Added create_training_pipeline_custom_package_job_sample

samples/model-builder/conftest.py

@@ -162,8 +162,8 @@ def mock_init_custom_training_job():
 
 
 @pytest.fixture
-def mock_run_custom_container_training_job():
-    with patch.object(aiplatform.training_jobs.CustomContainerTrainingJob, "run") as mock:
+def mock_run_custom_training_job():
+    with patch.object(aiplatform.training_jobs.CustomTrainingJob, "run") as mock:
         yield mock
 
 
@@ -174,11 +174,26 @@ def mock_init_custom_container_training_job():
     ) as mock:
         mock.return_value = None
         yield mock
+
+
+@pytest.fixture
+def mock_run_custom_container_training_job():
+    with patch.object(aiplatform.training_jobs.CustomContainerTrainingJob, "run") as mock:
+        yield mock
 
 
 @pytest.fixture
-def mock_run_custom_training_job():
-    with patch.object(aiplatform.training_jobs.CustomTrainingJob, "run") as mock:
+def mock_init_custom_package_training_job():
+    with patch.object(
+        aiplatform.training_jobs.CustomPythonPackageTrainingJob, "__init__"
+    ) as mock:
+        mock.return_value = None
+        yield mock
+
+
+@pytest.fixture
+def mock_run_custom_package_training_job():
+    with patch.object(aiplatform.training_jobs.CustomPythonPackageTrainingJob, "run") as mock:
         yield mock
 
 

samples/model-builder/create_training_pipeline_custom_package_job_sample.py

@@ -0,0 +1,71 @@
+# 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 google.cloud import aiplatform
+from typing import List, Optional, Union
+
+
+#  [START aiplatform_sdk_create_training_pipeline_custom_package_job_sample]
+def create_training_pipeline_custom_package_job_sample(
+    project: str,
+    location: str,
+    staging_bucket: str,
+    display_name: str,
+    python_package_gcs_uri: str,
+    python_module_name: str,
+    container_uri: str,    
+    model_serving_container_image_uri: str,    
+    model_display_name: Optional[str] = None,
+    args: Optional[List[Union[str, float, int]]] = None,
+    replica_count: int = 1,
+    machine_type: str = "n1-standard-4",
+    accelerator_type: str = "ACCELERATOR_TYPE_UNSPECIFIED",
+    accelerator_count: int = 0,
+    training_fraction_split: float = 0.8,
+    validation_fraction_split: float = 0.1,
+    test_fraction_split: float = 0.1,
+    sync: bool = True,
+):
+    aiplatform.init(project=project, location=location, staging_bucket=staging_bucket)
+
+    job = aiplatform.CustomPythonPackageTrainingJob(
+        display_name=display_name,
+        python_package_gcs_uri=python_package_gcs_uri,
+        python_module_name=python_module_name,
+        container_uri=container_uri,
+        model_serving_container_image_uri=model_serving_container_image_uri,
+    )
+
+    model = job.run(
+        model_display_name=model_display_name,
+        args=args,
+        replica_count=replica_count,
+        machine_type=machine_type,
+        accelerator_type=accelerator_type,
+        accelerator_count=accelerator_count,
+        training_fraction_split=training_fraction_split,
+        validation_fraction_split=validation_fraction_split,
+        test_fraction_split=test_fraction_split,        
+        sync=sync,
+    )
+
+    model.wait()
+
+    print(model.display_name)
+    print(model.resource_name)
+    print(model.uri)
+    return model
+
+
+#  [END aiplatform_sdk_create_training_pipeline_custom_package_job_sample]

samples/model-builder/create_training_pipeline_custom_package_job_test.py

@@ -0,0 +1,68 @@
+# 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 create_training_pipeline_custom_package_job_sample
+import test_constants as constants
+
+
+def test_create_training_pipeline_custom_package_job_sample(
+    mock_sdk_init,
+    mock_init_custom_package_training_job,
+    mock_run_custom_package_training_job,
+):
+
+    create_training_pipeline_custom_package_job_sample.create_training_pipeline_custom_package_job_sample(
+        project=constants.PROJECT,
+        location=constants.LOCATION,
+        staging_bucket=constants.STAGING_BUCKET,
+        display_name=constants.DISPLAY_NAME,
+        python_package_gcs_uri=constants.PYTHON_PACKAGE_GCS_URI,
+        python_module_name=constants.PYTHON_MODULE_NAME,        
+        container_uri=constants.CONTAINER_URI,
+        args=constants.ARGS,
+        model_serving_container_image_uri=constants.CONTAINER_URI,
+        model_display_name=constants.DISPLAY_NAME_2,
+        replica_count=constants.REPLICA_COUNT,
+        machine_type=constants.MACHINE_TYPE,
+        accelerator_type=constants.ACCELERATOR_TYPE,
+        accelerator_count=constants.ACCELERATOR_COUNT,
+        training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
+        validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
+        test_fraction_split=constants.TEST_FRACTION_SPLIT,
+    )
+
+    mock_sdk_init.assert_called_once_with(
+        project=constants.PROJECT, location=constants.LOCATION, staging_bucket=constants.STAGING_BUCKET
+    )
+
+    mock_init_custom_package_training_job.assert_called_once_with(
+        display_name=constants.DISPLAY_NAME,
+        python_package_gcs_uri=constants.PYTHON_PACKAGE_GCS_URI,
+        python_module_name=constants.PYTHON_MODULE_NAME,
+        container_uri=constants.CONTAINER_URI,
+        model_serving_container_image_uri=constants.CONTAINER_URI,
+    )
+    mock_run_custom_package_training_job.assert_called_once_with(
+        model_display_name=constants.DISPLAY_NAME_2,
+        replica_count=constants.REPLICA_COUNT,
+        machine_type=constants.MACHINE_TYPE,
+        accelerator_type=constants.ACCELERATOR_TYPE,
+        accelerator_count=constants.ACCELERATOR_COUNT,
+        args=constants.ARGS,
+        training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
+        validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
+        test_fraction_split=constants.TEST_FRACTION_SPLIT,
+        sync=True,
+    )

samples/model-builder/test_constants.py

@@ -59,4 +59,15 @@
 REPLICA_COUNT = 1
 MACHINE_TYPE = "n1-standard-4"
 ACCELERATOR_TYPE = "ACCELERATOR_TYPE_UNSPECIFIED"
-ACCELERATOR_COUNT = 0
+ACCELERATOR_COUNT = 0
+MODEL_SERVING_CONTAINER_COMMAND=['/usr/bin/tensorflow_model_server'],
+MODEL_SERVING_CONTAINER_ARGS=[
+    f'--model_name={MODEL_NAME}',
+    '--model_base_path=$(AIP_STORAGE_URI)',
+    '--rest_api_port=8080',
+    '--port=8500',
+    '--file_system_poll_wait_seconds=31540000'],
+MODEL_SERVING_CONTAINER_PREDICT_ROUTE=f'/v1/models/{MODEL_NAME}:predict',
+MODEL_SERVING_CONTAINER_HEALTH_ROUTE=f'/v1/models/{MODEL_NAME}'
+PYTHON_PACKAGE_GCS_URI="gs://bucket3/custom-training-python-package/my_app/trainer-0.1.tar.gz"
+PYTHON_MODULE_NAME="trainer.task"