Model registration tags come from parameters.json (#237)

Author: jotaylo

diabetes_regression/evaluate/evaluate_model.py

@@ -83,7 +83,7 @@
     "--model_name",
     type=str,
     help="Name of the Model",
-    default="sklearn_regression_model.pkl",
+    default="diabetes_model.pkl",
 )
 
 parser.add_argument(

diabetes_regression/parameters.json

@@ -6,6 +6,10 @@
     "evaluation":
     {
 
+    },
+    "registration":
+    {
+        "tags": ["mse"]
     },
     "scoring":
     {

diabetes_regression/register/register_model.py

@@ -23,6 +23,7 @@
 ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
 POSSIBILITY OF SUCH DAMAGE.
 """
+import json
 import os
 import sys
 import argparse
@@ -69,8 +70,9 @@ def main():
         "--model_name",
         type=str,
         help="Name of the Model",
-        default="sklearn_regression_model.pkl",
+        default="diabetes_model.pkl",
     )
+
     parser.add_argument(
         "--step_input",
         type=str,
@@ -85,40 +87,58 @@ def main():
     model_name = args.model_name
     model_path = args.step_input
 
+    print("Getting registration parameters")
+
+    # Load the registration parameters from the parameters file
+    with open("parameters.json") as f:
+        pars = json.load(f)
+    try:
+        register_args = pars["registration"]
+    except KeyError:
+        print("Could not load registration values from file")
+        register_args = {"tags": []}
+
+    model_tags = {}
+    for tag in register_args["tags"]:
+        try:
+            mtag = run.parent.get_metrics()[tag]
+            model_tags[tag] = mtag
+        except KeyError:
+            print(f"Could not find {tag} metric on parent run.")
+
     # load the model
     print("Loading model from " + model_path)
     model_file = os.path.join(model_path, model_name)
     model = joblib.load(model_file)
-    model_mse = run.parent.get_metrics()["mse"]
     parent_tags = run.parent.get_tags()
     try:
         build_id = parent_tags["BuildId"]
     except KeyError:
         build_id = None
         print("BuildId tag not found on parent run.")
-        print("Tags present: {parent_tags}")
+        print(f"Tags present: {parent_tags}")
     try:
         build_uri = parent_tags["BuildUri"]
     except KeyError:
         build_uri = None
         print("BuildUri tag not found on parent run.")
-        print("Tags present: {parent_tags}")
+        print(f"Tags present: {parent_tags}")
 
     if (model is not None):
         dataset_id = parent_tags["dataset_id"]
         if (build_id is None):
             register_aml_model(
                 model_file,
                 model_name,
-                model_mse,
+                model_tags,
                 exp,
                 run_id,
                 dataset_id)
         elif (build_uri is None):
             register_aml_model(
                 model_file,
                 model_name,
-                model_mse,
+                model_tags,
                 exp,
                 run_id,
                 dataset_id,
@@ -127,7 +147,7 @@ def main():
             register_aml_model(
                 model_file,
                 model_name,
-                model_mse,
+                model_tags,
                 exp,
                 run_id,
                 dataset_id,
@@ -152,7 +172,7 @@ def model_already_registered(model_name, exp, run_id):
 def register_aml_model(
     model_path,
     model_name,
-    model_mse,
+    model_tags,
     exp,
     run_id,
     dataset_id,
@@ -162,8 +182,8 @@ def register_aml_model(
     try:
         tagsValue = {"area": "diabetes_regression",
                      "run_id": run_id,
-                     "experiment_name": exp.name,
-                     "mse": model_mse}
+                     "experiment_name": exp.name}
+        tagsValue.update(model_tags)
         if (build_id != 'none'):
             model_already_registered(model_name, exp, run_id)
             tagsValue["BuildId"] = build_id

diabetes_regression/training/train_aml.py

@@ -55,7 +55,7 @@ def main():
         "--model_name",
         type=str,
         help="Name of the Model",
-        default="sklearn_regression_model.pkl",
+        default="diabetes_model.pkl",
     )
 
     parser.add_argument(