How to submit Dataset Input as a Parameter to AZ ML CLI run submit-pipeline command?

Refers to: https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-showcasing-dataset-and-pipelineparameter.ipynb

To submit a parameter in an az ml cli `run submit-pipeline` command we use the syntax:

az ml run submit-pipeline –datapaths [DataPATHS Name=datastore/datapath] --experiment-name [Experiment_Name] --parameters [String_parameters Name=Value] --pipeline-id [ID]--resource-group [RGP] --subscription-id [SUB_ID] --workspace-name [AML_WS_NAME]

This will submit Datapaths and some string parameters with the pipeline. How do we submit Dataset references using az ml cli `run submit-pipeline` command?

For example, the Documentation Notebook: [aml-pipelines-showcasing-dataset-and-pipelineparameter](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-showcasing-dataset-and-pipelineparameter.ipynb)

To submit a Dataset Class reference we do:

iris_tabular_ds = Dataset.Tabular.from_delimited_files('link/iris.csv')
pipeline_run_with_params = experiment.submit(pipeline, pipeline_parameters={'tabular_ds_param': iris_tabular_ds})

Using REST Call the syntax is:

response = requests.post(rest_endpoint,
headers=aad_token,
json={"ExperimentName": "MyRestPipeline",
"RunSource": "SDK",
"DataSetDefinitionValueAssignments": { "tabular_ds_param": {"SavedDataSetReference": {"Id": iris_tabular_ds.id}}}
}
)

What is the syntax to achieve this using `az ml cli`?

`az ml run submit-pipeline --datapaths tabular_ds_param=[datastore]/[registered-dataset] --experiment-name [exp-name]-exp --pipeline-id [pipeline-id] --resource-group $(AML_RG) --subscription-id $(AML_SUB_ID) --workspace-name $(AML_WS)` does not work.