You register a file dataset named csvjolder that references a folder. The folder includes multiple com ma-separated values (CSV) files in an Azure storage blob container. You plan to use the following code to run a script that loads data from the file dataset.
You create and instantiate the following variables:
You have the following code:
You need to pass the dataset to ensure that the script can read the files it references.
Which code segment should you insert to replace the code comment?
A . inputs=[file_dataset.as_named_input(‘training_files’).to_pandas_dataframe()],
B . inputs=[file_dataset.as_named_input(‘training_files’).as_mount()],
C . script_params={‘–training_files’: file_dataset},
D . inputs=[file_dataset.as_named_input(‘training_files’)],
Answer: D
Explanation:
from azureml.train.estimator import Estimator
script_params = {
# to mount files referenced by mnist dataset
‘–data-folder’: mnist_file_dataset.as_named_input(‘mnist_opendataset’).as_mount(),
‘–regularization’: 0.5
}
est = Estimator(source_directory=script_folder,
script_params=script_params,
compute_target=compute_target,
environment_definition=env,
entry_script=’train.py’)
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-train-models-with-aml
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