Potential feature request: PipelineArgument dynamically derived from PipelineParameter

Hello,

I couldn't find a pre-existing issue or documentation on this topic. Is it possible to create pipeline parameters which are dynamically generated from the values of other PipelineParameters?

e.g. the below shows the basic scenario we're looking for.

```python

customer_project = PipelineParameter(name="customer_project")
publish_version = PipelineParameter(name="publish_version")

# following is generated from above pipeline parameters but can still be used as an argument in Pipeline Steps
input_data_parameter = PipelineArgument(name="input_data", value_spec="base_input/{param:customer_project}/{param:publish_version}/train")
input_data = (input_data_parameter, DataPathComputeBinding(mode='mount'))
...
train_step = PythonScriptStep(
...
inputs=[input_data]
)

```

Is there a better way to do what I'm trying to do here?

Currently we have some workarounds like have a "parent" PythonScriptStep which just handles submitting child runs, and generating the right paths from pipeline arguments, but it seems like an extra step and ability to have something like above would be nicer for us.

El issue menciona PipelineParameter, PipelineArgument, PythonScriptStep y DataPathComputeBinding, pero no indica ningún archivo ni prueba. Empieza revisando la API y la documentación de Azure Machine Learning sobre la interpolación de parámetros en argumentos y, después, compara el comportamiento propuesto con el workaround del PythonScriptStep principal; el trabajo estaría terminado cuando se haya decidido un enfoque compatible y exista un ejemplo o una implementación.

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