fix: Add deprecation warning to Ray version 2.9.3

PiperOrigin-RevId: 688252265

Author: yinghsienwu

.kokoro/release.sh

@@ -23,13 +23,13 @@ python3 -m releasetool publish-reporter-script > /tmp/publisher-script; source /
 export PYTHONUNBUFFERED=1
 
 # Move into the `google-cloud-aiplatform` package, build the distribution and upload.
-GCA_TWINE_PASSWORD=$(cat "${KOKORO_KEYSTORE_DIR}/73713_google-cloud-pypi-token-keystore-2")
+GCA_TWINE_PASSWORD=$(cat "${KOKORO_KEYSTORE_DIR}/73713_google-cloud-pypi-token-keystore-3")
 cd github/python-aiplatform
 python3 setup.py sdist bdist_wheel
 twine upload --username __token__ --password "${GCA_TWINE_PASSWORD}" dist/*
 
 # Move into the `vertexai` package, build the distribution and upload.
-VERTEXAI_TWINE_PASSWORD=$(cat "${KOKORO_KEYSTORE_DIR}/73713_vertexai-pypi-token-1")
+VERTEXAI_TWINE_PASSWORD=$(cat "${KOKORO_KEYSTORE_DIR}/73713_vertexai-pypi-token-2")
 cd pypi/_vertex_ai_placeholder
 python3 -m build
 twine upload --username __token__ --password "${VERTEXAI_TWINE_PASSWORD}" dist/*

.kokoro/release/common.cfg

@@ -28,7 +28,7 @@ before_action {
   fetch_keystore {
     keystore_resource {
       keystore_config_id: 73713
-      keyname: "google-cloud-pypi-token-keystore-2"
+      keyname: "google-cloud-pypi-token-keystore-3"
     }
   }
 }
@@ -38,7 +38,7 @@ before_action {
   fetch_keystore {
     keystore_resource {
       keystore_config_id: 73713
-      keyname: "vertexai-pypi-token-1"
+      keyname: "vertexai-pypi-token-2"
     }
   }
 }

google/cloud/aiplatform/vertex_ray/cluster_init.py

@@ -19,6 +19,7 @@
 import logging
 import time
 from typing import Dict, List, Optional
+import warnings
 
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import utils
@@ -46,6 +47,7 @@
 from google.protobuf import field_mask_pb2  # type: ignore
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 
 
@@ -154,6 +156,8 @@ def create_ray_cluster(
         )
     if ray_version == "2.4":
         raise RuntimeError(_V2_4_WARNING_MESSAGE)
+    if ray_version == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
     local_ray_verion = _validation_utils.get_local_ray_version()
     if ray_version != local_ray_verion:
         if custom_images is None and head_node_type.custom_image is None:

google/cloud/aiplatform/vertex_ray/data.py

@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-
+import warnings
 import ray.data
 from ray.data.dataset import Dataset
 from typing import Any, Dict, Optional
@@ -32,6 +32,7 @@
 
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 
 
@@ -88,6 +89,7 @@ def read_bigquery(
     )
 
     if ray.__version__ == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
         # Concurrency and override_num_blocks are not supported in 2.9.3
         return ray.data.read_datasource(
             datasource=datasource,
@@ -146,6 +148,8 @@ def write_bigquery(
         raise RuntimeError(_V2_4_WARNING_MESSAGE)
 
     elif ray.__version__ == "2.9.3" or ray.__version__ == "2.33.0":
+        if ray.__version__ == "2.9.3":
+            warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
         if ray_remote_args is None:
             ray_remote_args = {}
 

google/cloud/aiplatform/vertex_ray/predict/sklearn/register.py

@@ -19,6 +19,7 @@
 
 import os
 import pickle
+import warnings
 import ray
 import ray.cloudpickle as cpickle
 import tempfile
@@ -34,6 +35,7 @@
 )
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 
 
@@ -94,6 +96,8 @@ def register_sklearn(
             f"Ray version {ray_version} is not supported to upload Sklearn"
             " model to Vertex Model Registry yet. Please use Ray 2.9.3."
         )
+    if ray_version == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
 
     artifact_uri = artifact_uri or initializer.global_config.staging_bucket
     predict_utils.validate_artifact_uri(artifact_uri)

google/cloud/aiplatform/vertex_ray/predict/tensorflow/register.py

@@ -20,7 +20,7 @@
 import logging
 import ray
 from typing import Callable, Optional, Union, TYPE_CHECKING
-
+import warnings
 from google.cloud import aiplatform
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import utils
@@ -30,6 +30,7 @@
 )
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 
 
@@ -99,7 +100,8 @@ def create_model():
     Raises:
         ValueError: Invalid Argument.
     """
-
+    if ray.__version__ == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
     if tensorflow_version is None:
         tensorflow_version = constants._TENSORFLOW_VERSION
     artifact_uri = artifact_uri or initializer.global_config.staging_bucket

google/cloud/aiplatform/vertex_ray/predict/torch/register.py

@@ -16,11 +16,13 @@
 # limitations under the License.
 
 import os
+import warnings
 import ray
 from ray.air._internal.torch_utils import load_torch_model
 import tempfile
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 from google.cloud.aiplatform.utils import gcs_utils
 from typing import Optional
@@ -71,6 +73,8 @@ def get_pytorch_model_from(
             f"Ray on Vertex does not support Ray version {ray_version} to"
             " convert PyTorch model artifacts yet. Please use Ray 2.9.3."
         )
+    if ray_version == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
 
     try:
         return checkpoint.get_model()

google/cloud/aiplatform/vertex_ray/predict/xgboost/register.py

@@ -22,7 +22,7 @@
 import ray
 import tempfile
 from typing import Optional, TYPE_CHECKING
-
+import warnings
 from google.cloud import aiplatform
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import utils
@@ -33,6 +33,7 @@
 )
 from google.cloud.aiplatform.vertex_ray.util._validation_utils import (
     _V2_4_WARNING_MESSAGE,
+    _V2_9_WARNING_MESSAGE,
 )
 
 
@@ -102,7 +103,8 @@ def register_xgboost(
             f"Ray version {ray_version} is not supported to upload XGBoost"
             " model to Vertex Model Registry yet. Please use Ray 2.9.3."
         )
-
+    if ray_version == "2.9.3":
+        warnings.warn(_V2_9_WARNING_MESSAGE, DeprecationWarning, stacklevel=1)
     artifact_uri = artifact_uri or initializer.global_config.staging_bucket
     predict_utils.validate_artifact_uri(artifact_uri)
     display_model_name = (

google/cloud/aiplatform/vertex_ray/util/_validation_utils.py

@@ -29,8 +29,13 @@
 SUPPORTED_PY_VERSION = ["3.10"]
 _V2_4_WARNING_MESSAGE = (
     "After google-cloud-aiplatform>1.53.0, using Ray version = 2.4 will result in an error. "
-    "Please use Ray version = 2.33.0 (default) or 2.9.3 instead."
+    "Please use Ray version = 2.33.0 (default)."
 )
+_V2_9_WARNING_MESSAGE = (
+    "In March 2025, using Ray version = 2.9 will result in an error. "
+    "Please use Ray version = 2.33.0 (default) instead."
+)
+
 
 # Artifact Repository available regions.
 _AVAILABLE_REGIONS = ["us", "europe", "asia"]

testing/constraints-ray-2.9.3.txt

@@ -10,4 +10,4 @@ grpcio-testing==1.34.0
 mlflow==1.30.1 # Pinned to speed up installation
 pytest-xdist==3.3.1 # Pinned to unbreak unit tests
 IPython # Added to test supernova rich html buttons
-
+pandas==2.1.4 # Pandas must be <2.2.0 to be compatible with ray 2.9.3

tests/unit/vertex_ray/test_cluster_init.py

@@ -54,7 +54,7 @@
 
 _TEST_V2_4_WARNING_MESSAGE = (
     "After google-cloud-aiplatform>1.53.0, using Ray version = 2.4 will result"
-    " in an error. Please use Ray version = 2.33.0 (default) or 2.9.3 instead."
+    " in an error. Please use Ray version = 2.33.0 (default)."
 )