Merge branch 'staging' into deeprec/seqreco_update
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SETUP.md
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SETUP.md
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@ -224,14 +224,14 @@ sudo rm -rf Azure_mmlspark-0.12.jar com.microsoft.cntk_cntk-2.4.jar com.microsof
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## Setup guide for Azure Databricks
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### Requirements of Azure Databricks
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### Requirements
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* Databricks Runtime version >= 4.3 (Apache Spark 2.3.1, Scala 2.11) and <= 5.5 (Apache Spark 2.4.3, Scala 2.11)
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* Python 3
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An example of how to create an Azure Databricks workspace and an Apache Spark cluster within the workspace can be found from [here](https://docs.microsoft.com/en-us/azure/azure-databricks/quickstart-create-databricks-workspace-portal). To utilize deep learning models and GPUs, you may setup GPU-enabled cluster. For more details about this topic, please see [Azure Databricks deep learning guide](https://docs.azuredatabricks.net/applications/deep-learning/index.html).
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### Repository installation
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### Dependencies setup
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You can setup the repository as a library on Databricks either manually or by running an [installation script](tools/databricks_install.py). Both options assume you have access to a provisioned Databricks workspace and cluster and that you have appropriate permissions to install libraries.
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notebook_path, OUTPUT_NOTEBOOK, kernel_name=KERNEL_NAME, parameters=params
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)
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@pytest.mark.notebooks
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@pytest.mark.gpu
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def test_dkn_quickstart(notebooks):
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notebook_path = notebooks["dkn_quickstart"]
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