Merge branch 'staging' into deeprec/seqreco_update

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LeavingSeason 2020-12-01 11:13:38 +08:00 коммит произвёл GitHub
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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
## Setup guide for Azure Databricks
### Requirements of Azure Databricks
### Requirements
* Databricks Runtime version >= 4.3 (Apache Spark 2.3.1, Scala 2.11) and <= 5.5 (Apache Spark 2.4.3, Scala 2.11)
* Python 3
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).
### Repository installation
### Dependencies setup
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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@ -109,7 +109,7 @@ def test_wide_deep(notebooks, tmp):
notebook_path, OUTPUT_NOTEBOOK, kernel_name=KERNEL_NAME, parameters=params
)
@pytest.mark.notebooks
@pytest.mark.gpu
def test_dkn_quickstart(notebooks):
notebook_path = notebooks["dkn_quickstart"]