Creating a file dataset from a single directory in datastore requires azureml-dataset-runtime?
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- documentation, machine-learning
Research direction
Start with the FileDatasetFactory.from_files documentation example and the FileDataset.as_mount entry point, then check how the example behaves with Python 3.11 and the azureml-dataset-runtime dependency. Done means the documented single-directory workflow has a supported runtime and dependency path, or the documentation clearly explains the limitation and an alternative mounting approach.
Written by the indexing model from the issue text.
Description
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
- Dominant language
- Jupyter Notebook
- Stars
- 4.4k
- Forks
- 2.6k
- PR merge metrics
- No merged PRs in 30d
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