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Misleading error message when using Pipeline Parameters with same name

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
30/100
Issue type
Bug
Clarity
Mostly clear
Activity status
Stale
Tech stack
python

Research direction

Start with azureml/pipeline/core/graph.py around str at line 4538 and reproduce the sample using two PipelineParameter objects with the same name. Trace where the duplicate names are handled; done means the collision produces an informative error identifying the duplicate parameter rather than “PipelineDataset does not have a name.”

Written by the indexing model from the issue text.

Description

I accidently provided the same parameter name for two different pipeline parameters used in different steps, what lead to the error message:

ValueError: PipelineDataset does not have a name.

> /anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py(4538)__str__()
   4536         """
   4537         if not self.name:
-> 4538             raise ValueError("PipelineDataset does not have a name.")
   4539         return "$AZUREML_DATAREFERENCE_{0}".format(self.name)
   4540 

Sample code leading to the issue (assuming default_input_ds: TabularDataset, output_loc: PipelineData, run configs and computetarget are initialized)

input_ds_pipeline_param = PipelineParameter(
    name="input_ds_param", default_value=default_input_ds
)

input_ds_consumption = DatasetConsumptionConfig(
    "tabular_dataset", input_ds_pipeline_param
)

scoring_step = ParallelRunStep(
    name="scoringstep",
    inputs=[input_ds_consumption],
    output=output_loc,
    parallel_run_config=score_run_config,
    allow_reuse=False,
)


destination_path = PipelineParameter(
    name="input_ds_param",
    default_value="samplepath/sampleoutput.parquet",
)

copying_step = PythonScriptStep(
    name="scorecopystep",
    script_name="scoring/parallel_batchscore_copyoutput.py",
    source_directory="../aml_sourcedir",
    arguments=["--output_path", output_loc, "--destination_path", destination_path],
    inputs=[output_loc],
    allow_reuse=False,
    compute_target=aml_compute_score,
    runconfig=copy_run_config,
)

Pipeline(workspace=ws, steps=[scoring_step, copying_step])


---
#### Document Details

⚠ *Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.*

* ID: 696d753e-ad1b-3e09-6756-425de691b1be
* Version Independent ID: 42ba9f58-3c4d-4cf7-1f89-1fea2a2efa62
* Content: [azureml.pipeline.core.graph module - Azure Machine Learning Python](https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.graph?view=azure-ml-py)
* Content Source: [AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.graph.yml](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.graph.yml)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @DebFro
* Microsoft Alias: **debfro**
Dominant language
Jupyter Notebook
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