feat: Added GA support for running Custom and Hp tuning jobs on Persi…

…stent Resources

PiperOrigin-RevId: 620975901

google/cloud/aiplatform/jobs.py

@@ -1731,6 +1731,7 @@ def __init__(
         labels: Optional[Dict[str, str]] = None,
         encryption_spec_key_name: Optional[str] = None,
         staging_bucket: Optional[str] = None,
+        persistent_resource_id: Optional[str] = None,
     ):
         """Constructs a Custom Job with Worker Pool Specs.
 
@@ -1802,6 +1803,13 @@ def __init__(
             staging_bucket (str):
                 Optional. Bucket for produced custom job artifacts. Overrides
                 staging_bucket set in aiplatform.init.
+            persistent_resource_id (str):
+                Optional. The ID of the PersistentResource in the same Project
+                and Location. If this is specified, the job will be run on
+                existing machines held by the PersistentResource instead of
+                on-demand short-live machines. The network and CMEK configs on
+                the job should be consistent with those on the PersistentResource,
+                otherwise, the job will be rejected.
 
         Raises:
             RuntimeError: If staging bucket was not set using aiplatform.init
@@ -1836,6 +1844,7 @@ def __init__(
                 base_output_directory=gca_io_compat.GcsDestination(
                     output_uri_prefix=base_output_dir
                 ),
+                persistent_resource_id=persistent_resource_id,
             ),
             labels=labels,
             encryption_spec=initializer.global_config.get_encryption_spec(
@@ -2669,7 +2678,8 @@ def __init__(
                 of any UTF-8 characters.
             custom_job (aiplatform.CustomJob):
                 Required. Configured CustomJob. The worker pool spec from this custom job
-                applies to the CustomJobs created in all the trials.
+                applies to the CustomJobs created in all the trials. A persistent_resource_id can be
+                specified on the custom job to be used when running this Hyperparameter Tuning job.
             metric_spec: Dict[str, str]
                 Required. Dictionary representing metrics to optimize. The dictionary key is the metric_id,
                 which is reported by your training job, and the dictionary value is the

google/cloud/aiplatform/preview/jobs.py

@@ -70,7 +70,7 @@
 
 
 class CustomJob(jobs.CustomJob):
-    """Vertex AI Custom Job."""
+    """Deprecated. Vertex AI Custom Job (preview)."""
 
     def __init__(
         self,
@@ -88,7 +88,9 @@ def __init__(
         staging_bucket: Optional[str] = None,
         persistent_resource_id: Optional[str] = None,
     ):
-        """Constructs a Custom Job with Worker Pool Specs.
+        """Deprecated. Please use the GA (non-preview) version of this class.
+
+        Constructs a Custom Job with Worker Pool Specs.
 
         ```
         Example usage:
@@ -472,7 +474,7 @@ def submit(
 
 
 class HyperparameterTuningJob(jobs.HyperparameterTuningJob):
-    """Vertex AI Hyperparameter Tuning Job."""
+    """Deprecated. Vertex AI Hyperparameter Tuning Job (preview)."""
 
     def __init__(
         self,
@@ -492,7 +494,8 @@ def __init__(
         labels: Optional[Dict[str, str]] = None,
         encryption_spec_key_name: Optional[str] = None,
     ):
-        """
+        """Deprecated. Please use the GA (non-preview) version of this class.
+
         Configures a HyperparameterTuning Job.
 
         Example usage:

tests/unit/aiplatform/test_custom_job_persistent_resource.py

@@ -20,16 +20,12 @@
 from unittest.mock import patch
 
 from google.cloud import aiplatform
-from google.cloud.aiplatform.compat.services import (
-    job_service_client_v1beta1,
-)
-from google.cloud.aiplatform.compat.types import custom_job_v1beta1
-from google.cloud.aiplatform.compat.types import encryption_spec_v1beta1
-from google.cloud.aiplatform.compat.types import io_v1beta1
-from google.cloud.aiplatform.compat.types import (
-    job_state_v1beta1 as gca_job_state_compat,
-)
-from google.cloud.aiplatform.preview import jobs
+from google.cloud.aiplatform import jobs
+from google.cloud.aiplatform.compat.services import job_service_client_v1
+from google.cloud.aiplatform.compat.types import custom_job_v1
+from google.cloud.aiplatform.compat.types import encryption_spec_v1
+from google.cloud.aiplatform.compat.types import io_v1
+from google.cloud.aiplatform.compat.types import job_state_v1 as gca_job_state_compat
 import constants as test_constants
 import pytest
 
@@ -58,7 +54,7 @@
 
 # CMEK encryption
 _TEST_DEFAULT_ENCRYPTION_KEY_NAME = "key_1234"
-_TEST_DEFAULT_ENCRYPTION_SPEC = encryption_spec_v1beta1.EncryptionSpec(
+_TEST_DEFAULT_ENCRYPTION_SPEC = encryption_spec_v1.EncryptionSpec(
     kms_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME
 )
 
@@ -78,14 +74,14 @@
 
 # Persistent Resource
 _TEST_PERSISTENT_RESOURCE_ID = "test-persistent-resource-1"
-_TEST_CUSTOM_JOB_WITH_PERSISTENT_RESOURCE_PROTO = custom_job_v1beta1.CustomJob(
+_TEST_CUSTOM_JOB_WITH_PERSISTENT_RESOURCE_PROTO = custom_job_v1.CustomJob(
     display_name=_TEST_DISPLAY_NAME,
-    job_spec=custom_job_v1beta1.CustomJobSpec(
+    job_spec=custom_job_v1.CustomJobSpec(
         worker_pool_specs=_TEST_WORKER_POOL_SPEC,
-        base_output_directory=io_v1beta1.GcsDestination(
+        base_output_directory=io_v1.GcsDestination(
             output_uri_prefix=_TEST_BASE_OUTPUT_DIR
         ),
-        scheduling=custom_job_v1beta1.Scheduling(
+        scheduling=custom_job_v1.Scheduling(
             timeout=duration_pb2.Duration(seconds=_TEST_TIMEOUT),
             restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
             disable_retries=_TEST_DISABLE_RETRIES,
@@ -108,21 +104,21 @@ def _get_custom_job_proto(state=None, name=None, error=None):
 
 
 @pytest.fixture
-def create_preview_custom_job_mock():
+def create_custom_job_mock():
     with mock.patch.object(
-        job_service_client_v1beta1.JobServiceClient, "create_custom_job"
-    ) as create_preview_custom_job_mock:
-        create_preview_custom_job_mock.return_value = _get_custom_job_proto(
+        job_service_client_v1.JobServiceClient, "create_custom_job"
+    ) as create_custom_job_mock:
+        create_custom_job_mock.return_value = _get_custom_job_proto(
             name=_TEST_CUSTOM_JOB_NAME,
             state=gca_job_state_compat.JobState.JOB_STATE_PENDING,
         )
-        yield create_preview_custom_job_mock
+        yield create_custom_job_mock
 
 
 @pytest.fixture
 def get_custom_job_mock():
     with patch.object(
-        job_service_client_v1beta1.JobServiceClient, "get_custom_job"
+        job_service_client_v1.JobServiceClient, "get_custom_job"
     ) as get_custom_job_mock:
         get_custom_job_mock.side_effect = [
             _get_custom_job_proto(
@@ -152,7 +148,7 @@ def teardown_method(self):
 
     @pytest.mark.parametrize("sync", [True, False])
     def test_create_custom_job_with_persistent_resource(
-        self, create_preview_custom_job_mock, get_custom_job_mock, sync
+        self, create_custom_job_mock, get_custom_job_mock, sync
     ):
 
         aiplatform.init(
@@ -188,7 +184,7 @@ def test_create_custom_job_with_persistent_resource(
 
         expected_custom_job = _get_custom_job_proto()
 
-        create_preview_custom_job_mock.assert_called_once_with(
+        create_custom_job_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             custom_job=expected_custom_job,
             timeout=None,
@@ -201,7 +197,7 @@ def test_create_custom_job_with_persistent_resource(
         assert job.network == _TEST_NETWORK
 
     def test_submit_custom_job_with_persistent_resource(
-        self, create_preview_custom_job_mock, get_custom_job_mock
+        self, create_custom_job_mock, get_custom_job_mock
     ):
 
         aiplatform.init(
@@ -236,7 +232,7 @@ def test_submit_custom_job_with_persistent_resource(
 
         expected_custom_job = _get_custom_job_proto()
 
-        create_preview_custom_job_mock.assert_called_once_with(
+        create_custom_job_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             custom_job=expected_custom_job,
             timeout=None,

tests/unit/aiplatform/test_hyperparameter_tuning_job_persistent_resource.py

@@ -21,18 +21,18 @@
 
 from google.cloud import aiplatform
 from google.cloud.aiplatform.compat.services import (
-    job_service_client_v1beta1,
+    job_service_client_v1,
 )
 from google.cloud.aiplatform import hyperparameter_tuning as hpt
 from google.cloud.aiplatform.compat.types import (
-    custom_job_v1beta1,
-    encryption_spec_v1beta1,
-    hyperparameter_tuning_job_v1beta1,
-    io_v1beta1,
-    job_state_v1beta1 as gca_job_state_compat,
-    study_v1beta1 as gca_study_compat,
+    custom_job_v1,
+    encryption_spec_v1,
+    hyperparameter_tuning_job_v1,
+    io_v1,
+    job_state_v1 as gca_job_state_compat,
+    study_v1 as gca_study_compat,
 )
-from google.cloud.aiplatform.preview import jobs
+from google.cloud.aiplatform import jobs
 import constants as test_constants
 import pytest
 
@@ -59,7 +59,7 @@
 
 # CMEK encryption
 _TEST_DEFAULT_ENCRYPTION_KEY_NAME = "key_1234"
-_TEST_DEFAULT_ENCRYPTION_SPEC = encryption_spec_v1beta1.EncryptionSpec(
+_TEST_DEFAULT_ENCRYPTION_SPEC = encryption_spec_v1.EncryptionSpec(
     kms_key_name=_TEST_DEFAULT_ENCRYPTION_KEY_NAME
 )
 
@@ -95,12 +95,12 @@
 # Persistent Resource
 _TEST_PERSISTENT_RESOURCE_ID = "test-persistent-resource-1"
 
-_TEST_TRIAL_JOB_SPEC = custom_job_v1beta1.CustomJobSpec(
+_TEST_TRIAL_JOB_SPEC = custom_job_v1.CustomJobSpec(
     worker_pool_specs=test_constants.TrainingJobConstants._TEST_WORKER_POOL_SPEC,
-    base_output_directory=io_v1beta1.GcsDestination(
+    base_output_directory=io_v1.GcsDestination(
         output_uri_prefix=test_constants.TrainingJobConstants._TEST_BASE_OUTPUT_DIR
     ),
-    scheduling=custom_job_v1beta1.Scheduling(
+    scheduling=custom_job_v1.Scheduling(
         timeout=duration_pb2.Duration(seconds=_TEST_TIMEOUT),
         restart_job_on_worker_restart=_TEST_RESTART_JOB_ON_WORKER_RESTART,
         disable_retries=_TEST_DISABLE_RETRIES,
@@ -110,7 +110,7 @@
     persistent_resource_id=_TEST_PERSISTENT_RESOURCE_ID,
 )
 
-_TEST_BASE_HYPERPARAMETER_TUNING_JOB_WITH_PERSISTENT_RESOURCE_PROTO = hyperparameter_tuning_job_v1beta1.HyperparameterTuningJob(
+_TEST_BASE_HYPERPARAMETER_TUNING_JOB_WITH_PERSISTENT_RESOURCE_PROTO = hyperparameter_tuning_job_v1.HyperparameterTuningJob(
     display_name=_TEST_DISPLAY_NAME,
     study_spec=gca_study_compat.StudySpec(
         metrics=[
@@ -197,23 +197,23 @@ def _get_hyperparameter_tuning_job_proto(state=None, name=None, error=None):
 
 
 @pytest.fixture
-def create_preview_hyperparameter_tuning_job_mock():
+def create_hyperparameter_tuning_job_mock():
     with mock.patch.object(
-        job_service_client_v1beta1.JobServiceClient, "create_hyperparameter_tuning_job"
-    ) as create_preview_hyperparameter_tuning_job_mock:
-        create_preview_hyperparameter_tuning_job_mock.return_value = (
+        job_service_client_v1.JobServiceClient, "create_hyperparameter_tuning_job"
+    ) as create_hyperparameter_tuning_job_mock:
+        create_hyperparameter_tuning_job_mock.return_value = (
             _get_hyperparameter_tuning_job_proto(
                 name=_TEST_HYPERPARAMETERTUNING_JOB_NAME,
                 state=gca_job_state_compat.JobState.JOB_STATE_PENDING,
             )
         )
-        yield create_preview_hyperparameter_tuning_job_mock
+        yield create_hyperparameter_tuning_job_mock
 
 
 @pytest.fixture
 def get_hyperparameter_tuning_job_mock():
     with patch.object(
-        job_service_client_v1beta1.JobServiceClient, "get_hyperparameter_tuning_job"
+        job_service_client_v1.JobServiceClient, "get_hyperparameter_tuning_job"
     ) as get_hyperparameter_tuning_job_mock:
         get_hyperparameter_tuning_job_mock.side_effect = [
             _get_hyperparameter_tuning_job_proto(
@@ -248,7 +248,7 @@ def teardown_method(self):
     @pytest.mark.parametrize("sync", [True, False])
     def test_create_hyperparameter_tuning_job_with_persistent_resource(
         self,
-        create_preview_hyperparameter_tuning_job_mock,
+        create_hyperparameter_tuning_job_mock,
         get_hyperparameter_tuning_job_mock,
         sync,
     ):
@@ -308,7 +308,7 @@ def test_create_hyperparameter_tuning_job_with_persistent_resource(
 
         expected_hyperparameter_tuning_job = _get_hyperparameter_tuning_job_proto()
 
-        create_preview_hyperparameter_tuning_job_mock.assert_called_once_with(
+        create_hyperparameter_tuning_job_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             hyperparameter_tuning_job=expected_hyperparameter_tuning_job,
             timeout=None,