Merge branch 'main' into feat--Made-display_name-optional-for-most-calls

.github/CODEOWNERS

@@ -4,8 +4,8 @@
 # For syntax help see:
 # https://help.github.com/en/github/creating-cloning-and-archiving-repositories/about-code-owners#codeowners-syntax
 
-# yoshi-python is the default owner
-*                                      @googleapis/yoshi-python
+# @googleapis/cdpe-cloudai and yoshi-python are the default owners
+*                                      @googleapis/cdpe-cloudai @googleapis/yoshi-python
 
 # The AI Platform GAPIC libraries are owned by Cloud AI DPE
 /google/cloud/aiplatform_*/**          @googleapis/cdpe-cloudai

README.rst

@@ -111,7 +111,7 @@ Initialize the SDK to store common configurations that you use with the SDK.
         staging_bucket='gs://my_staging_bucket',
 
         # custom google.auth.credentials.Credentials
-        # environment default creds used if not set
+        # environment default credentials used if not set
         credentials=my_credentials,
 
         # customer managed encryption key resource name
@@ -188,7 +188,7 @@ Please visit `Using a managed dataset in a custom training application`_ for a d
 
 .. _Using a managed dataset in a custom training application: https://cloud.google.com/vertex-ai/docs/training/using-managed-datasets
 
-It must write the model artifact to the environment variable populated by the traing service:
+It must write the model artifact to the environment variable populated by the training service:
 
 .. code-block:: Python
 

google/cloud/aiplatform/__init__.py

@@ -38,6 +38,10 @@
     Feature,
     Featurestore,
 )
+from google.cloud.aiplatform.matching_engine import (
+    MatchingEngineIndex,
+    MatchingEngineIndexEndpoint,
+)
 from google.cloud.aiplatform.metadata import metadata
 from google.cloud.aiplatform.models import Endpoint
 from google.cloud.aiplatform.models import Model
@@ -104,6 +108,8 @@
     "EntityType",
     "Feature",
     "Featurestore",
+    "MatchingEngineIndex",
+    "MatchingEngineIndexEndpoint",
     "ImageDataset",
     "HyperparameterTuningJob",
     "Model",

google/cloud/aiplatform/base.py

@@ -98,7 +98,7 @@ def log_create_complete(
             cls (VertexAiResourceNoun):
                 Vertex AI Resource Noun class that is being created.
             resource (proto.Message):
-                Vertex AI Resourc proto.Message
+                Vertex AI Resource proto.Message
             variable_name (str): Name of variable to use for code snippet
         """
         self._logger.info(f"{cls.__name__} created. Resource name: {resource.name}")
@@ -121,7 +121,7 @@ def log_create_complete_with_getter(
             cls (VertexAiResourceNoun):
                 Vertex AI Resource Noun class that is being created.
             resource (proto.Message):
-                Vertex AI Resourc proto.Message
+                Vertex AI Resource proto.Message
             variable_name (str): Name of variable to use for code snippet
         """
         self._logger.info(f"{cls.__name__} created. Resource name: {resource.name}")
@@ -462,7 +462,7 @@ def __init__(
         Args:
             project(str): Project of the resource noun.
             location(str): The location of the resource noun.
-            credentials(google.auth.crendentials.Crendentials): Optional custom
+            credentials(google.auth.credentials.Credentials): Optional custom
                 credentials to use when accessing interacting with resource noun.
             resource_name(str): A fully-qualified resource name or ID.
         """
@@ -655,6 +655,15 @@ def gca_resource(self) -> proto.Message:
         self._assert_gca_resource_is_available()
         return self._gca_resource
 
+    @property
+    def _resource_is_available(self) -> bool:
+        """Returns True if GCA resource has been created and is available, otherwise False"""
+        try:
+            self._assert_gca_resource_is_available()
+            return True
+        except RuntimeError:
+            return False
+
     def _assert_gca_resource_is_available(self) -> None:
         """Helper method to raise when property is not accessible.
 
@@ -840,7 +849,7 @@ def __init__(
         Args:
             project (str): Optional. Project of the resource noun.
             location (str): Optional. The location of the resource noun.
-            credentials(google.auth.crendentials.Crendentials):
+            credentials(google.auth.credentials.Credentials):
                 Optional. custom credentials to use when accessing interacting with
                 resource noun.
             resource_name(str): A fully-qualified resource name or ID.
@@ -870,7 +879,7 @@ def _empty_constructor(
         Args:
             project (str): Optional. Project of the resource noun.
             location (str): Optional. The location of the resource noun.
-            credentials(google.auth.crendentials.Crendentials):
+            credentials(google.auth.credentials.Credentials):
                 Optional. custom credentials to use when accessing interacting with
                 resource noun.
             resource_name(str): A fully-qualified resource name or ID.
@@ -1160,7 +1169,7 @@ def delete(self, sync: bool = True) -> None:
         _LOGGER.log_action_completed_against_resource("deleted.", "", self)
 
     def __repr__(self) -> str:
-        if self._gca_resource:
+        if self._gca_resource and self._resource_is_available:
             return VertexAiResourceNoun.__repr__(self)
 
         return FutureManager.__repr__(self)
@@ -1227,3 +1236,58 @@ def get_annotation_class(annotation: type) -> type:
         return annotation.__args__[0]
     else:
         return annotation
+
+
+class DoneMixin(abc.ABC):
+    """An abstract class for implementing a done method, indicating
+    whether a job has completed.
+
+    """
+
+    @abc.abstractmethod
+    def done(self) -> bool:
+        """Method indicating whether a job has completed."""
+        pass
+
+
+class StatefulResource(DoneMixin):
+    """Extends DoneMixin to check whether a job returning a stateful resource has compted."""
+
+    @property
+    @abc.abstractmethod
+    def state(self):
+        """The current state of the job."""
+        pass
+
+    @property
+    @classmethod
+    @abc.abstractmethod
+    def _valid_done_states(cls):
+        """A set() containing all job states associated with a completed job."""
+        pass
+
+    def done(self) -> bool:
+        """Method indicating whether a job has completed.
+
+        Returns:
+            True if the job has completed.
+        """
+        if self.state in self._valid_done_states:
+            return True
+        else:
+            return False
+
+
+class VertexAiStatefulResource(VertexAiResourceNounWithFutureManager, StatefulResource):
+    """Extends StatefulResource to include a check for self._gca_resource."""
+
+    def done(self) -> bool:
+        """Method indicating whether a job has completed.
+
+        Returns:
+            True if the job has completed.
+        """
+        if self._gca_resource and self._gca_resource.name:
+            return super().done()
+        else:
+            return False

google/cloud/aiplatform/compat/__init__.py

@@ -76,6 +76,11 @@
     types.job_state = types.job_state_v1beta1
     types.machine_resources = types.machine_resources_v1beta1
     types.manual_batch_tuning_parameters = types.manual_batch_tuning_parameters_v1beta1
+    types.matching_engine_deployed_index_ref = (
+        types.matching_engine_deployed_index_ref_v1beta1
+    )
+    types.matching_engine_index = types.matching_engine_index_v1beta1
+    types.matching_engine_index_endpoint = types.matching_engine_index_endpoint_v1beta1
     types.metadata_service = types.metadata_service_v1beta1
     types.metadata_store = types.metadata_store_v1beta1
     types.model = types.model_v1beta1
@@ -147,6 +152,11 @@
     types.job_state = types.job_state_v1
     types.machine_resources = types.machine_resources_v1
     types.manual_batch_tuning_parameters = types.manual_batch_tuning_parameters_v1
+    types.matching_engine_deployed_index_ref = (
+        types.matching_engine_deployed_index_ref_v1
+    )
+    types.matching_engine_index = types.matching_engine_index_v1
+    types.matching_engine_index_endpoint = types.matching_engine_index_endpoint_v1
     types.metadata_service = types.metadata_service_v1
     types.metadata_store = types.metadata_store_v1
     types.model = types.model_v1

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

@@ -27,6 +27,12 @@
 from google.cloud.aiplatform_v1beta1.services.featurestore_service import (
     client as featurestore_service_client_v1beta1,
 )
+from google.cloud.aiplatform_v1beta1.services.index_service import (
+    client as index_service_client_v1beta1,
+)
+from google.cloud.aiplatform_v1beta1.services.index_endpoint_service import (
+    client as index_endpoint_service_client_v1beta1,
+)
 from google.cloud.aiplatform_v1beta1.services.job_service import (
     client as job_service_client_v1beta1,
 )
@@ -61,6 +67,12 @@
 from google.cloud.aiplatform_v1.services.featurestore_service import (
     client as featurestore_service_client_v1,
 )
+from google.cloud.aiplatform_v1.services.index_service import (
+    client as index_service_client_v1,
+)
+from google.cloud.aiplatform_v1.services.index_endpoint_service import (
+    client as index_endpoint_service_client_v1,
+)
 from google.cloud.aiplatform_v1.services.job_service import (
     client as job_service_client_v1,
 )
@@ -89,6 +101,8 @@
     endpoint_service_client_v1,
     featurestore_online_serving_service_client_v1,
     featurestore_service_client_v1,
+    index_service_client_v1,
+    index_endpoint_service_client_v1,
     job_service_client_v1,
     metadata_service_client_v1,
     model_service_client_v1,
@@ -101,6 +115,8 @@
     endpoint_service_client_v1beta1,
     featurestore_online_serving_service_client_v1beta1,
     featurestore_service_client_v1beta1,
+    index_service_client_v1beta1,
+    index_endpoint_service_client_v1beta1,
     job_service_client_v1beta1,
     model_service_client_v1beta1,
     pipeline_service_client_v1beta1,

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

@@ -28,6 +28,7 @@
     data_labeling_job as data_labeling_job_v1beta1,
     dataset as dataset_v1beta1,
     dataset_service as dataset_service_v1beta1,
+    deployed_index_ref as matching_engine_deployed_index_ref_v1beta1,
     deployed_model_ref as deployed_model_ref_v1beta1,
     encryption_spec as encryption_spec_v1beta1,
     endpoint as endpoint_v1beta1,
@@ -45,6 +46,8 @@
     featurestore_monitoring as featurestore_monitoring_v1beta1,
     featurestore_online_service as featurestore_online_service_v1beta1,
     featurestore_service as featurestore_service_v1beta1,
+    index as matching_engine_index_v1beta1,
+    index_endpoint as matching_engine_index_endpoint_v1beta1,
     hyperparameter_tuning_job as hyperparameter_tuning_job_v1beta1,
     io as io_v1beta1,
     job_service as job_service_v1beta1,
@@ -86,6 +89,7 @@
     data_labeling_job as data_labeling_job_v1,
     dataset as dataset_v1,
     dataset_service as dataset_service_v1,
+    deployed_index_ref as matching_engine_deployed_index_ref_v1,
     deployed_model_ref as deployed_model_ref_v1,
     encryption_spec as encryption_spec_v1,
     endpoint as endpoint_v1,
@@ -103,6 +107,8 @@
     featurestore_online_service as featurestore_online_service_v1,
     featurestore_service as featurestore_service_v1,
     hyperparameter_tuning_job as hyperparameter_tuning_job_v1,
+    index as matching_engine_index_v1,
+    index_endpoint as matching_engine_index_endpoint_v1,
     io as io_v1,
     job_service as job_service_v1,
     job_state as job_state_v1,
@@ -167,6 +173,9 @@
     job_state_v1,
     machine_resources_v1,
     manual_batch_tuning_parameters_v1,
+    matching_engine_deployed_index_ref_v1,
+    matching_engine_index_v1,
+    matching_engine_index_endpoint_v1,
     metadata_service_v1,
     metadata_store_v1,
     model_v1,
@@ -223,6 +232,9 @@
     job_state_v1beta1,
     machine_resources_v1beta1,
     manual_batch_tuning_parameters_v1beta1,
+    matching_engine_deployed_index_ref_v1beta1,
+    matching_engine_index_v1beta1,
+    matching_engine_index_endpoint_v1beta1,
     metadata_service_v1beta1,
     metadata_store_v1beta1,
     model_v1beta1,

google/cloud/aiplatform/constants/base.py

@@ -36,6 +36,8 @@
     "us-east4",
     "us-west1",
     "us-west2",
+    "us-west4",
+    "southamerica-east1",
 }
 
 API_BASE_PATH = "aiplatform.googleapis.com"

google/cloud/aiplatform/datasets/dataset.py

@@ -164,7 +164,7 @@ def create(
                 be picked randomly. Two DataItems are considered identical
                 if their content bytes are identical (e.g. image bytes or
                 pdf bytes). These labels will be overridden by Annotation
-                labels specified inside index file refenced by
+                labels specified inside index file referenced by
                 ``import_schema_uri``,
                 e.g. jsonl file.
             project (str):
@@ -489,7 +489,7 @@ def import_data(
                 be picked randomly. Two DataItems are considered identical
                 if their content bytes are identical (e.g. image bytes or
                 pdf bytes). These labels will be overridden by Annotation
-                labels specified inside index file refenced by
+                labels specified inside index file referenced by
                 ``import_schema_uri``,
                 e.g. jsonl file.
             sync (bool):

google/cloud/aiplatform/datasets/image_dataset.py

@@ -82,7 +82,7 @@ def create(
                 be picked randomly. Two DataItems are considered identical
                 if their content bytes are identical (e.g. image bytes or
                 pdf bytes). These labels will be overridden by Annotation
-                labels specified inside index file refenced by
+                labels specified inside index file referenced by
                 ``import_schema_uri``,
                 e.g. jsonl file.
             project (str):

google/cloud/aiplatform/datasets/text_dataset.py

@@ -89,7 +89,7 @@ def create(
                 be picked randomly. Two DataItems are considered identical
                 if their content bytes are identical (e.g. image bytes or
                 pdf bytes). These labels will be overridden by Annotation
-                labels specified inside index file refenced by
+                labels specified inside index file referenced by
                 ``import_schema_uri``,
                 e.g. jsonl file.
             project (str):

google/cloud/aiplatform/datasets/video_dataset.py

@@ -82,7 +82,7 @@ def create(
                 be picked randomly. Two DataItems are considered identical
                 if their content bytes are identical (e.g. image bytes or
                 pdf bytes). These labels will be overridden by Annotation
-                labels specified inside index file refenced by
+                labels specified inside index file referenced by
                 ``import_schema_uri``,
                 e.g. jsonl file.
             project (str):

google/cloud/aiplatform/explain/lit.py

@@ -29,23 +29,23 @@
 except ImportError:
     raise ImportError(
         "LIT is not installed and is required to get Dataset as the return format. "
-        'Please install the SDK using "pip install python-aiplatform[lit]"'
+        'Please install the SDK using "pip install google-cloud-aiplatform[lit]"'
     )
 
 try:
     import tensorflow as tf
 except ImportError:
     raise ImportError(
         "Tensorflow is not installed and is required to load saved model. "
-        'Please install the SDK using "pip install pip install python-aiplatform[lit]"'
+        'Please install the SDK using "pip install google-cloud-aiplatform[lit]"'
     )
 
 try:
     import pandas as pd
 except ImportError:
     raise ImportError(
         "Pandas is not installed and is required to read the dataset. "
-        'Please install Pandas using "pip install python-aiplatform[lit]"'
+        'Please install Pandas using "pip install google-cloud-aiplatform[lit]"'
     )