forked from Azure/azureml-examples
-
Notifications
You must be signed in to change notification settings - Fork 2
/
deploy-arm-templates-az-cli.sh
175 lines (148 loc) · 7.11 KB
/
deploy-arm-templates-az-cli.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
set -x
#<get_access_token>
TOKEN=$(az account get-access-token --query accessToken -o tsv)
#</get_access_token>
# <create_variables>
SUBSCRIPTION_ID=$(az account show --query id -o tsv)
LOCATION=$(az ml workspace show --query location -o tsv)
RESOURCE_GROUP=$(az group show --query name -o tsv)
WORKSPACE=$(az configure -l --query "[?name=='workspace'].value" -o tsv)
#</create_variables>
# <set_endpoint_name>
export ENDPOINT_NAME=endpoint-`echo $RANDOM`
# </set_endpoint_name>
#<api_version>
API_VERSION="2022-05-01"
#</api_version>
echo -e "Using:\nSUBSCRIPTION_ID=$SUBSCRIPTION_ID\nLOCATION=$LOCATION\nRESOURCE_GROUP=$RESOURCE_GROUP\nWORKSPACE=$WORKSPACE"
# define how to wait
wait_for_completion () {
operation_id=$1
status="unknown"
if [[ $operation_id == "" || -z $operation_id || $operation_id == "null" ]]; then
echo "operation id cannot be empty"
exit 1
fi
while [[ $status != "Succeeded" && $status != "Failed" ]]
do
echo "Getting operation status from: $operation_id"
operation_result=$(curl --location --request GET $operation_id --header "Authorization: Bearer $TOKEN")
# TODO error handling here
status=$(echo $operation_result | jq -r '.status')
echo "Current operation status: $status"
sleep 5
done
if [[ $status == "Failed" ]]
then
error=$(echo $operation_result | jq -r '.error')
echo "Error: $error"
fi
}
# <get_storage_details>
# Get values for storage account
response=$(curl --location --request GET "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/datastores?api-version=$API_VERSION&isDefault=true" \
--header "Authorization: Bearer $TOKEN")
AZUREML_DEFAULT_DATASTORE=$(echo $response | jq -r '.value[0].name')
AZUREML_DEFAULT_CONTAINER=$(echo $response | jq -r '.value[0].properties.containerName')
export AZURE_STORAGE_ACCOUNT=$(echo $response | jq -r '.value[0].properties.accountName')
# </get_storage_details>
# <upload_code>
az storage blob upload-batch -d $AZUREML_DEFAULT_CONTAINER/score -s cli/endpoints/online/model-1/onlinescoring --account-name $AZURE_STORAGE_ACCOUNT
# </upload_code>
# <create_code>
az deployment group create -g $RESOURCE_GROUP \
--template-file arm-templates/code-version.json \
--parameters \
workspaceName=$WORKSPACE \
codeAssetName="score-sklearn" \
codeUri="https://$AZURE_STORAGE_ACCOUNT.blob.core.windows.net/$AZUREML_DEFAULT_CONTAINER/score"
# </create_code>
# <upload_model>
az storage blob upload-batch -d $AZUREML_DEFAULT_CONTAINER/model -s cli/endpoints/online/model-1/model --account-name $AZURE_STORAGE_ACCOUNT
# </upload_model>
# <create_model>
az deployment group create -g $RESOURCE_GROUP \
--template-file arm-templates/model-version.json \
--parameters \
workspaceName=$WORKSPACE \
modelAssetName="sklearn" \
modelUri="azureml://subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/workspaces/$WORKSPACE/datastores/$AZUREML_DEFAULT_DATASTORE/paths/model/sklearn_regression_model.pkl"
# </create_model>
# <read_condafile>
CONDA_FILE=$(cat cli/endpoints/online/model-1/environment/conda.yaml)
# </read_condafile>
# <create_environment>
ENV_VERSION=$RANDOM
az deployment group create -g $RESOURCE_GROUP \
--template-file arm-templates/environment-version.json \
--parameters \
workspaceName=$WORKSPACE \
environmentAssetName=sklearn-env \
environmentAssetVersion=$ENV_VERSION \
dockerImage=mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20210727.v1 \
condaFile="$CONDA_FILE"
# </create_environment>
# <create_endpoint>
az deployment group create -g $RESOURCE_GROUP \
--template-file arm-templates/online-endpoint.json \
--parameters \
workspaceName=$WORKSPACE \
onlineEndpointName=$ENDPOINT_NAME \
identityType=SystemAssigned \
authMode=AMLToken \
location=$LOCATION
# </create_endpoint>
# <get_endpoint>
response=$(curl --location --request GET "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/onlineEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN")
operation_id=$(echo $response | jq -r '.properties.properties.AzureAsyncOperationUri')
wait_for_completion $operation_id
# </get_endpoint>
# <create_deployment>
resourceScope="/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices"
az deployment group create -g $RESOURCE_GROUP \
--template-file arm-templates/online-endpoint-deployment.json \
--parameters \
workspaceName=$WORKSPACE \
location=$LOCATION \
onlineEndpointName=$ENDPOINT_NAME \
onlineDeploymentName=blue \
codeId="$resourceScope/workspaces/$WORKSPACE/codes/score-sklearn/versions/1" \
scoringScript=score.py \
environmentId="$resourceScope/workspaces/$WORKSPACE/environments/sklearn-env/versions/$ENV_VERSION" \
model="$resourceScope/workspaces/$WORKSPACE/models/sklearn/versions/1" \
endpointComputeType=Managed \
skuName=Standard_F2s_v2 \
skuCapacity=1
# </create_deployment>
# <get_deployment>
response=$(curl --location --request GET "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/onlineEndpoints/$ENDPOINT_NAME/deployments/blue?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN")
operation_id=$(echo $response | jq -r '.properties.properties.AzureAsyncOperationUri')
wait_for_completion $operation_id
scoringUri=$(echo $response | jq -r '.properties.scoringUri')
# </get_endpoint>
# <get_endpoint_access_token>
response=$(curl -H "Content-Length: 0" --location --request POST "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/onlineEndpoints/$ENDPOINT_NAME/token?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN")
accessToken=$(echo $response | jq -r '.accessToken')
# </get_endpoint_access_token>
# <score_endpoint>
curl --location --request POST $scoringUri \
--header "Authorization: Bearer $accessToken" \
--header "Content-Type: application/json" \
--data-raw @cli/endpoints/online/model-1/sample-request.json
# </score_endpoint>
# <get_deployment_logs>
curl --location --request POST "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/onlineEndpoints/$ENDPOINT_NAME/deployments/blue/getLogs?api-version=$API_VERSION" \
--header "Authorization: Bearer $TOKEN" \
--header "Content-Type: application/json" \
--data-raw "{ \"tail\": 100 }"
# </get_deployment_logs>
# <delete_endpoint>
curl --location --request DELETE "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.MachineLearningServices/workspaces/$WORKSPACE/onlineEndpoints/$ENDPOINT_NAME?api-version=$API_VERSION" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $TOKEN" || true
# </delete_endpoint>