feature: Add business details and hyper parameters fields and update test_model_card.py

Author: Haonian Wang

src/sagemaker/model_card/model_card.py

@@ -493,6 +493,11 @@ def _create_training_details(training_job_data: dict, cls: "TrainingDetails", **
                 ]
                 if "FinalMetricDataList" in training_job_data
                 else [],
+                # "hyper_parameters": print(training_job_data["HyperParameters"]),
+                "hyper_parameters": [
+                    HyperParameter(key, value)
+                    for key, value in training_job_data["HyperParameters"].items()
+                ],
             }
             kwargs.update({"training_job_details": TrainingJobDetails(**job)})
             instance = cls(**kwargs)

tests/unit/test_model_card.py

@@ -361,29 +361,22 @@
                         "Timestamp": datetime.datetime(2022, 9, 5, 19, 18, 40),
                     },
                 ],
-                "HyperParameters": [
-                    {
-                        "feature_dim": "2",
-                        "mini_batch_size": "10",
-                        "predictor_type": "binary_classifier",
-                    },
-                    {
-                        "_kfold": "5",
-                        "_tuning_objective_metric": "validation:accuracy",
-                        "alpha": "0.0037170512924477993",
-                        "colsample_bytree": "0.7476726040667319",
-                        "eta": "0.011391935592233605",
-                        "eval_metric": "accuracy,f1,balanced_accuracy,precision_macro,recall_macro,mlogloss",
-                        "gamma": "1.8903517751689445",
-                        "lambda": "0.5098604662224621",
-                        "max_depth": "3",
-                        "min_child_weight": "5.081388147234708e-06",
-                        "num_class": "28",
-                        "num_round": "165",
-                        "objective": "multi:softprob",
-                        "subsample": "0.8828549481113146",
-                    },
-                ],
+                "HyperParameters": {
+                    "_kfold": "5",
+                    "_tuning_objective_metric": "validation:accuracy",
+                    "alpha": "0.0037170512924477993",
+                    "colsample_bytree": "0.7476726040667319",
+                    "eta": "0.011391935592233605",
+                    "eval_metric": "accuracy,f1,balanced_accuracy,precision_macro,recall_macro,mlogloss",
+                    "gamma": "1.8903517751689445",
+                    "lambda": "0.5098604662224621",
+                    "max_depth": "3",
+                    "min_child_weight": "5.081388147234708e-06",
+                    "num_class": "28",
+                    "num_round": "165",
+                    "objective": "multi:softprob",
+                    "subsample": "0.8828549481113146",
+                },
                 "CreatedBy": {},
             }
         }
@@ -1065,7 +1058,7 @@ def test_training_details_autodiscovery_from_model_overview(
     assert len(training_details.training_job_details.training_metrics) == len(
         SEARCH_TRAINING_JOB_EXAMPLE["Results"][0]["TrainingJob"]["FinalMetricDataList"]
     )
-    assert len(training_details.training_job_details.training_metrics) == len(
+    assert len(training_details.training_job_details.hyper_parameters) == len(
         SEARCH_TRAINING_JOB_EXAMPLE["Results"][0]["TrainingJob"]["HyperParameters"]
     )
     assert training_details.training_job_details.training_environment.container_image == [
@@ -1097,8 +1090,10 @@ def test_training_details_autodiscovery_from_model_overview_autopilot(
         model_overview=model_overview_example, sagemaker_session=session
     )
 
+    # There are 0 required keys in training_metrics field in SEARCH_TRAINING_JOB_AUTOPILOT_EXAMPLE has
     assert len(training_details.training_job_details.training_metrics) == 0
-    assert len(training_details.training_job_details.hyper_parameters) == 0
+    # There are 3 required keys in hyper_parameters field in SEARCH_TRAINING_JOB_AUTOPILOT_EXAMPLE has
+    assert len(training_details.training_job_details.hyper_parameters) == 3
 
 
 @patch("sagemaker.Session")
@@ -1115,7 +1110,7 @@ def test_training_details_autodiscovery_from_job_name(session):
     assert len(training_details.training_job_details.training_metrics) == len(
         SEARCH_TRAINING_JOB_EXAMPLE["Results"][0]["TrainingJob"]["FinalMetricDataList"]
     )
-    assert len(training_details.training_job_details.training_metrics) == len(
+    assert len(training_details.training_job_details.hyper_parameters) == len(
         SEARCH_TRAINING_JOB_EXAMPLE["Results"][0]["TrainingJob"]["HyperParameters"]
     )
     assert training_details.training_job_details.training_environment.container_image == [