Pipeline parameters used with DataPath and DataPathComputeBinding to specify side inputs of Parallel pipeline

PipelineParameter API ページとリンクされている AzureML-Docset ソースファイルから始め、azureml-core==1.40.0.post2 と azureml-pipeline==1.40.0 を使用して例を再現します。文書化されている DataPath/DataPathComputeBinding の使用方法と、報告された ParallelRunStep エラーを比較します。ドキュメントまたはサポート対象バージョンに関するガイダンスが動作を正確に反映していれば完了です。

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I'm following this example to create a PipelineParameters for my Parallel pipeline

from azureml.core.datastore import Datastore
from azureml.data.datapath import DataPath, DataPathComputeBinding
from azureml.pipeline.steps import PythonScriptStep
from azureml.pipeline.core import PipelineParameter

datastore = Datastore(workspace=workspace, name="workspaceblobstore")
datapath = DataPath(datastore=datastore, path_on_datastore='input_data')
data_path_pipeline_param = (PipelineParameter(name="input_data", default_value=datapath),
                           DataPathComputeBinding(mode='mount'))

train_step = PythonScriptStep(script_name="train.py",
                             arguments=["--input", data_path_pipeline_param],
                             inputs=[data_path_pipeline_param],
                             compute_target=compute_target,
                             source_directory=project_folder)

This is my code to create the pipeline with the parameters

path = DataPath(datastore=default_store, path_on_datastore='path')
input_param= (PipelineParameter(name="param_name", default_value=path), DataPathComputeBinding(mode='mount'))

parallel_run_config = ParallelRunConfig(
    source_directory=script_dir,
    entry_script='script.py',  # the user script to run against each input
    partition_keys=['key'],
    error_threshold=50,
    output_action='append_row',
    environment=environment,
    compute_target=compute_target, 
    node_count=2,
    run_invocation_timeout=1200
)

parallel_run_step = ParallelRunStep(
    name='test-batch-inference',
    inputs=[partition_input],
    side_inputs=[input1, input2, input_param],
    output=output_dir,
    parallel_run_config=parallel_run_config,
    arguments=['--input_param', input_param],
    allow_reuse=False
)

And it raised this error:

Exception: Step input must be of any type: (<class 'azureml.data.dataset_consumption_config.DatasetConsumptionConfig'>, <class 'azureml.pipeline.core.pipeline_output_dataset.PipelineOutputFileDataset'>, <class 'azureml.pipeline.core.pipeline_output_dataset.PipelineOutputTabularDataset'>, <class 'azureml.data.output_dataset_config.OutputFileDatasetConfig'>, <class 'azureml.data.output_dataset_config.OutputTabularDatasetConfig'>, <class 'azureml.data.output_dataset_config.LinkFileOutputDatasetConfig'>, <class 'azureml.data.output_dataset_config.LinkTabularOutputDatasetConfig'>), found <class 'tuple'>

I'm using azureml-core==1.40.0.post2, azureml-pipeline==1.40.0
It's seems like the sample code is not supported with these version? Before trying this datapath as pipeline parameter, I tried int type input and its just work fine

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• ID: 8e3ec7f7-25c2-8f63-331c-2eb62ffb73c7
• Version Independent ID: 4e31dffb-12fd-85d9-a1a2-aa038017d075
• Content: azureml.pipeline.core.graph.PipelineParameter class - Azure Machine Learning Python
• Content Source: AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.graph.PipelineParameter.yml
• Service: machine-learning
• Sub-service: core
• GitHub Login: @DebFro
• Microsoft Alias: debfro