
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damaldon
1 year, 3 months ago
Correct. from azure.ai.ml import command # define the command command_job = command( command="python -c "print('Hello world!')"", environment="AzureML-lightgbm-3.2-ubuntu18.04-py37-cpu@latest", compute="<Kubernetes-compute_target_name>", instance_type="<instance_type_name>" )
upvoted 4 times
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Batman160591
1 year, 4 months ago
To configure the command parameter to select different types of compute nodes when running a command job on an Azure Machine Learning Kubernetes compute target (AKS) using the Azure ML Python SDK v2, you should use: B. compute The "compute" parameter allows you to specify the target compute resource for the command job. In this case, you want to target different types of compute nodes. By setting the "compute" parameter to the desired node type, you can instruct the command job to use the specific compute nodes for the job execution.
upvoted 3 times
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