update samples - test

how-to-use-azureml/automated-machine-learning/forecasting-grouping/deploy/deploy.py

@@ -0,0 +1,65 @@
+import argparse
+from azureml.core import Run, Model
+from azureml.core import Workspace
+from azureml.core.webservice import AciWebservice
+from azureml.core.model import InferenceConfig
+import json
+
+
+script_file_name = 'score.py'
+conda_env_file_name = 'myenv.yml'
+
+print("In deploy.py")
+parser = argparse.ArgumentParser()
+parser.add_argument("--time_column_name", type=str, help="time column name")
+parser.add_argument("--group_column_names", type=str, help="group column names")
+parser.add_argument("--model_names", type=str, help="model names")
+parser.add_argument("--service_name", type=str, help="service name")
+
+args = parser.parse_args()
+
+# replace the group column names in scoring script to the ones set by user
+print("Update group_column_names")
+print(args.group_column_names)
+
+with open(script_file_name, 'r') as cefr:
+    content = cefr.read()
+with open(script_file_name, 'w') as cefw:
+    content = content.replace('<<groups>>', args.group_column_names.rstrip())
+    cefw.write(content.replace('<<time_colname>>', args.time_column_name.rstrip()))
+
+with open(script_file_name, 'r') as cefr1:
+    content1 = cefr1.read()
+print(content1)
+
+model_list = json.loads(args.model_names)
+print(model_list)
+
+run = Run.get_context()
+ws = run.experiment.workspace
+
+deployment_config = AciWebservice.deploy_configuration(
+    cpu_cores=1,
+    memory_gb=2,
+    tags={"method": "grouping"},
+    description='grouping demo aci deployment'
+)
+
+inference_config = InferenceConfig(
+    entry_script=script_file_name,
+    runtime='python',
+    conda_file=conda_env_file_name
+)
+
+models = []
+for model_name in model_list:
+    models.append(Model(ws, name=model_name))
+
+service = Model.deploy(
+    ws,
+    name=args.service_name,
+    models=models,
+    inference_config=inference_config,
+    deployment_config=deployment_config
+)
+service.wait_for_deployment(True)