HOTSPOT - You use an Azure Machine Learning workspace. You create the following Python code: For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:
Suggested Answer:
Box 1: No - Environment is a required parameter. The environment to use for the run. If no environment is specified, azureml.core.runconfig.DEFAULT_CPU_IMAGE will be used as the Docker image for the run. The following example shows how to instantiate a new environment. from azureml.core import Environment myenv = Environment(name="myenv")
Box 2: Yes - Parameter compute_target: The compute target where training will happen. This can either be a ComputeTarget object, the name of an existing ComputeTarget, or the string "local". If no compute target is specified, your local machine will be used.
Box 3: Yes - Parameter source_directory. A local directory containing code files needed for a run. Parameter script. The file path relative to the source_directory of the script to be run. Reference: https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.scriptrunconfig https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.environment.environment
No-Yes-Yes
for 2nd:
The compute target where training will happen. This can either be a ComputeTarget object, the name of an existing ComputeTarget, or the string "local". If no compute target is specified, your local machine will be used.
see: https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.core.scriptrunconfig?view=azure-ml-py
The default environment will be created: No
The training script will run on local compute: No
A script run configuration runs a training script named train.py located in the directory defined by the project_folder variable: Yes
I'm skeptic about Box3: "A ScriptRunConfig object is used to configure the information necessary for submitting a training run as part of an Experiment"...so it should "configure", not "run"...isn't it?
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.scriptrunconfig?view=azure-ml-py
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