Difference between upload and mount

Hey,

I'm confused by the methodes of the class PipelineData. Is there a tutorial that explains and shows when and how to use as_dataset, as_mount, as_upload, as_input? I can only find very basic examples.

Thanks

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#### Document Details

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* ID: 76780996-4443-4aff-18c0-65195afcab00
* Version Independent ID: 6032c190-bb76-7050-89fa-30476b36b43f
* Content: [azureml.pipeline.core.PipelineData class - Azure Machine Learning Python](https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azure-ml-py)
* Content Source: [AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.PipelineData.yml](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.PipelineData.yml)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @DebFro
* Microsoft Alias: **debfro**

閱讀 PipelineData API 頁面以及 AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-core/azureml.pipeline.core.PipelineData.yml 原始檔。釐清何時以及如何使用 as_dataset、as_mount、as_upload 和 as_input，特別注意 upload 和 mount 之間的差異。完成標準是文件包含涵蓋這些方法的實用教學或範例。

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