OutputDatasetConfig.register_on_complete registers dataset if the step finish with error

While I was running a pipeline a step finished with **Error**:
AzureMLCompute job failed.
DiskFullError: Disk full while running job. Reduce amount of data accessed, or upgrade VM Sku.

As a result of this step I had defined an OutputDatasetConfig with the properties "as_upload" and "register_on_complete". What I was expecting was not to upload dataset neither register it because the step finished with error, so the output is not right, but the situation was that the dataset was upload an registered, and this implies that a tagged version of the dataset is corrupted.

I recommend not to register a dataset if the step finishes with an error that it's what I would expect from documentation.

Regards

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* ID: 02631223-bb1d-f9de-2536-23d753c98508
* Version Independent ID: f524ca56-5419-b233-b67a-a1b3d10408e7
* Content: [azureml.data.output_dataset_config.OutputDatasetConfig class - Azure Machine Learning Python](https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.data.output_dataset_config.outputdatasetconfig?view=azure-ml-py)
* Content Source: [AzureML-Docset/stable/docs-ref-autogen/azureml-core/azureml.data.output_dataset_config.OutputDatasetConfig.yml](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/stable/docs-ref-autogen/azureml-core/azureml.data.output_dataset_config.OutputDatasetConfig.yml)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @DebFro
* Microsoft Alias: **debfro**

從 OutputDatasetConfig 文件和連結的 AzureML-Docset 來源開始，然後重現一個在使用 as_upload 和 register_on_complete 時失敗的 pipeline 步驟。追蹤失敗後何時進行上傳和註冊。完成標準是，失敗的步驟不會上傳或註冊損壞的輸出資料集，並且涵蓋所回報的錯誤情況。

由索引模型根據 Issue 內容生成。