feat: Upgrade Tensorboard from v1beta1 to v1

google/cloud/aiplatform/compat/__init__.py

@@ -77,13 +77,14 @@
     types.specialist_pool = types.specialist_pool_v1beta1
     types.specialist_pool_service = types.specialist_pool_service_v1beta1
     types.study = types.study_v1beta1
-    types.training_pipeline = types.training_pipeline_v1beta1
+    types.tensorboard = types.tensorboard_v1beta1
     types.tensorboard_service = types.tensorboard_service_v1beta1
     types.tensorboard_data = types.tensorboard_data_v1beta1
     types.tensorboard_experiment = types.tensorboard_experiment_v1beta1
     types.tensorboard_run = types.tensorboard_run_v1beta1
     types.tensorboard_service = types.tensorboard_service_v1beta1
     types.tensorboard_time_series = types.tensorboard_time_series_v1beta1
+    types.training_pipeline = types.training_pipeline_v1beta1
 
 if DEFAULT_VERSION == V1:
 
@@ -135,6 +136,13 @@
     types.specialist_pool = types.specialist_pool_v1
     types.specialist_pool_service = types.specialist_pool_service_v1
     types.study = types.study_v1
+    types.tensorboard = types.tensorboard_v1
+    types.tensorboard_service = types.tensorboard_service_v1
+    types.tensorboard_data = types.tensorboard_data_v1
+    types.tensorboard_experiment = types.tensorboard_experiment_v1
+    types.tensorboard_run = types.tensorboard_run_v1
+    types.tensorboard_service = types.tensorboard_service_v1
+    types.tensorboard_time_series = types.tensorboard_time_series_v1
     types.training_pipeline = types.training_pipeline_v1
 
 __all__ = (

google/cloud/aiplatform/compat/services/__init__.py

@@ -67,6 +67,9 @@
 from google.cloud.aiplatform_v1.services.specialist_pool_service import (
     client as specialist_pool_service_client_v1,
 )
+from google.cloud.aiplatform_v1.services.tensorboard_service import (
+    client as tensorboard_service_client_v1,
+)
 
 __all__ = (
     # v1
@@ -78,6 +81,7 @@
     pipeline_service_client_v1,
     prediction_service_client_v1,
     specialist_pool_service_client_v1,
+    tensorboard_service_client_v1,
     # v1beta1
     dataset_service_client_v1beta1,
     endpoint_service_client_v1beta1,

google/cloud/aiplatform/compat/types/__init__.py

@@ -57,13 +57,13 @@
     specialist_pool as specialist_pool_v1beta1,
     specialist_pool_service as specialist_pool_service_v1beta1,
     study as study_v1beta1,
-    training_pipeline as training_pipeline_v1beta1,
     tensorboard as tensorboard_v1beta1,
     tensorboard_data as tensorboard_data_v1beta1,
     tensorboard_experiment as tensorboard_experiment_v1beta1,
     tensorboard_run as tensorboard_run_v1beta1,
     tensorboard_service as tensorboard_service_v1beta1,
     tensorboard_time_series as tensorboard_time_series_v1beta1,
+    training_pipeline as training_pipeline_v1beta1,
 )
 from google.cloud.aiplatform_v1.types import (
     accelerator_type as accelerator_type_v1,
@@ -107,6 +107,12 @@
     specialist_pool as specialist_pool_v1,
     specialist_pool_service as specialist_pool_service_v1,
     study as study_v1,
+    tensorboard as tensorboard_v1,
+    tensorboard_data as tensorboard_data_v1,
+    tensorboard_experiment as tensorboard_experiment_v1,
+    tensorboard_run as tensorboard_run_v1,
+    tensorboard_service as tensorboard_service_v1,
+    tensorboard_time_series as tensorboard_time_series_v1,
     training_pipeline as training_pipeline_v1,
 )
 
@@ -152,6 +158,13 @@
     prediction_service_v1,
     specialist_pool_v1,
     specialist_pool_service_v1,
+    tensorboard_v1,
+    tensorboard_service_v1,
+    tensorboard_data_v1,
+    tensorboard_experiment_v1,
+    tensorboard_run_v1,
+    tensorboard_service_v1,
+    tensorboard_time_series_v1,
     training_pipeline_v1,
     # v1beta1
     accelerator_type_v1beta1,
@@ -194,13 +207,12 @@
     prediction_service_v1beta1,
     specialist_pool_v1beta1,
     specialist_pool_service_v1beta1,
-    training_pipeline_v1beta1,
-    metadata_service_v1beta1,
     tensorboard_v1beta1,
     tensorboard_service_v1beta1,
     tensorboard_data_v1beta1,
     tensorboard_experiment_v1beta1,
     tensorboard_run_v1beta1,
     tensorboard_service_v1beta1,
     tensorboard_time_series_v1beta1,
+    training_pipeline_v1beta1,
 )

google/cloud/aiplatform/jobs.py

@@ -35,12 +35,10 @@
     batch_prediction_job as gca_bp_job_compat,
     completion_stats as gca_completion_stats,
     custom_job as gca_custom_job_compat,
-    custom_job_v1beta1 as gca_custom_job_v1beta1,
     explanation as gca_explanation_compat,
     io as gca_io_compat,
     job_state as gca_job_state,
     hyperparameter_tuning_job as gca_hyperparameter_tuning_job_compat,
-    hyperparameter_tuning_job_v1beta1 as gca_hyperparameter_tuning_job_v1beta1,
     machine_resources as gca_machine_resources_compat,
     study as gca_study_compat,
 )
@@ -1388,17 +1386,11 @@ def run(
             self._gca_resource.job_spec.enable_web_access = enable_web_access
 
         if tensorboard:
-            v1beta1_gca_resource = gca_custom_job_v1beta1.CustomJob()
-            v1beta1_gca_resource._pb.MergeFromString(
-                self._gca_resource._pb.SerializeToString()
-            )
-            self._gca_resource = v1beta1_gca_resource
             self._gca_resource.job_spec.tensorboard = tensorboard
 
         _LOGGER.log_create_with_lro(self.__class__)
 
-        version = "v1beta1" if tensorboard else "v1"
-        self._gca_resource = self.api_client.select_version(version).create_custom_job(
+        self._gca_resource = self.api_client.create_custom_job(
             parent=self._parent, custom_job=self._gca_resource
         )
 
@@ -1773,21 +1765,11 @@ def run(
             self._gca_resource.trial_job_spec.enable_web_access = enable_web_access
 
         if tensorboard:
-            v1beta1_gca_resource = (
-                gca_hyperparameter_tuning_job_v1beta1.HyperparameterTuningJob()
-            )
-            v1beta1_gca_resource._pb.MergeFromString(
-                self._gca_resource._pb.SerializeToString()
-            )
-            self._gca_resource = v1beta1_gca_resource
             self._gca_resource.trial_job_spec.tensorboard = tensorboard
 
         _LOGGER.log_create_with_lro(self.__class__)
 
-        version = "v1beta1" if tensorboard else "v1"
-        self._gca_resource = self.api_client.select_version(
-            version
-        ).create_hyperparameter_tuning_job(
+        self._gca_resource = self.api_client.create_hyperparameter_tuning_job(
             parent=self._parent, hyperparameter_tuning_job=self._gca_resource
         )
 

google/cloud/aiplatform/tensorboard/tensorboard.py

@@ -18,17 +18,13 @@
 from typing import Optional, Sequence, Dict, Tuple
 
 from google.auth import credentials as auth_credentials
+from google.protobuf import field_mask_pb2
 
 from google.cloud.aiplatform import base
-from google.cloud.aiplatform import compat
+from google.cloud.aiplatform.compat.types import tensorboard as gca_tensorboard
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import utils
 
-
-from google.cloud.aiplatform.compat.types import tensorboard_v1beta1 as gca_tensorboard
-
-from google.protobuf import field_mask_pb2
-
 _LOGGER = base.Logger(__name__)
 
 
@@ -156,8 +152,7 @@ def create(
         )
 
         encryption_spec = initializer.global_config.get_encryption_spec(
-            encryption_spec_key_name=encryption_spec_key_name,
-            select_version=compat.V1BETA1,
+            encryption_spec_key_name=encryption_spec_key_name
         )
 
         gapic_tensorboard = gca_tensorboard.Tensorboard(
@@ -254,7 +249,6 @@ def update(
         if encryption_spec_key_name:
             encryption_spec = initializer.global_config.get_encryption_spec(
                 encryption_spec_key_name=encryption_spec_key_name,
-                select_version=compat.V1BETA1,
             )
             update_mask.append("encryption_spec")
 

google/cloud/aiplatform/utils/__init__.py

@@ -51,6 +51,7 @@
     model_service_client_v1,
     pipeline_service_client_v1,
     prediction_service_client_v1,
+    tensorboard_service_client_v1,
 )
 
 from google.cloud.aiplatform.compat.types import (
@@ -67,6 +68,7 @@
     pipeline_service_client_v1beta1.PipelineServiceClient,
     job_service_client_v1beta1.JobServiceClient,
     metadata_service_client_v1beta1.MetadataServiceClient,
+    tensorboard_service_client_v1beta1.TensorboardServiceClient,
     # v1
     dataset_service_client_v1.DatasetServiceClient,
     endpoint_service_client_v1.EndpointServiceClient,
@@ -75,6 +77,7 @@
     prediction_service_client_v1.PredictionServiceClient,
     pipeline_service_client_v1.PipelineServiceClient,
     job_service_client_v1.JobServiceClient,
+    tensorboard_service_client_v1.TensorboardServiceClient,
 )
 
 RESOURCE_NAME_PATTERN = re.compile(
@@ -506,8 +509,9 @@ class MetadataClientWithOverride(ClientWithOverride):
 
 class TensorboardClientWithOverride(ClientWithOverride):
     _is_temporary = False
-    _default_version = compat.V1BETA1
+    _default_version = compat.DEFAULT_VERSION
     _version_map = (
+        (compat.V1, tensorboard_service_client_v1.TensorboardServiceClient),
         (compat.V1BETA1, tensorboard_service_client_v1beta1.TensorboardServiceClient),
     )
 

tests/system/aiplatform/test_tensorboard.py

@@ -0,0 +1,44 @@
+# -*- coding: utf-8 -*-
+
+# 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
+#
+#     http://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 tests.system.aiplatform import e2e_base
+
+
+class TestTensorboard(e2e_base.TestEndToEnd):
+
+    _temp_prefix = "temp-vertex-sdk-e2e-test"
+
+    def test_create_and_get_tensorboard(self, shared_state):
+
+        aiplatform.init(
+            project=e2e_base._PROJECT, location=e2e_base._LOCATION,
+        )
+
+        display_name = self._make_display_name("tensorboard")
+
+        tb = aiplatform.Tensorboard.create(display_name=display_name)
+
+        shared_state["resources"] = [tb]
+
+        get_tb = aiplatform.Tensorboard(tb.resource_name)
+
+        assert tb.resource_name == get_tb.resource_name
+
+        list_tb = aiplatform.Tensorboard.list()
+
+        assert len(list_tb) > 0

tests/unit/aiplatform/test_custom_job.py

@@ -31,18 +31,12 @@
 from google.cloud import aiplatform
 from google.cloud.aiplatform import base
 from google.cloud.aiplatform.compat.types import custom_job as gca_custom_job_compat
-from google.cloud.aiplatform.compat.types import (
-    custom_job_v1beta1 as gca_custom_job_v1beta1,
-)
 from google.cloud.aiplatform.compat.types import io as gca_io_compat
 from google.cloud.aiplatform.compat.types import job_state as gca_job_state_compat
 from google.cloud.aiplatform.compat.types import (
     encryption_spec as gca_encryption_spec_compat,
 )
 from google.cloud.aiplatform_v1.services.job_service import client as job_service_client
-from google.cloud.aiplatform_v1beta1.services.job_service import (
-    client as job_service_client_v1beta1,
-)
 
 _TEST_PROJECT = "test-project"
 _TEST_LOCATION = "us-central1"
@@ -114,29 +108,16 @@
 )
 
 
-def _get_custom_job_proto(state=None, name=None, error=None, version="v1"):
+def _get_custom_job_proto(state=None, name=None, error=None):
     custom_job_proto = copy.deepcopy(_TEST_BASE_CUSTOM_JOB_PROTO)
     custom_job_proto.name = name
     custom_job_proto.state = state
     custom_job_proto.error = error
-
-    if version == "v1beta1":
-        v1beta1_custom_job_proto = gca_custom_job_v1beta1.CustomJob()
-        v1beta1_custom_job_proto._pb.MergeFromString(
-            custom_job_proto._pb.SerializeToString()
-        )
-        custom_job_proto = v1beta1_custom_job_proto
-        custom_job_proto.job_spec.tensorboard = _TEST_TENSORBOARD_NAME
-
     return custom_job_proto
 
 
-def _get_custom_job_proto_with_enable_web_access(
-    state=None, name=None, error=None, version="v1"
-):
-    custom_job_proto = _get_custom_job_proto(
-        state=state, name=name, error=error, version=version
-    )
+def _get_custom_job_proto_with_enable_web_access(state=None, name=None, error=None):
+    custom_job_proto = _get_custom_job_proto(state=state, name=name, error=error)
     custom_job_proto.job_spec.enable_web_access = _TEST_ENABLE_WEB_ACCESS
     if state == gca_job_state_compat.JobState.JOB_STATE_RUNNING:
         custom_job_proto.web_access_uris = _TEST_WEB_ACCESS_URIS
@@ -260,24 +241,25 @@ def create_custom_job_mock_with_enable_web_access():
 
 
 @pytest.fixture
-def create_custom_job_mock_fail():
+def create_custom_job_mock_with_tensorboard():
     with mock.patch.object(
         job_service_client.JobServiceClient, "create_custom_job"
     ) as create_custom_job_mock:
-        create_custom_job_mock.side_effect = RuntimeError("Mock fail")
+        custom_job_proto = _get_custom_job_proto(
+            name=_TEST_CUSTOM_JOB_NAME,
+            state=gca_job_state_compat.JobState.JOB_STATE_PENDING,
+        )
+        custom_job_proto.job_spec.tensorboard = _TEST_TENSORBOARD_NAME
+        create_custom_job_mock.return_value = custom_job_proto
         yield create_custom_job_mock
 
 
 @pytest.fixture
-def create_custom_job_v1beta1_mock():
+def create_custom_job_mock_fail():
     with mock.patch.object(
-        job_service_client_v1beta1.JobServiceClient, "create_custom_job"
+        job_service_client.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,
-            version="v1beta1",
-        )
+        create_custom_job_mock.side_effect = RuntimeError("Mock fail")
         yield create_custom_job_mock
 
 
@@ -573,7 +555,7 @@ def test_get_web_access_uris_job_succeeded(
 
     @pytest.mark.parametrize("sync", [True, False])
     def test_create_custom_job_with_tensorboard(
-        self, create_custom_job_v1beta1_mock, get_custom_job_mock, sync
+        self, create_custom_job_mock_with_tensorboard, get_custom_job_mock, sync
     ):
 
         aiplatform.init(
@@ -601,9 +583,10 @@ def test_create_custom_job_with_tensorboard(
 
         job.wait()
 
-        expected_custom_job = _get_custom_job_proto(version="v1beta1")
+        expected_custom_job = _get_custom_job_proto()
+        expected_custom_job.job_spec.tensorboard = _TEST_TENSORBOARD_NAME
 
-        create_custom_job_v1beta1_mock.assert_called_once_with(
+        create_custom_job_mock_with_tensorboard.assert_called_once_with(
             parent=_TEST_PARENT, custom_job=expected_custom_job
         )