ParallelRunStep on Intermediate Partitioned File Dataset Failing

Hi,

I am attempting to use `ParallelRunStep` for a batch training job. The data that is being ingested for training is a partitioned file dataset, so I am using [this example notebook](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/parallel-run/file-dataset-partition-per-folder.ipynb) as a template.

In my script, the batch training step is preceded by a data pulling step, so the `input` to the training step is of type `OutputDatasetConfig` rather than `Dataset.File.from_files`, which is how it is done in the example notebook. Because of this, the training step fails with the following error:

azureml_common.parallel_run.exception_info.Exception: Run failed. Below is the error detail:
Traceback (most recent call last):
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/azureml/7d68a66e-aa64-4732-a159-22d477774715/driver/simulator.py", line 93, in main
simulator.wait()
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/7d68a66e-aa64-4732-a159-22d477774715/prs_prod/lib/python3.8/site-packages/azureml_sys/parallel_run/masterless_simulator.py", line 122, in wait
ProgressReport().save()
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/7d68a66e-aa64-4732-a159-22d477774715/prs_prod/lib/python3.8/site-packages/azureml_sys/parallel_run/progress_report.py", line 191, in save
task_exporter.save()
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/7d68a66e-aa64-4732-a159-22d477774715/prs_prod/lib/python3.8/site-packages/azureml_sys/parallel_run/task_exporter.py", line 113, in save
self.save_remaining()
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/7d68a66e-aa64-4732-a159-22d477774715/prs_prod/lib/python3.8/site-packages/azureml_sys/parallel_run/task_exporter.py", line 100, in save_remaining
for task in total_tasks:
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/7d68a66e-aa64-4732-a159-22d477774715/prs_prod/lib/python3.8/site-packages/azureml_sys/parallel_run/partition_by_keys_provider.py", line 70, in get_tasks
DatasetHelper().save(dataset)
File "/mnt/batch/tasks/shared/LS_root/jobs/sdpesp-dev-cvx/azureml/7d68a66e-aa64-4732-a159-22d477774715/wd/azureml/7d68a66e-aa64-4732-a159-22d477774715/driver/azureml_common/parallel_run/dataset_helper.py", line 29, in save
self.logger.info("Dump dataset {} as preppy files to local directory.".format(dataset.id))
AttributeError: 'str' object has no attribute 'id'

Could this possibly be an issue with `ParallelRunStep` being unable to accept a partitioned `OutputDatasetConfig` as an `input`? Thanks in advance!

---
#### Document Details

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

* ID: f69044d5-213e-a764-31dd-24f8368212b7
* Version Independent ID: 23d38b1c-974a-b2fc-332a-70d7500e1751
* Content: [azureml.pipeline.steps.ParallelRunStep class - Azure Machine Learning Python](https://docs.microsoft.com/en-us/python/api/azureml-pipeline-steps/azureml.pipeline.steps.parallelrunstep?view=azure-ml-py)
* Content Source: [AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-steps/azureml.pipeline.steps.ParallelRunStep.yml](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/stable/docs-ref-autogen/azureml-pipeline-steps/azureml.pipeline.steps.ParallelRunStep.yml)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @DebFro
* Microsoft Alias: **debfro**

Bắt đầu với notebook ví dụ partition-per-folder được tham chiếu và tài liệu về ParallelRunStep, sau đó so sánh đầu vào Dataset.File.from_files của nó với đầu vào OutputDatasetConfig được báo cáo. Tái hiện traceback xung quanh dataset_helper.py và xác định liệu các kiểu đầu vào được tài liệu hóa có bao quát trường hợp này hay không; được xem là hoàn tất khi hành vi hoặc cách sử dụng được hỗ trợ đã được xác lập rõ ràng.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.