In the Azure Machine Learning Python SDK v2, the @command_component decorator is used to define a component that executes a specific command or Python function. It encapsulates the inputs, outputs, and environment specification required for a single step in a pipeline. The @pipeline decorator is reserved for defining the workflow that connects multiple components, while tool is not a standard decorator for this context.

For the second selection, the Python import statement follows the syntax from <module_name> import <function_name>. Since the prompt explicitly states that the logic is contained in the file named model_train.py, the module name corresponds to the filename without the extension. Therefore, the correct code is from model_train import train.

Microsoft. (n.d.). Create and run machine learning pipelines using components with the Azure Machine Learning SDK v2. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-component-pipeline-python (Refer to section: "Define a component using the Python function").

Microsoft. (n.d.). azure.ai.ml package - command_component. Azure SDK for Python. Retrieved from https://learn.microsoft.com/en-us/python/api/azure-ai-ml/azure.ai.ml?view=azure-python#azure-ai-ml-command-component