model name as aml pipeline parameter

Author: praneet22

aml_config/security_config.json

@@ -8,6 +8,7 @@
     "remote_vm_ip" : "<>",
     "experiment_name" : "devops-ai-demo",
     "aml_cluster_name" : "aml-compute",
+    "model_name" : "sklearn_regression_model2.pkl",
     "vnet_resourcegroup_name" : "<>", 
     "vnet_name" : "<>", 
     "subnet_name" : "<>"

aml_service/04-AmlPipelines.py

@@ -67,6 +67,8 @@
 experiment_name = config["experiment_name"]
 aml_cluster_name = config["aml_cluster_name"]
 aml_pipeline_name = "training-pipeline"
+#model_name = config["model_name"]
+model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl")
 
 source_directory = "code"
 
@@ -76,8 +78,9 @@
 cd = CondaDependencies("aml_config/conda_dependencies.yml")
 
 run_config = RunConfiguration(conda_dependencies=cd)
-
 aml_compute = ws.compute_targets[aml_cluster_name]
+run_config.environment.docker.enabled = True
+run_config.environment.spark.precache_packages = False
 
 jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store)
 
@@ -91,7 +94,11 @@
     script_name="training/train.py",
     compute_target=aml_compute,
     source_directory=source_directory,
-    arguments=["--config_suffix", config_suffix, "--json_config", jsonconfigs],
+    arguments=[
+        "--config_suffix", config_suffix, 
+        "--json_config", jsonconfigs, 
+        "--model_name", model_name,
+        ],
     runconfig=run_config,
     # inputs=[jsonconfigs],
     outputs=[jsonconfigs],
@@ -104,7 +111,10 @@
     script_name="evaluate/evaluate_model.py",
     compute_target=aml_compute,
     source_directory=source_directory,
-    arguments=["--config_suffix", config_suffix, "--json_config", jsonconfigs],
+    arguments=[
+                "--config_suffix", config_suffix, 
+                "--json_config", jsonconfigs,
+                ],
     runconfig=run_config,
     inputs=[jsonconfigs],
     # outputs=[jsonconfigs],
@@ -117,7 +127,11 @@
     script_name="register/register_model.py",
     compute_target=aml_compute,
     source_directory=source_directory,
-    arguments=["--config_suffix", config_suffix, "--json_config", jsonconfigs],
+    arguments=[
+        "--config_suffix", config_suffix, 
+        "--json_config", jsonconfigs,
+        "--model_name", model_name,
+        ],
     runconfig=run_config,
     inputs=[jsonconfigs],
     # outputs=[jsonconfigs],

aml_service/05-TriggerAmlPipeline.py

@@ -31,6 +31,8 @@
 try:
     with open("aml_config/pipeline_config.json") as f:
         config = json.load(f)
+    with open("aml_config/security_config.json") as f:
+        security_config = json.load(f)
 except:
     print("No pipeline config found")
     sys.exit(0)
@@ -40,10 +42,14 @@
 aad_token = cli_auth.get_authentication_header()
 rest_endpoint1 = config["rest_endpoint"]
 experiment_name = config["experiment_name"]
+model_name = security_config["experiment_name"]
+
 print(rest_endpoint1)
 
 response = requests.post(
-    rest_endpoint1, headers=aad_token, json={"ExperimentName": experiment_name}
+    rest_endpoint1, headers=aad_token, 
+    json={"ExperimentName": experiment_name,
+    "ParameterAssignments": {"model_name":model_name}}
 )
 
 run_id = response.json()["Id"]

code/register/register_model.py

@@ -50,6 +50,13 @@
     type=str,
     help="Directory to write all the intermediate json configs",
 )
+parser.add_argument(
+    "--model_name",
+    type=str,
+    help="Name of the Model",
+    default="sklearn_regression_model.pkl",
+)
+
 args = parser.parse_args()
 
 print("Argument 1: %s" % args.config_suffix)
@@ -61,6 +68,7 @@
 
 evaluate_run_id_json = "run_id_{}.json".format(args.config_suffix)
 evaluate_output_path = os.path.join(args.json_config, evaluate_run_id_json)
+model_name = args.model_name
 
 # Get the latest evaluation result
 try:
@@ -85,7 +93,7 @@
 os.makedirs(model_local_dir, exist_ok=True)
 
 # Download Model to Project root directory
-model_name = "sklearn_regression_model.pkl"
+# model_name = "sklearn_regression_model.pkl"
 run.download_file(
     name="./outputs/" + model_name, output_file_path="./model/" + model_name
 )

code/training/train.py

@@ -48,11 +48,20 @@
     type=str,
     help="Directory to write all the intermediate json configs",
 )
+parser.add_argument(
+    "--model_name",
+    type=str,
+    help="Name of the Model",
+    default="sklearn_regression_model.pkl",
+)
+
 args = parser.parse_args()
 
 print("Argument 1: %s" % args.config_suffix)
 print("Argument 2: %s" % args.json_config)
 
+model_name = args.model_name
+
 if not (args.json_config is None):
     os.makedirs(args.json_config, exist_ok=True)
     print("%s created" % args.json_config)
@@ -80,7 +89,7 @@
 
 
 # Save model as part of the run history
-model_name = "sklearn_regression_model.pkl"
+
 # model_name = "."
 
 with open(model_name, "wb") as file: