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.

A issue menciona PipelineParameter, PipelineArgument, PythonScriptStep e DataPathComputeBinding, mas não indica nenhum arquivo ou teste. Comece verificando a API e a documentação de pipeline do Azure Machine Learning sobre interpolação de parâmetros em argumentos e, em seguida, compare o comportamento proposto com o workaround do PythonScriptStep pai; o trabalho estará concluído quando uma abordagem compatível tiver sido definida e houver um exemplo ou uma implementação.

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