95 строки
3.3 KiB
Bash
95 строки
3.3 KiB
Bash
set -e
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export RESOURCEGROUP_NAME="<YOUR_RESOURCEGROUP_NAME>"
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export WORKSPACE_NAME="<YOUR_WORKSPACE_NAME>"
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# If you want to allow outbound traffic, use below instead.
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# <create_workspace_internet_outbound>
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# az ml workspace create -g $RESOURCEGROUP_NAME -n $WORKSPACE_NAME -m allow_internet_outbound
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# </create_workspace_internet_outbound>
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# If you want to block outbound traffic, use below instead.
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# <create_workspace_allow_only_approved_outbound>
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az ml workspace create -g $RESOURCEGROUP_NAME -n $WORKSPACE_NAME -m allow_only_approved_outbound
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# </create_workspace_allow_only_approved_outbound>
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# Before creating an online deployment, manually provision managed network for the workspace, and verify it's completed.
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# <manually_provision_managed_network>
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az ml workspace provision-network -g my_resource_group -n my_workspace_name
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az ml workspace show -n my_workspace_name -g my_resource_group --query managed_network
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# </manually_provision_managed_network>
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az configure --defaults workspace=$WORKSPACE_NAME group=$RESOURCEGROUP_NAME
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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-moe-`echo $RANDOM`
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# If you want to allow inbound traffic, use below instead.
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# <create_endpoint_inbound_allowed>
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# az ml online-endpoint create --name $ENDPOINT_NAME -f endpoints/online/managed/sample/endpoint.yml
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# </create_endpoint_inbound_allowed>
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# If you want to block inbound traffic, use below instead.
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# <create_endpoint_inbound_blocked>
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az ml online-endpoint create --name $ENDPOINT_NAME -f endpoints/online/managed/sample/endpoint.yml --set public_network_access=disabled
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# </create_endpoint_inbound_blocked>
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# <create_deployment>
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az ml online-deployment create --name blue --endpoint $ENDPOINT_NAME -f endpoints/online/managed/sample/blue-deployment.yml --all-traffic
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# </create_deployment>
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# <get_status>
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az ml online-endpoint show -n $ENDPOINT_NAME
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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 --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 --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 --name $ENDPOINT_NAME --request-file endpoints/online/model-1/sample-request.json
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# </test_endpoint>
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# supress printing secret
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set +x
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# <test_endpoint_using_curl_get_key>
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ENDPOINT_KEY=$(az ml online-endpoint get-credentials -n $ENDPOINT_NAME -o tsv --query primaryKey)
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# </test_endpoint_using_curl_get_key>
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set -x
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# <test_endpoint_using_curl>
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SCORING_URI=$(az ml online-endpoint show -n $ENDPOINT_NAME -o tsv --query scoring_uri)
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curl --request POST "$SCORING_URI" --header "Authorization: Bearer $ENDPOINT_KEY" --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 --name 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 --name $ENDPOINT_NAME --yes --no-wait
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# </delete_endpoint>
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