remove modelcatalog

Author: z7ye

docs/source/user_guide/model_deployment/predict.rst

@@ -93,7 +93,7 @@ Model framework serialization
    pytorch_model.predict(byte_im)['prediction'][0][:10]
 
    pytorch_model.delete_deployment(wait_for_completion=True)
-   ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+   pytorch_model.delete()
 
 
 The change needed in `score.py`:

docs/source/user_guide/model_registration/frameworks/genericmodel.rst

@@ -170,7 +170,7 @@ Here is a more realistic  example using CatBoost model.
     catboost_model.deploy()
     catboost_model.predict(X_test)
     catboost_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    catboost_model.delete() # delete the model
 
 
 Example -- Save Your Own Model

docs/source/user_guide/model_serialization/automlmodel.rst

@@ -179,5 +179,4 @@ Example
   deploy = automl_model.deploy(display_name='Demo AutoMLModel deployment')
   automl_model.predict(test.X.iloc[:10])
   automl_model.delete_deployment(wait_for_completion=True)
-  ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
-
+  automl_model.delete()

docs/source/user_guide/model_serialization/genericmodel.rst

@@ -188,7 +188,7 @@ By default, the ``GenericModel`` serializes to a pickle file. The following exam
     catboost_model.deploy()
     catboost_model.predict(X_test)
     catboost_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    catboost_model.delete() # delete the model
 
 You can also use the shortcut ``.prepare_save_deploy()`` instead of calling ``.prepare()``, ``.save()`` and ``.deploy()`` seperately.
 

docs/source/user_guide/model_serialization/lightgbmmodel.rst

@@ -283,5 +283,5 @@ Example
     lightgbm_model.deploy()
     lightgbm_model.predict(X_test_transformed[:10])['prediction']
     lightgbm_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    lightgbm_model.delete()
 

docs/source/user_guide/model_serialization/pytorchmodel.rst

@@ -195,5 +195,5 @@ Example
     pytorch_model.deploy()
     pytorch_model.predict(test_data)
     pytorch_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    pytorch_model.delete()
 

docs/source/user_guide/model_serialization/quick_start.rst

@@ -46,7 +46,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     deploy = automl_model.deploy(display_name='Demo AutoMLModel deployment')
     automl_model.predict(test.X.iloc[:10])
     automl_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    automl_model.delete()
 
 GenericModel
 ------------
@@ -72,7 +72,8 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model.deploy()
     model.predict(2)
     model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    model.delete()
+
 
 
 LightGBMModel
@@ -105,7 +106,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model_deployment = lightgbm_model.deploy()
     lightgbm_model.predict(X_test)
     lightgbm_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    lightgbm_model.delete()
 
 
 PyTorchModel
@@ -148,7 +149,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model_deployment = torch_model.deploy()
     torch_model.predict(test_data)
     torch_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    torch_model.delete()
 
 
 SklearnModel
@@ -178,7 +179,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model_deployment = sklearn_model.deploy()
     sklearn_model.predict(X_test)
     sklearn_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    sklearn_model.delete()
 
 
 TensorFlowModel
@@ -216,7 +217,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model_deployment = tf_model.deploy()
     tf_model.predict(x_test[:1])
     tf_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    tf_model.delete()
 
 
 XGBoostModel
@@ -247,7 +248,7 @@ Create a model, prepare it, verify that it works, save it to the model catalog,
     model_deployment = xgboost_model.deploy()
     xgboost_model.predict(X_test)
     xgboost_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    xgboost_model.delete()
 
 Shortcut
 ========

docs/source/user_guide/model_serialization/sklearnmodel.rst

@@ -250,5 +250,5 @@ Examples
     sklearn_model.deploy()
     sklearn_model.predict(X_test.head(2))
     sklearn_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    sklearn_model.delete()
 

docs/source/user_guide/model_serialization/tensorflowmodel.rst

@@ -184,5 +184,5 @@ Example
     tensorflow_model_deployment = model.deploy()
     tensorflow_model.predict(x_test[:1])
     tensorflow_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
+    tensorflow_model.delete()
 

docs/source/user_guide/model_serialization/xgboostmodel.rst

@@ -285,5 +285,4 @@ Example
     xgboost_model.deploy()
     xgboost_model.predict(X_test_transformed[:10])['prediction']
     xgboost_model.delete_deployment(wait_for_completion=True)
-    ModelCatalog(compartment_id=os.environ['NB_SESSION_COMPARTMENT_OCID']).delete_model(model_id)
-
+    xgboost_model.delete()