chore: run the post processor

docs/aiplatform_v1beta1/services.rst

@@ -5,16 +5,9 @@ Services for Google Cloud Aiplatform v1beta1 API
 
     dataset_service
     endpoint_service
-    featurestore_online_serving_service
-    featurestore_service
-    index_endpoint_service
-    index_service
     job_service
-    metadata_service
     migration_service
     model_service
     pipeline_service
     prediction_service
     specialist_pool_service
-    tensorboard_service
-    vizier_service

google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/__init__.py

@@ -30,6 +30,7 @@
     AutoMlImageSegmentationInputs,
     AutoMlImageSegmentationMetadata,
 )
+from .export_evaluated_data_items_config import ExportEvaluatedDataItemsConfig
 from .automl_tables import (
     AutoMlTables,
     AutoMlTablesInputs,
@@ -59,7 +60,6 @@
     AutoMlVideoObjectTracking,
     AutoMlVideoObjectTrackingInputs,
 )
-from .export_evaluated_data_items_config import ExportEvaluatedDataItemsConfig
 
 __all__ = (
     "AutoMlImageClassification",
@@ -71,6 +71,7 @@
     "AutoMlImageSegmentation",
     "AutoMlImageSegmentationInputs",
     "AutoMlImageSegmentationMetadata",
+    "ExportEvaluatedDataItemsConfig",
     "AutoMlTables",
     "AutoMlTablesInputs",
     "AutoMlTablesMetadata",
@@ -86,5 +87,4 @@
     "AutoMlVideoClassificationInputs",
     "AutoMlVideoObjectTracking",
     "AutoMlVideoObjectTrackingInputs",
-    "ExportEvaluatedDataItemsConfig",
 )

google/cloud/aiplatform/v1beta1/schema/predict/instance_v1beta1/types/video_action_recognition.py

@@ -48,8 +48,8 @@ class VideoActionRecognitionPredictionInstance(proto.Message):
             Expressed as a number of seconds as measured
             from the start of the video, with "s" appended
             at the end. Fractions are allowed, up to a
-            microsecond precision, and "inf" or "Infinity"
-            is allowed, which means the end of the video.
+            microsecond precision, and "Infinity" is
+            allowed, which means the end of the video.
     """
 
     content = proto.Field(proto.STRING, number=1)

google/cloud/aiplatform/v1beta1/schema/predict/instance_v1beta1/types/video_classification.py

@@ -48,8 +48,8 @@ class VideoClassificationPredictionInstance(proto.Message):
             Expressed as a number of seconds as measured
             from the start of the video, with "s" appended
             at the end. Fractions are allowed, up to a
-            microsecond precision, and "inf" or "Infinity"
-            is allowed, which means the end of the video.
+            microsecond precision, and "Infinity" is
+            allowed, which means the end of the video.
     """
 
     content = proto.Field(proto.STRING, number=1)

google/cloud/aiplatform/v1beta1/schema/predict/instance_v1beta1/types/video_object_tracking.py

@@ -48,8 +48,8 @@ class VideoObjectTrackingPredictionInstance(proto.Message):
             Expressed as a number of seconds as measured
             from the start of the video, with "s" appended
             at the end. Fractions are allowed, up to a
-            microsecond precision, and "inf" or "Infinity"
-            is allowed, which means the end of the video.
+            microsecond precision, and "Infinity" is
+            allowed, which means the end of the video.
     """
 
     content = proto.Field(proto.STRING, number=1)

google/cloud/aiplatform/v1beta1/schema/predict/prediction/__init__.py

@@ -36,6 +36,9 @@
 from google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types.text_sentiment import (
     TextSentimentPredictionResult,
 )
+from google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types.time_series_forecasting import (
+    TimeSeriesForecastingPredictionResult,
+)
 from google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types.video_action_recognition import (
     VideoActionRecognitionPredictionResult,
 )
@@ -54,6 +57,7 @@
     "TabularRegressionPredictionResult",
     "TextExtractionPredictionResult",
     "TextSentimentPredictionResult",
+    "TimeSeriesForecastingPredictionResult",
     "VideoActionRecognitionPredictionResult",
     "VideoClassificationPredictionResult",
     "VideoObjectTrackingPredictionResult",

google/cloud/aiplatform/v1beta1/schema/predict/prediction_v1beta1/__init__.py

@@ -22,6 +22,7 @@
 from .types.tabular_regression import TabularRegressionPredictionResult
 from .types.text_extraction import TextExtractionPredictionResult
 from .types.text_sentiment import TextSentimentPredictionResult
+from .types.time_series_forecasting import TimeSeriesForecastingPredictionResult
 from .types.video_action_recognition import VideoActionRecognitionPredictionResult
 from .types.video_classification import VideoClassificationPredictionResult
 from .types.video_object_tracking import VideoObjectTrackingPredictionResult
@@ -34,6 +35,7 @@
     "TabularRegressionPredictionResult",
     "TextExtractionPredictionResult",
     "TextSentimentPredictionResult",
+    "TimeSeriesForecastingPredictionResult",
     "VideoActionRecognitionPredictionResult",
     "VideoClassificationPredictionResult",
     "VideoObjectTrackingPredictionResult",

google/cloud/aiplatform/v1beta1/schema/predict/prediction_v1beta1/types/__init__.py

@@ -22,6 +22,7 @@
 from .tabular_regression import TabularRegressionPredictionResult
 from .text_extraction import TextExtractionPredictionResult
 from .text_sentiment import TextSentimentPredictionResult
+from .time_series_forecasting import TimeSeriesForecastingPredictionResult
 from .video_action_recognition import VideoActionRecognitionPredictionResult
 from .video_classification import VideoClassificationPredictionResult
 from .video_object_tracking import VideoObjectTrackingPredictionResult
@@ -34,6 +35,7 @@
     "TabularRegressionPredictionResult",
     "TextExtractionPredictionResult",
     "TextSentimentPredictionResult",
+    "TimeSeriesForecastingPredictionResult",
     "VideoActionRecognitionPredictionResult",
     "VideoClassificationPredictionResult",
     "VideoObjectTrackingPredictionResult",

google/cloud/aiplatform/v1beta1/schema/predict/prediction_v1beta1/types/image_segmentation.py

@@ -28,7 +28,7 @@ class ImageSegmentationPredictionResult(proto.Message):
     r"""Prediction output format for Image Segmentation.
 
     Attributes:
-        category_mask (str):
+        category_mask (bytes):
             A PNG image where each pixel in the mask
             represents the category in which the pixel in
             the original image was predicted to belong to.
@@ -39,7 +39,7 @@ class ImageSegmentationPredictionResult(proto.Message):
             likely category and if none of the categories
             reach the confidence threshold, the pixel will
             be marked as background.
-        confidence_mask (str):
+        confidence_mask (bytes):
             A one channel image which is encoded as an
             8bit lossless PNG. The size of the image will be
             the same as the original image. For a specific
@@ -49,9 +49,9 @@ class ImageSegmentationPredictionResult(proto.Message):
             confidence and white means complete confidence.
     """
 
-    category_mask = proto.Field(proto.STRING, number=1)
+    category_mask = proto.Field(proto.BYTES, number=1)
 
-    confidence_mask = proto.Field(proto.STRING, number=2)
+    confidence_mask = proto.Field(proto.BYTES, number=2)
 
 
 __all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/aiplatform/v1beta1/schema/predict/prediction_v1beta1/types/text_sentiment.py

@@ -18,28 +18,51 @@
 import proto  # type: ignore
 
 
+from google.cloud.aiplatform.v1beta1.schema.predict.instance import text_sentiment_pb2 as gcaspi_text_sentiment  # type: ignore
+
+
 __protobuf__ = proto.module(
     package="google.cloud.aiplatform.v1beta1.schema.predict.prediction",
     manifest={"TextSentimentPredictionResult",},
 )
 
 
 class TextSentimentPredictionResult(proto.Message):
-    r"""Prediction output format for Text Sentiment
+    r"""Represents a line of JSONL in the text sentiment batch
+    prediction output file. This is a hack to allow printing of
+    integer values.
 
     Attributes:
-        sentiment (int):
-            The integer sentiment labels between 0
-            (inclusive) and sentimentMax label (inclusive),
-            while 0 maps to the least positive sentiment and
-            sentimentMax maps to the most positive one. The
-            higher the score is, the more positive the
-            sentiment in the text snippet is. Note:
-            sentimentMax is an integer value between 1
-            (inclusive) and 10 (inclusive).
+        instance (google.cloud.aiplatform.v1beta1.schema.predict.instance.text_sentiment_pb2.TextSentimentPredictionInstance):
+            User's input instance.
+        prediction (google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types.TextSentimentPredictionResult.Prediction):
+            The prediction result.
     """
 
-    sentiment = proto.Field(proto.INT32, number=1)
+    class Prediction(proto.Message):
+        r"""Prediction output format for Text Sentiment.
+
+        Attributes:
+            sentiment (int):
+                The integer sentiment labels between 0
+                (inclusive) and sentimentMax label (inclusive),
+                while 0 maps to the least positive sentiment and
+                sentimentMax maps to the most positive one. The
+                higher the score is, the more positive the
+                sentiment in the text snippet is. Note:
+                sentimentMax is an integer value between 1
+                (inclusive) and 10 (inclusive).
+        """
+
+        sentiment = proto.Field(proto.INT32, number=1)
+
+    instance = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=gcaspi_text_sentiment.TextSentimentPredictionInstance,
+    )
+
+    prediction = proto.Field(proto.MESSAGE, number=2, message=Prediction,)
 
 
 __all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition/__init__.py

@@ -15,6 +15,15 @@
 # limitations under the License.
 #
 
+from google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.automl_forecasting import (
+    AutoMlForecasting,
+)
+from google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.automl_forecasting import (
+    AutoMlForecastingInputs,
+)
+from google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.automl_forecasting import (
+    AutoMlForecastingMetadata,
+)
 from google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.automl_image_classification import (
     AutoMlImageClassification,
 )
@@ -92,6 +101,9 @@
 )
 
 __all__ = (
+    "AutoMlForecasting",
+    "AutoMlForecastingInputs",
+    "AutoMlForecastingMetadata",
     "AutoMlImageClassification",
     "AutoMlImageClassificationInputs",
     "AutoMlImageClassificationMetadata",

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/__init__.py

@@ -15,6 +15,9 @@
 # limitations under the License.
 #
 
+from .types.automl_forecasting import AutoMlForecasting
+from .types.automl_forecasting import AutoMlForecastingInputs
+from .types.automl_forecasting import AutoMlForecastingMetadata
 from .types.automl_image_classification import AutoMlImageClassification
 from .types.automl_image_classification import AutoMlImageClassificationInputs
 from .types.automl_image_classification import AutoMlImageClassificationMetadata
@@ -43,6 +46,10 @@
 
 
 __all__ = (
+    "AutoMlForecasting",
+    "AutoMlForecastingInputs",
+    "AutoMlForecastingMetadata",
+    "AutoMlImageClassification",
     "AutoMlImageClassificationInputs",
     "AutoMlImageClassificationMetadata",
     "AutoMlImageObjectDetection",
@@ -67,5 +74,4 @@
     "AutoMlVideoObjectTracking",
     "AutoMlVideoObjectTrackingInputs",
     "ExportEvaluatedDataItemsConfig",
-    "AutoMlImageClassification",
 )

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/__init__.py

@@ -15,6 +15,12 @@
 # limitations under the License.
 #
 
+from .export_evaluated_data_items_config import ExportEvaluatedDataItemsConfig
+from .automl_forecasting import (
+    AutoMlForecasting,
+    AutoMlForecastingInputs,
+    AutoMlForecastingMetadata,
+)
 from .automl_image_classification import (
     AutoMlImageClassification,
     AutoMlImageClassificationInputs,
@@ -59,9 +65,12 @@
     AutoMlVideoObjectTracking,
     AutoMlVideoObjectTrackingInputs,
 )
-from .export_evaluated_data_items_config import ExportEvaluatedDataItemsConfig
 
 __all__ = (
+    "ExportEvaluatedDataItemsConfig",
+    "AutoMlForecasting",
+    "AutoMlForecastingInputs",
+    "AutoMlForecastingMetadata",
     "AutoMlImageClassification",
     "AutoMlImageClassificationInputs",
     "AutoMlImageClassificationMetadata",
@@ -86,5 +95,4 @@
     "AutoMlVideoClassificationInputs",
     "AutoMlVideoObjectTracking",
     "AutoMlVideoObjectTrackingInputs",
-    "ExportEvaluatedDataItemsConfig",
 )

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_image_segmentation.py

@@ -82,7 +82,6 @@ class ModelType(proto.Enum):
         MODEL_TYPE_UNSPECIFIED = 0
         CLOUD_HIGH_ACCURACY_1 = 1
         CLOUD_LOW_ACCURACY_1 = 2
-        MOBILE_TF_LOW_LATENCY_1 = 3
 
     model_type = proto.Field(proto.ENUM, number=1, enum=ModelType,)
 

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_video_classification.py

@@ -51,7 +51,6 @@ class ModelType(proto.Enum):
         MODEL_TYPE_UNSPECIFIED = 0
         CLOUD = 1
         MOBILE_VERSATILE_1 = 2
-        MOBILE_JETSON_VERSATILE_1 = 3
 
     model_type = proto.Field(proto.ENUM, number=1, enum=ModelType,)
 

google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/export_evaluated_data_items_config.py

@@ -30,19 +30,18 @@ class ExportEvaluatedDataItemsConfig(proto.Message):
 
     Attributes:
         destination_bigquery_uri (str):
-            URI of desired destination BigQuery table. Expected format:
-            bq://<project_id>:<dataset_id>:
-
-            If not specified, then results are exported to the following
-            auto-created BigQuery table:
+            URI of desired destination BigQuery table. If not specified,
+            then results are exported to the following auto-created
+            BigQuery table:
 
             <project_id>:export_evaluated_examples_<model_name>_<yyyy_MM_dd'T'HH_mm_ss_SSS'Z'>.evaluated_examples
         override_existing_table (bool):
             If true and an export destination is
             specified, then the contents of the destination
-            are overwritten. Otherwise, if the export
+            will be overwritten. Otherwise, if the export
             destination already exists, then the export
-            operation fails.
+            operation will not trigger and a failure
+            response is returned.
     """
 
     destination_bigquery_uri = proto.Field(proto.STRING, number=1)