58 строки
1.7 KiB
Bash
58 строки
1.7 KiB
Bash
set -e
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# <set_endpoint_name>
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export ENDPOINT_NAME="<YOUR_ENDPOINT_NAME>"
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# </set_endpoint_name>
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export ENDPOINT_NAME=endpt-`echo $RANDOM`
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# <create_endpoint>
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az ml online-endpoint create --local -n $ENDPOINT_NAME -f endpoints/online/managed/sample/endpoint.yml
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# </create_endpoint>
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# <create_deployment>
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az ml online-deployment create --local -n blue --endpoint $ENDPOINT_NAME -f endpoints/online/managed/sample/blue-deployment.yml
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# </create_deployment>
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# <get_status>
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az ml online-endpoint show -n $ENDPOINT_NAME --local
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# </get_status>
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# check if create was successful
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endpoint_status=`az ml online-endpoint show --local --name $ENDPOINT_NAME --query "provisioning_state" -o tsv`
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echo $endpoint_status
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if [[ $endpoint_status == "Succeeded" ]]
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then
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echo "Endpoint created successfully"
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else
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echo "Endpoint creation failed"
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exit 1
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fi
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deploy_status=`az ml online-deployment show --local --name blue --endpoint $ENDPOINT_NAME --query "provisioning_state" -o tsv`
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echo $deploy_status
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if [[ $deploy_status == "Succeeded" ]]
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then
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echo "Deployment completed successfully"
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else
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echo "Deployment failed"
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exit 1
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fi
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# <test_endpoint>
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az ml online-endpoint invoke --local --name $ENDPOINT_NAME --request-file endpoints/online/model-1/sample-request.json
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# </test_endpoint>
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# <test_endpoint_using_curl>
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SCORING_URI=$(az ml online-endpoint show --local -n $ENDPOINT_NAME -o tsv --query scoring_uri)
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curl --request POST "$SCORING_URI" --header 'Content-Type: application/json' --data @endpoints/online/model-1/sample-request.json
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# </test_endpoint_using_curl>
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# <get_logs>
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az ml online-deployment get-logs --local -n blue --endpoint $ENDPOINT_NAME
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# </get_logs>
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# <delete_endpoint>
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az ml online-endpoint delete --local --name $ENDPOINT_NAME --yes --no-wait
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# </delete_endpoint> |