feat!: move to microgen (#61)

See UPGRADING.md

Author: busunkim96

automl/beta/batch_predict.py

@@ -27,21 +27,27 @@ def batch_predict(
     prediction_client = automl.PredictionServiceClient()
 
     # Get the full path of the model.
-    model_full_id = prediction_client.model_path(
+    model_full_id = automl.AutoMlClient.model_path(
         project_id, "us-central1", model_id
     )
 
-    gcs_source = automl.types.GcsSource(input_uris=[input_uri])
+    gcs_source = automl.GcsSource(input_uris=[input_uri])
 
-    input_config = automl.types.BatchPredictInputConfig(gcs_source=gcs_source)
-    gcs_destination = automl.types.GcsDestination(output_uri_prefix=output_uri)
-    output_config = automl.types.BatchPredictOutputConfig(
+    input_config = automl.BatchPredictInputConfig(gcs_source=gcs_source)
+    gcs_destination = automl.GcsDestination(output_uri_prefix=output_uri)
+    output_config = automl.BatchPredictOutputConfig(
         gcs_destination=gcs_destination
     )
     params = {}
 
+    request = automl.BatchPredictRequest(
+        name=model_full_id,
+        input_config=input_config,
+        output_config=output_config,
+        params=params
+    )
     response = prediction_client.batch_predict(
-        model_full_id, input_config, output_config, params=params
+        request=request
     )
 
     print("Waiting for operation to complete...")

automl/beta/cancel_operation.py

@@ -31,7 +31,7 @@ def sample_cancel_operation(project, operation_id):
 
     client = automl_v1beta1.AutoMlClient()
 
-    operations_client = client.transport._operations_client
+    operations_client = client._transport.operations_client
 
     # project = '[Google Cloud Project ID]'
     # operation_id = '[Operation ID]'

automl/beta/delete_dataset.py

@@ -24,7 +24,7 @@ def delete_dataset(project_id="YOUR_PROJECT_ID", dataset_id="YOUR_DATASET_ID"):
     dataset_full_id = client.dataset_path(
         project_id, "us-central1", dataset_id
     )
-    response = client.delete_dataset(dataset_full_id)
+    response = client.delete_dataset(name=dataset_full_id)
 
     print("Dataset deleted. {}".format(response.result()))
 # [END automl_delete_dataset_beta]

automl/beta/delete_dataset_test.py

@@ -27,13 +27,13 @@
 @pytest.fixture(scope="function")
 def dataset_id():
     client = automl.AutoMlClient()
-    project_location = client.location_path(PROJECT_ID, "us-central1")
+    project_location = f"projects/{PROJECT_ID}/locations/us-central1"
     display_name = "test_{}".format(uuid.uuid4()).replace("-", "")[:32]
-    metadata = automl.types.TextExtractionDatasetMetadata()
-    dataset = automl.types.Dataset(
+    metadata = automl.TextExtractionDatasetMetadata()
+    dataset = automl.Dataset(
         display_name=display_name, text_extraction_dataset_metadata=metadata
     )
-    response = client.create_dataset(project_location, dataset)
+    response = client.create_dataset(parent=project_location, dataset=dataset)
     dataset_id = response.name.split("/")[-1]
 
     yield dataset_id

automl/beta/delete_model.py

@@ -25,7 +25,7 @@ def delete_model(project_id, model_id):
     client = automl.AutoMlClient()
     # Get the full path of the model.
     model_full_id = client.model_path(project_id, "us-central1", model_id)
-    response = client.delete_model(model_full_id)
+    response = client.delete_model(name=model_full_id)
 
     print("Model deleted. {}".format(response.result()))
     # [END automl_delete_model_beta]

automl/beta/get_model.py

@@ -25,10 +25,10 @@ def get_model(project_id, model_id):
     client = automl.AutoMlClient()
     # Get the full path of the model.
     model_full_id = client.model_path(project_id, "us-central1", model_id)
-    model = client.get_model(model_full_id)
+    model = client.get_model(name=model_full_id)
 
     # Retrieve deployment state.
-    if model.deployment_state == automl.enums.Model.DeploymentState.DEPLOYED:
+    if model.deployment_state == automl.Model.DeploymentState.DEPLOYED:
         deployment_state = "deployed"
     else:
         deployment_state = "undeployed"
@@ -37,8 +37,6 @@ def get_model(project_id, model_id):
     print("Model name: {}".format(model.name))
     print("Model id: {}".format(model.name.split("/")[-1]))
     print("Model display name: {}".format(model.display_name))
-    print("Model create time:")
-    print("\tseconds: {}".format(model.create_time.seconds))
-    print("\tnanos: {}".format(model.create_time.nanos))
+    print("Model create time: {}".format(model.create_time))
     print("Model deployment state: {}".format(deployment_state))
     # [END automl_get_model_beta]

automl/beta/get_model_evaluation.py

@@ -26,18 +26,15 @@ def get_model_evaluation(project_id, model_id, model_evaluation_id):
 
     client = automl.AutoMlClient()
     # Get the full path of the model evaluation.
-    model_evaluation_full_id = client.model_evaluation_path(
-        project_id, "us-central1", model_id, model_evaluation_id
-    )
+    model_path = client.model_path(project_id, "us-central1", model_id)
+    model_evaluation_full_id = f"{model_path}/modelEvaluations/{model_evaluation_id}"
 
     # Get complete detail of the model evaluation.
-    response = client.get_model_evaluation(model_evaluation_full_id)
+    response = client.get_model_evaluation(name=model_evaluation_full_id)
 
     print("Model evaluation name: {}".format(response.name))
     print("Model annotation spec id: {}".format(response.annotation_spec_id))
-    print("Create Time:")
-    print("\tseconds: {}".format(response.create_time.seconds))
-    print("\tnanos: {}".format(response.create_time.nanos / 1e9))
+    print("Create Time: {}".format(response.create_time))
     print(
         "Evaluation example count: {}".format(response.evaluated_example_count)
     )

automl/beta/get_model_evaluation_test.py

@@ -27,9 +27,12 @@
 def model_evaluation_id():
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
-    generator = client.list_model_evaluations(model_full_id, "").pages
-    page = next(generator)
-    evaluation = page.next()
+    request = automl.ListModelEvaluationsRequest(
+        parent=model_full_id,
+        filter=""
+    )
+    evaluations = client.list_model_evaluations(request=request)
+    evaluation = next(iter(evaluations))
     model_evaluation_id = evaluation.name.split(
         "{}/modelEvaluations/".format(MODEL_ID)
     )[1].split("\n")[0]

automl/beta/get_operation_status.py

@@ -24,7 +24,7 @@ def get_operation_status(
     client = automl.AutoMlClient()
 
     # Get the latest state of a long-running operation.
-    response = client.transport._operations_client.get_operation(
+    response = client._transport.operations_client.get_operation(
         operation_full_id
     )
 

automl/beta/get_operation_status_test.py

@@ -25,8 +25,8 @@
 @pytest.fixture(scope="function")
 def operation_id():
     client = automl.AutoMlClient()
-    project_location = client.location_path(PROJECT_ID, "us-central1")
-    generator = client.transport._operations_client.list_operations(
+    project_location = f"projects/{PROJECT_ID}/locations/us-central1"
+    generator = client._transport.operations_client.list_operations(
         project_location, filter_=""
     ).pages
     page = next(generator)

automl/beta/import_dataset.py

@@ -30,10 +30,10 @@ def import_dataset(
     )
     # Get the multiple Google Cloud Storage URIs
     input_uris = path.split(",")
-    gcs_source = automl.types.GcsSource(input_uris=input_uris)
-    input_config = automl.types.InputConfig(gcs_source=gcs_source)
+    gcs_source = automl.GcsSource(input_uris=input_uris)
+    input_config = automl.InputConfig(gcs_source=gcs_source)
     # Import data from the input URI
-    response = client.import_data(dataset_full_id, input_config)
+    response = client.import_data(name=dataset_full_id, input_config=input_config)
 
     print("Processing import...")
     print("Data imported. {}".format(response.result()))

automl/beta/list_datasets.py

@@ -22,19 +22,18 @@ def list_datasets(project_id="YOUR_PROJECT_ID"):
     """List datasets."""
     client = automl.AutoMlClient()
     # A resource that represents Google Cloud Platform location.
-    project_location = client.location_path(project_id, "us-central1")
+    project_location = f"projects/{project_id}/locations/us-central1"
 
     # List all the datasets available in the region.
-    response = client.list_datasets(project_location, "")
+    request = automl.ListDatasetsRequest(parent=project_location, filter="")
+    response = client.list_datasets(request=request)
 
     print("List of datasets:")
     for dataset in response:
         print("Dataset name: {}".format(dataset.name))
         print("Dataset id: {}".format(dataset.name.split("/")[-1]))
         print("Dataset display name: {}".format(dataset.display_name))
-        print("Dataset create time:")
-        print("\tseconds: {}".format(dataset.create_time.seconds))
-        print("\tnanos: {}".format(dataset.create_time.nanos))
+        print("Dataset create time: {}".format(dataset.create_time))
         # [END automl_video_object_tracking_list_datasets_beta]
 
         print(

automl/beta/list_models.py

@@ -23,15 +23,16 @@ def list_models(project_id):
 
     client = automl.AutoMlClient()
     # A resource that represents Google Cloud Platform location.
-    project_location = client.location_path(project_id, "us-central1")
-    response = client.list_models(project_location, "")
+    project_location = f"projects/{project_id}/locations/us-central1"
+    request = automl.ListModelsRequest(parent=project_location, filter="")
+    response = client.list_models(request=request)
 
     print("List of models:")
     for model in response:
         # Display the model information.
         if (
             model.deployment_state
-            == automl.enums.Model.DeploymentState.DEPLOYED
+            == automl.Model.DeploymentState.DEPLOYED
         ):
             deployment_state = "deployed"
         else:
@@ -40,8 +41,6 @@ def list_models(project_id):
         print("Model name: {}".format(model.name))
         print("Model id: {}".format(model.name.split("/")[-1]))
         print("Model display name: {}".format(model.display_name))
-        print("Model create time:")
-        print("\tseconds: {}".format(model.create_time.seconds))
-        print("\tnanos: {}".format(model.create_time.nanos))
+        print("Model create time: {}".format(model.create_time))
         print("Model deployment state: {}".format(deployment_state))
     # [END automl_list_models_beta]

automl/beta/set_endpoint.py

@@ -27,13 +27,18 @@ def set_endpoint(project_id):
 
     # A resource that represents Google Cloud Platform location.
     # project_id = 'YOUR_PROJECT_ID'
-    project_location = client.location_path(project_id, 'eu')
+    project_location = f"projects/{project_id}/locations/eu"
     # [END automl_set_endpoint]
 
     # List all the datasets available
     # Note: Create a dataset in `eu`, before calling `list_datasets`.
+    request = automl.ListDatasetsRequest(
+        parent=project_location,
+        filter=""
+    )
     response = client.list_datasets(
-        project_location, filter_='')
+        request=request
+    )
 
     for dataset in response:
         print(dataset)

automl/beta/video_classification_create_dataset.py

@@ -25,15 +25,15 @@ def create_dataset(
     client = automl.AutoMlClient()
 
     # A resource that represents Google Cloud Platform location.
-    project_location = client.location_path(project_id, "us-central1")
-    metadata = automl.types.VideoClassificationDatasetMetadata()
-    dataset = automl.types.Dataset(
+    project_location = f"projects/{project_id}/locations/us-central1"
+    metadata = automl.VideoClassificationDatasetMetadata()
+    dataset = automl.Dataset(
         display_name=display_name,
         video_classification_dataset_metadata=metadata,
     )
 
     # Create a dataset with the dataset metadata in the region.
-    created_dataset = client.create_dataset(project_location, dataset)
+    created_dataset = client.create_dataset(parent=project_location, dataset=dataset)
 
     # Display the dataset information
     print("Dataset name: {}".format(created_dataset.name))

automl/beta/video_classification_create_dataset_test.py

@@ -34,7 +34,7 @@ def teardown():
     dataset_full_id = client.dataset_path(
         PROJECT_ID, "us-central1", DATASET_ID
     )
-    response = client.delete_dataset(dataset_full_id)
+    response = client.delete_dataset(name=dataset_full_id)
     response.result()
 
 

automl/beta/video_classification_create_model.py

@@ -25,18 +25,19 @@ def create_model(
     client = automl.AutoMlClient()
 
     # A resource that represents Google Cloud Platform location.
-    project_location = client.location_path(project_id, "us-central1")
+    project_location = f"projects/{project_id}/locations/us-central1"
     # Leave model unset to use the default base model provided by Google
-    metadata = automl.types.VideoClassificationModelMetadata()
-    model = automl.types.Model(
+    metadata = automl.VideoClassificationModelMetadata()
+    model = automl.Model(
         display_name=display_name,
         dataset_id=dataset_id,
         video_classification_model_metadata=metadata,
     )
 
     # Create a model with the model metadata in the region.
-    response = client.create_model(project_location, model)
+    response = client.create_model(parent=project_location, model=model)
 
     print("Training operation name: {}".format(response.operation.name))
     print("Training started...")
 # [END automl_video_classification_create_model_beta]
+    return response

automl/beta/video_classification_create_model_test.py

@@ -31,14 +31,15 @@ def teardown():
 
     # Cancel the training operation
     client = automl.AutoMlClient()
-    client.transport._operations_client.cancel_operation(OPERATION_ID)
+    client._transport.operations_client.cancel_operation(OPERATION_ID)
 
 
 def test_video_classification_create_model(capsys):
     model_name = "test_{}".format(uuid.uuid4()).replace("-", "")[:32]
     video_classification_create_model.create_model(
         PROJECT_ID, DATASET_ID, model_name
     )
+
     out, _ = capsys.readouterr()
     assert "Training started" in out
 

automl/beta/video_object_tracking_create_dataset.py

@@ -23,15 +23,15 @@ def create_dataset(
     client = automl.AutoMlClient()
 
     # A resource that represents Google Cloud Platform location.
-    project_location = client.location_path(project_id, "us-central1")
-    metadata = automl.types.VideoObjectTrackingDatasetMetadata()
-    dataset = automl.types.Dataset(
+    project_location = f"projects/{project_id}/locations/us-central1"
+    metadata = automl.VideoObjectTrackingDatasetMetadata()
+    dataset = automl.Dataset(
         display_name=display_name,
         video_object_tracking_dataset_metadata=metadata,
     )
 
     # Create a dataset with the dataset metadata in the region.
-    created_dataset = client.create_dataset(project_location, dataset)
+    created_dataset = client.create_dataset(parent=project_location, dataset=dataset)
     # Display the dataset information
     print("Dataset name: {}".format(created_dataset.name))
     print("Dataset id: {}".format(created_dataset.name.split("/")[-1]))

automl/beta/video_object_tracking_create_dataset_test.py

@@ -33,7 +33,7 @@ def teardown():
     dataset_full_id = client.dataset_path(
         PROJECT_ID, "us-central1", DATASET_ID
     )
-    response = client.delete_dataset(dataset_full_id)
+    response = client.delete_dataset(name=dataset_full_id)
     response.result()
 
 

automl/beta/video_object_tracking_create_model.py

@@ -25,17 +25,17 @@ def create_model(
     client = automl.AutoMlClient()
 
     # A resource that represents Google Cloud Platform loacation.
-    project_location = client.location_path(project_id, "us-central1")
+    project_location = f"projects/{project_id}/locations/us-central1"
     # Leave model unset to use the default base model provided by Google
-    metadata = automl.types.VideoObjectTrackingModelMetadata()
-    model = automl.types.Model(
+    metadata = automl.VideoObjectTrackingModelMetadata()
+    model = automl.Model(
         display_name=display_name,
         dataset_id=dataset_id,
         video_object_tracking_model_metadata=metadata,
     )
 
     # Create a model with the model metadata in the region.
-    response = client.create_model(project_location, model)
+    response = client.create_model(parent=project_location, model=model)
 
     print("Training operation name: {}".format(response.operation.name))
     print("Training started...")

automl/beta/video_object_tracking_create_model_test.py

@@ -31,7 +31,7 @@ def teardown():
 
     # Cancel the training operation
     client = automl.AutoMlClient()
-    client.transport._operations_client.cancel_operation(OPERATION_ID)
+    client._transport.operations_client.cancel_operation(OPERATION_ID)
 
 
 def test_video_classification_create_model(capsys):