Azure / Azure/MachineLearningNotebooks
Creating a file dataset from a single directory in datastore requires azureml-dataset-runtime?
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描述
I am trying to create a file dataset from a single directory in datastore. Im following the code block from
Specifically,
from azureml.core import Dataset, Datastore
# create file dataset from a single file in datastore
datastore = Datastore.get(workspace, 'workspaceblobstore')
# create file dataset from a single directory in datastore
file_dataset_2 = Dataset.File.from_files(path=(datastore, 'image/'))
However, when I try to replicate these steps for my own Datastore, I encounter an Import Error
ImportError: Missing required package "azureml-dataset-runtime", which can be installed by running: "c:\Users\<user>\.conda\envs\<my-conda-env-name>\python.exe" -m pip install azureml-dataset-runtime --upgrade
I am on Python 3.11.3 and I tried installing azureml-dataset-runtime but I encounter a dependency clash which requires me to downgrade to Python 3.8.
Furthermore, from the PyPI page
https://pypi.org/project/azureml-dataset-runtime/
It states that azureml-dataset-runtime is "is internal, and is not intended to be used directly."
Is this intended? I am trying to mount my data for a custom ML training job, using the as_mount function from the FileDataset Class. Please let me know if there is a better alternative to mounting data, or am I forced to use Python 3.8?
Document Details
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- ID: 091afd7e-72ca-a384-01db-4da4d40a6734
- Version Independent ID: 0f3783bf-ab1f-f0d6-08f3-90becae914e8
- Content: azureml.data.dataset_factory.FileDatasetFactory class - Azure Machine Learning Python
- Content Source: AzureML-Docset/stable/docs-ref-autogen/azureml-core/azureml.data.dataset_factory.FileDatasetFactory.yml
- Service: machine-learning
- Sub-service: core
- GitHub Login: @DebFro
- Microsoft Alias: debfro
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研究方向
從 FileDatasetFactory.from_files 的文件範例和 FileDataset.as_mount 進入點開始,接著檢查該範例在 Python 3.11 和 azureml-dataset-runtime 相依性下的行為。完成的標準是:文件所述的單一目錄工作流程具有受支援的執行階段和相依性路徑,或文件清楚說明限制以及替代的掛載方法。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- python
- 領域
- documentation, machine-learning
- Issue 類型
- 缺陷
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 活躍度
- 停滯
- 描述清晰度
- 基本清楚
- 新手友好度
- 25/100