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CaymanWilliams
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Nov 30, 2023
| # MAGIC * The Gradient Webhook has been configured | ||
| # MAGIC * The Databricks Job has been Gradient enabled | ||
| # MAGIC | ||
| # MAGIC When bypassing the Gradient Webhook with AWS, the cluster attached to this notebook must have an instance_arn with describe_instances and describe_volumes permissions. When bypassing the Gradient Webhook with Azure, the following environment variables must be set with the correct values: "AZURE_TENANT_ID", "AZURE_SUBSCRIPTION_ID", "AZURE_CLIENT_SECRET", "AZURE_CLIENT_ID" |
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Just added this in case it's unclear what customers would need to do to bypass the webhook. I'm fine with taking it out if bypassing the webhook is supposed to be a complete edge case
CaymanWilliams
commented
Nov 30, 2023
| # MAGIC | ||
| # MAGIC When bypassing the Gradient Webhook with AWS, the cluster attached to this notebook must have an instance_arn with describe_instances and describe_volumes permissions. When bypassing the Gradient Webhook with Azure, the following environment variables must be set with the correct values: "AZURE_TENANT_ID", "AZURE_SUBSCRIPTION_ID", "AZURE_CLIENT_SECRET", "AZURE_CLIENT_ID" | ||
| # MAGIC | ||
| # MAGIC This job will configure all runs to execute using ON DEMAND nodes only. The orginal settings will be restored after training is complete. |
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Is this true? Are the settings ever restored? (Supposed to be looking at the line under the highlighted one)
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A couple small edits to make compatible with python >=3.7 and only making the access_report necessary when bypassing the webhook.