dp-100-data-scientist-assoc video for scenario: The Advanced Cosmic Microwave Explorer Corporation (ACME Corp) has contracted you to lead a team of data
Scenario: The Advanced Cosmic Microwave Explorer Corporation (ACME Corp) has contracted you to lead a team of data scientists for a new deep learning (DL) project. The priority on your list is to create a pipeline to process data and train the DL model using Azure Machine Learning SDK v2. Python Code Segment: The provided Python script imports required libraries, sets up Azure ML authentication, and initializes an MLClient to interact with the workspace. However, the pipeline class import statement is incomplete: Python # import required libraries from azure . identity import DefaultAzureCredential , InteractiveBrowserCredential from azure . ai . ml import MLClient , Input # import pipeline class from [ ? ] try : credential = DefaultAzureCredential () # Check if given credential can get token successfully. credential . get_token ( "https://management.azure.com/.default" ) except Exception as ex : # Fall back to InteractiveBrowserCredential in case DefaultAzureCredential not work credential = InteractiveBrowserCredential () # Get a handle to workspace ml_client = MLClient . from_config ( credential = credential ) # Retrieve an already attached Azure Machine Learning Compute. cluster_name = "cpu-cluster" print ( ml_client . compute . get ( cluster_name )) # Import components that are defined with Python function with open ( "src/components.py" ) as fin : print ( fin . read ()) # You need to install mldesigner package to use command_component decorator. # Option 1: install directly # !pip install mldesigner # Option 2: install as an extra dependency of azure-ai-ml # !pip install azure-ai-ml[designer] # import the components as functions from src . components import train_model , score_data , eval_model cluster_name = "cpu-cluster" # define a pipeline with component @pipeline ( default_compute = cluster_name ) def pipeline_with_python_function_components ( input_data , test_data , learning_rate ): """E2E dummy train-score-eval pipeline with components defined via Python function components""" # Call component obj as function: apply given inputs & parameters to create a node in pipeline train_with_sample_data = train_model ( training_data = input_data , max_epochs = 5 , learning_rate = learning_rate ) score_with_sample_data = score_data ( model_input = train_with_sample_data . outputs . model_output , test_data = test_data ) eval_with_sample_data = eval_model ( scoring_result = score_with_sample_data . outputs . score_output ) # Return: pipeline outputs return { "eval_output" : eval_with_sample_data . outputs . eval_output , "model_output" : train_with_sample_data . outputs . model_output , } pipeline_job = pipeline_with_python_function_components ( input_data = Input ( path = "wasbs://demo@dprepdata.blob.core.windows.net/Titanic.csv" , type = "uri_file" ), test_data = Input ( path = "wasbs://demo@dprepdata.blob.core.windows.net/Titanic.csv" , type = "uri_file" ), learning_rate = 0.1 , ) # submit job to workspace pipeline_job = ml_client . jobs . create_or_update ( pipeline_job , experiment_name = "train_score_eval_pipeline" ) Question: Which library should be used to replace [?] in the above SDK v2 sample (below # import pipeline class ) to correctly import the pipeline class?