feat: Added explain tabular samples

samples/model-builder/conftest.py

@@ -237,8 +237,9 @@ def mock_batch_predict_model(mock_model):
 
 
 @pytest.fixture
-def mock_upload_model():
-    with patch.object(aiplatform.models.Model, "upload") as mock:
+def mock_upload_model(mock_model):
+    with patch.object(aiplatform.Model, "upload") as mock:
+        mock.return_value = mock_model
         yield mock
 
 
@@ -277,7 +278,7 @@ def mock_endpoint():
 
 @pytest.fixture
 def mock_create_endpoint():
-    with patch.object(aiplatform.Endpoint, "create") as mock:
+    with patch.object(aiplatform.models.Endpoint, "create") as mock:
         yield mock
 
 
@@ -286,3 +287,10 @@ def mock_get_endpoint(mock_endpoint):
     with patch.object(aiplatform, "Endpoint") as mock_get_endpoint:
         mock_get_endpoint.return_value = mock_endpoint
         yield mock_get_endpoint
+
+
+@pytest.fixture
+def mock_endpoint_explain(mock_endpoint):
+    with patch.object(mock_endpoint, "explain") as mock_endpoint_explain:
+        mock_get_endpoint.return_value = mock_endpoint
+        yield mock_endpoint_explain

samples/model-builder/create_and_import_dataset_video_sample_test.py

@@ -16,7 +16,6 @@
 from google.cloud.aiplatform import schema
 
 import create_and_import_dataset_video_sample
-
 import test_constants as constants
 
 

samples/model-builder/explain_tabular_sample.py

@@ -0,0 +1,50 @@
+# Copyright 2021 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Dict
+
+from google.cloud import aiplatform
+
+
+#  [START aiplatform_sdk_explain_tabular_sample]
+def explain_tabular_sample(
+    project: str, location: str, endpoint_id: str, instance_dict: Dict
+):
+
+    aiplatform.init(project=project, location=location)
+
+    endpoint = aiplatform.Endpoint(endpoint_id)
+
+    response = endpoint.explain(instances=[instance_dict], parameters={})
+
+    for explanation in response.explanations:
+        print(" explanation")
+        # Feature attributions.
+        attributions = explanation.attributions
+        for attribution in attributions:
+            print("  attribution")
+            print("   baseline_output_value:", attribution.baseline_output_value)
+            print("   instance_output_value:", attribution.instance_output_value)
+            print("   output_display_name:", attribution.output_display_name)
+            print("   approximation_error:", attribution.approximation_error)
+            print("   output_name:", attribution.output_name)
+            output_index = attribution.output_index
+            for output_index in output_index:
+                print("   output_index:", output_index)
+
+    for prediction in response.predictions:
+        print(prediction)
+
+
+#  [END aiplatform_sdk_explain_tabular_sample]

samples/model-builder/explain_tabular_sample_test.py

@@ -0,0 +1,39 @@
+# Copyright 2021 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import explain_tabular_sample
+import test_constants as constants
+
+
+def test_explain_tabular_sample(
+    mock_sdk_init, mock_endpoint, mock_get_endpoint, mock_endpoint_explain
+):
+
+    explain_tabular_sample.explain_tabular_sample(
+        project=constants.PROJECT,
+        location=constants.LOCATION,
+        endpoint_id=constants.ENDPOINT_NAME,
+        instance_dict=constants.PREDICTION_TABULAR_INSTANCE,
+    )
+
+    mock_sdk_init.assert_called_once_with(
+        project=constants.PROJECT, location=constants.LOCATION
+    )
+
+    mock_get_endpoint.assert_called_once_with(constants.ENDPOINT_NAME,)
+
+    mock_endpoint_explain.assert_called_once_with(
+        instances=[constants.PREDICTION_TABULAR_INSTANCE], parameters={}
+    )

samples/model-builder/import_data_video_classification_sample_test.py

@@ -17,7 +17,6 @@
 import pytest
 
 import import_data_video_classification_sample
-
 import test_constants as constants
 
 

samples/model-builder/test_constants.py

@@ -131,15 +131,31 @@
     inputs={
         "features": {
             "input_tensor_name": "dense_input",
-            "encoding": "BAG_OF_FEATURES",
+            # Input is tabular data
             "modality": "numeric",
-            "index_feature_mapping": ["abc", "def", "ghj"],
+            # Assign feature names to the inputs for explanation
+            "encoding": "BAG_OF_FEATURES",
+            "index_feature_mapping": [
+                "crim",
+                "zn",
+                "indus",
+                "chas",
+                "nox",
+                "rm",
+                "age",
+                "dis",
+                "rad",
+                "tax",
+                "ptratio",
+                "b",
+                "lstat",
+            ],
         }
     },
-    outputs={"medv": {"output_tensor_name": "dense_2"}},
+    outputs={"prediction": {"output_tensor_name": "dense_2"}},
 )
 EXPLANATION_PARAMETERS = aiplatform.explain.ExplanationParameters(
-    {"sampled_shapley_attribution": {"path_count": 10}}
+    {"xrai_attribution": {"step_count": 1}}
 )
 
 # Endpoint constants
@@ -148,4 +164,16 @@
 TRAFFIC_SPLIT = {"a": 99, "b": 1}
 MIN_REPLICA_COUNT = 1
 MAX_REPLICA_COUNT = 1
+ACCELERATOR_TYPE = "NVIDIA_TESLA_P100"
+ACCELERATOR_COUNT = 2
 ENDPOINT_DEPLOY_METADATA = ()
+PREDICTION_TABULAR_INSTANCE = {
+    "longitude": "-124.35",
+    "latitude": "40.54",
+    "housing_median_age": "52.0",
+    "total_rooms": "1820.0",
+    "total_bedrooms": "300.0",
+    "population": "806",
+    "households": "270.0",
+    "median_income": "3.014700",
+}

samples/model-builder/upload_model_explain_tabular_managed_container_sample.py

@@ -0,0 +1,70 @@
+# Copyright 2021 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Dict, Optional, Sequence
+
+from google.cloud import aiplatform
+
+
+#  [START aiplatform_sdk_upload_model_explain_tabular_managed_container_sample]
+def upload_model_explain_tabular_managed_container_sample(
+    project,
+    location,
+    model_display_name: str,
+    serving_container_image_uri: str,
+    artifact_uri: Optional[str] = None,
+    serving_container_predict_route: Optional[str] = None,
+    serving_container_health_route: Optional[str] = None,
+    description: Optional[str] = None,
+    serving_container_command: Optional[Sequence[str]] = None,
+    serving_container_args: Optional[Sequence[str]] = None,
+    serving_container_environment_variables: Optional[Dict[str, str]] = None,
+    serving_container_ports: Optional[Sequence[int]] = None,
+    instance_schema_uri: Optional[str] = None,
+    parameters_schema_uri: Optional[str] = None,
+    prediction_schema_uri: Optional[str] = None,
+    explanation_metadata: Optional[aiplatform.explain.ExplanationMetadata] = None,
+    explanation_parameters: Optional[aiplatform.explain.ExplanationParameters] = None,
+    sync: bool = True,
+):
+
+    aiplatform.init(project=project, location=location)
+
+    model = aiplatform.Model.upload(
+        display_name=model_display_name,
+        serving_container_image_uri=serving_container_image_uri,
+        artifact_uri=artifact_uri,
+        serving_container_predict_route=serving_container_predict_route,
+        serving_container_health_route=serving_container_health_route,
+        description=description,
+        serving_container_command=serving_container_command,
+        serving_container_args=serving_container_args,
+        serving_container_environment_variables=serving_container_environment_variables,
+        serving_container_ports=serving_container_ports,
+        instance_schema_uri=instance_schema_uri,
+        parameters_schema_uri=parameters_schema_uri,
+        prediction_schema_uri=prediction_schema_uri,
+        explanation_metadata=explanation_metadata,
+        explanation_parameters=explanation_parameters,
+        sync=sync,
+    )
+
+    model.wait()
+
+    print(model.display_name)
+    print(model.resource_name)
+    return model
+
+
+#  [END aiplatform_sdk_upload_model_explain_tabular_managed_container_sample]

samples/model-builder/upload_model_explain_tabular_managed_container_sample_test.py

@@ -0,0 +1,65 @@
+# Copyright 2021 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import test_constants as constants
+
+import upload_model_explain_tabular_managed_container_sample
+
+
+def test_upload_model_explain_tabular_managed_container_sample(
+    mock_sdk_init, mock_model, mock_init_model, mock_upload_model
+):
+
+    upload_model_explain_tabular_managed_container_sample.upload_model_explain_tabular_managed_container_sample(
+        project=constants.PROJECT,
+        location=constants.LOCATION,
+        model_display_name=constants.MODEL_NAME,
+        serving_container_image_uri=constants.SERVING_CONTAINER_IMAGE_URI,
+        artifact_uri=constants.MODEL_ARTIFACT_URI,
+        serving_container_predict_route=constants.SERVING_CONTAINER_PREDICT_ROUTE,
+        serving_container_health_route=constants.SERVING_CONTAINER_HEALTH_ROUTE,
+        description=constants.DESCRIPTION,
+        serving_container_command=constants.SERVING_CONTAINER_COMMAND,
+        serving_container_args=constants.SERVING_CONTAINER_ARGS,
+        serving_container_environment_variables=constants.SERVING_CONTAINER_ENVIRONMENT_VARIABLES,
+        serving_container_ports=constants.SERVING_CONTAINER_PORTS,
+        instance_schema_uri=constants.INSTANCE_SCHEMA_URI,
+        parameters_schema_uri=constants.PARAMETERS_SCHEMA_URI,
+        prediction_schema_uri=constants.PREDICTION_SCHEMA_URI,
+        explanation_metadata=constants.EXPLANATION_METADATA,
+        explanation_parameters=constants.EXPLANATION_PARAMETERS,
+    )
+
+    mock_sdk_init.assert_called_once_with(
+        project=constants.PROJECT, location=constants.LOCATION
+    )
+
+    mock_upload_model.assert_called_once_with(
+        display_name=constants.MODEL_NAME,
+        serving_container_image_uri=constants.SERVING_CONTAINER_IMAGE_URI,
+        artifact_uri=constants.MODEL_ARTIFACT_URI,
+        serving_container_predict_route=constants.SERVING_CONTAINER_PREDICT_ROUTE,
+        serving_container_health_route=constants.SERVING_CONTAINER_HEALTH_ROUTE,
+        description=constants.DESCRIPTION,
+        serving_container_command=constants.SERVING_CONTAINER_COMMAND,
+        serving_container_args=constants.SERVING_CONTAINER_ARGS,
+        serving_container_environment_variables=constants.SERVING_CONTAINER_ENVIRONMENT_VARIABLES,
+        serving_container_ports=constants.SERVING_CONTAINER_PORTS,
+        instance_schema_uri=constants.INSTANCE_SCHEMA_URI,
+        parameters_schema_uri=constants.PARAMETERS_SCHEMA_URI,
+        prediction_schema_uri=constants.PREDICTION_SCHEMA_URI,
+        explanation_metadata=constants.EXPLANATION_METADATA,
+        explanation_parameters=constants.EXPLANATION_PARAMETERS,
+        sync=True,
+    )