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Summary of entries of Classes for aiplatform.
Classes
Artifact
Metadata Artifact resource for Vertex AI
AutoMLForecastingTrainingJob
Class to train AutoML forecasting models.
The AutoMLForecastingTrainingJob
class uses the AutoML training method
to train and run a forecasting model. The AutoML
training method is a good
choice for most forecasting use cases. If your use case doesn't benefit from
the Seq2seq
or the Temporal fusion transformer
training method offered
by the
SequenceToSequencePlusForecastingTrainingJob
and
[TemporalFusionTransformerForecastingTrainingJob
]https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.TemporalFusionTransformerForecastingTrainingJob)
classes respectively, then AutoML
is likely the best training method for
your forecasting predictions.
For sample code that shows you how to use AutoMLForecastingTrainingJob
see
the Create a training pipeline forecasting sample
on GitHub.
AutoMLImageTrainingJob
Creates an AutoML image training job.
Use the AutoMLImageTrainingJob
class to create, train, and return an
image model. For more information about working with image data models
in Vertex AI, see Image data.
For an example of how to use the AutoMLImageTrainingJob
class, see the
tutorial in the AutoML image
classification
notebook on GitHub.
AutoMLTabularTrainingJob
Constructs a AutoML Tabular Training Job.
Example usage:
job = training_jobs.AutoMLTabularTrainingJob( display_name="my_display_name", optimization_prediction_type="classification", optimization_objective="minimize-log-loss", column_specs={"column_1": "auto", "column_2": "numeric"}, labels={'key': 'value'}, )
AutoMLTextTrainingJob
Constructs a AutoML Text Training Job.
AutoMLVideoTrainingJob
Constructs a AutoML Video Training Job.
BatchPredictionJob
Retrieves a BatchPredictionJob resource and instantiates its representation.
CustomContainerTrainingJob
Class to launch a Custom Training Job in Vertex AI using a Container.
CustomJob
Vertex AI Custom Job.
CustomPythonPackageTrainingJob
Class to launch a Custom Training Job in Vertex AI using a Python Package.
Use the CustomPythonPackageTrainingJob
class to use a Python package to
launch a custom training pipeline in Vertex AI. For an example of how to use
the CustomPythonPackageTrainingJob
class, see the tutorial in the Custom
training using Python package, managed text dataset, and TensorFlow serving
container
notebook.
CustomTrainingJob
Class to launch a Custom Training Job in Vertex AI using a script.
Takes a training implementation as a python script and executes that script in Cloud Vertex AI Training.
Endpoint
Retrieves an endpoint resource.
EntityType
Public managed EntityType resource for Vertex AI.
Execution
Metadata Execution resource for Vertex AI
Experiment
Represents a Vertex AI Experiment resource.
ExperimentRun
A Vertex AI Experiment run.
Feature
Managed feature resource for Vertex AI.
Featurestore
Managed featurestore resource for Vertex AI.
HyperparameterTuningJob
Vertex AI Hyperparameter Tuning Job.
ImageDataset
A managed image dataset resource for Vertex AI.
Use this class to work with a managed image dataset. To create a managed image dataset, you need a datasource file in CSV format and a schema file in YAML format. A schema is optional for a custom model. You put the CSV file and the schema into Cloud Storage buckets.
Use image data for the following objectives:
- Single-label classification. For more information, see Prepare image training data for single-label classification.
- Multi-label classification. For more information, see Prepare image training data for multi-label classification.
- Object detection. For more information, see Prepare image training data for object detection.
The following code shows you how to create an image dataset by importing data from a CSV datasource file and a YAML schema file. The schema file you use depends on whether your image dataset is used for single-label classification, multi-label classification, or object detection.
my_dataset = aiplatform.ImageDataset.create(
display_name="my-image-dataset",
gcs_source=['gs://path/to/my/image-dataset.csv'],
import_schema_uri=['gs://path/to/my/schema.yaml']
)
MatchingEngineIndex
Matching Engine index resource for Vertex AI.
MatchingEngineIndexEndpoint
Matching Engine index endpoint resource for Vertex AI.
Model
Retrieves the model resource and instantiates its representation.
ModelDeploymentMonitoringJob
Vertex AI Model Deployment Monitoring Job.
This class should be used in conjunction with the Endpoint class in order to configure model monitoring for deployed models.
ModelEvaluation
Retrieves the ModelEvaluation resource and instantiates its representation.
PipelineJob
Retrieves a PipelineJob resource and instantiates its representation.
PipelineJobSchedule
Retrieves a PipelineJobSchedule resource and instantiates its representation.
PrivateEndpoint
Represents a Vertex AI PrivateEndpoint resource.
PrivateServiceConnectConfig
Represents a Vertex AI PrivateServiceConnectConfig resource.
SequenceToSequencePlusForecastingTrainingJob
Class to train Sequence to Sequence (Seq2Seq) forecasting models.
The SequenceToSequencePlusForecastingTrainingJob
class uses the Seq2seq+
training method to train and run a forecasting model. The Seq2seq+
training method is a good choice for experimentation. Its algorithm is
simpler and uses a smaller search space than the AutoML
option. Seq2seq+
is a good option if you want fast results and your datasets are smaller than
1 GB.
For sample code that shows you how to use
SequenceToSequencePlusForecastingTrainingJob
, see the Create a training
pipeline forecasting Seq2seq
sample
on GitHub.
TabularDataset
A managed tabular dataset resource for Vertex AI.
Use this class to work with tabular datasets. You can use a CSV file, BigQuery, or a pandas
DataFrame
to create a tabular dataset. For more information about paging through
BigQuery data, see Read data with BigQuery API using
pagination. For more
information about tabular data, see Tabular
data.
The following code shows you how to create and import a tabular dataset with a CSV file.
my_dataset = aiplatform.TabularDataset.create(
display_name="my-dataset", gcs_source=['gs://path/to/my/dataset.csv'])
The following code shows you how to create and import a tabular dataset in two distinct steps.
my_dataset = aiplatform.TextDataset.create(
display_name="my-dataset")
my_dataset.import(
gcs_source=['gs://path/to/my/dataset.csv']
import_schema_uri=aiplatform.schema.dataset.ioformat.text.multi_label_classification
)
If you create a tabular dataset with a pandas
DataFrame
,
you need to use a BigQuery table to stage the data for Vertex AI:
my_dataset = aiplatform.TabularDataset.create_from_dataframe(
df_source=my_pandas_dataframe,
staging_path=f"bq://{bq_dataset_id}.table-unique"
)
TemporalFusionTransformerForecastingTrainingJob
Class to train Temporal Fusion Transformer (TFT) forecasting models.
The TemporalFusionTransformerForecastingTrainingJob
class uses the
Temporal Fusion Transformer (TFT) training method to train and run a
forecasting model. The TFT training method implements an attention-based
deep neural network (DNN) model that uses a multi-horizon forecasting task
to produce predictions.
For sample code that shows you how to use `TemporalFusionTransformerForecastingTrainingJob, see the Create a training pipeline forecasting temporal fusion transformer sample on GitHub.
Tensorboard
Managed tensorboard resource for Vertex AI.
TensorboardExperiment
Managed tensorboard resource for Vertex AI.
TensorboardRun
Managed tensorboard resource for Vertex AI.
TensorboardTimeSeries
Managed tensorboard resource for Vertex AI.
TextDataset
A managed text dataset resource for Vertex AI.
Use this class to work with a managed text dataset. To create a managed text dataset, you need a datasource file in CSV format and a schema file in YAML format. A schema is optional for a custom model. The CSV file and the schema are accessed in Cloud Storage buckets.
Use text data for the following objectives:
- Classification. For more information, see Prepare text training data for classification.
- Entity extraction. For more information, see Prepare text training data for entity extraction.
- Sentiment analysis. For more information, see [Prepare text training data for sentiment analysis](Prepare text training data for sentiment analysis).
The following code shows you how to create and import a text dataset with a CSV datasource file and a YAML schema file. The schema file you use depends on whether your text dataset is used for single-label classification, multi-label classification, or object detection.
my_dataset = aiplatform.TextDataset.create(
display_name="my-text-dataset",
gcs_source=['gs://path/to/my/text-dataset.csv'],
import_schema_uri=['gs://path/to/my/schema.yaml'],
)
TimeSeriesDataset
A managed time series dataset resource for Vertex AI.
Use this class to work with time series datasets. A time series is a dataset that contains data recorded at different time intervals. The dataset includes time and at least one variable that's dependent on time. You use a time series dataset for forecasting predictions. For more information, see Forecasting overview.
You can create a managed time series dataset from CSV files in a Cloud Storage bucket or from a BigQuery table.
The following code shows you how to create a TimeSeriesDataset
with a CSV
file that has the time series dataset:
my_dataset = aiplatform.TimeSeriesDataset.create(
display_name="my-dataset",
gcs_source=['gs://path/to/my/dataset.csv'],
)
The following code shows you how to create with a TimeSeriesDataset
with a
BigQuery table file that has the time series dataset:
my_dataset = aiplatform.TimeSeriesDataset.create(
display_name="my-dataset",
bq_source=['bq://path/to/my/bigquerydataset.train'],
)
TimeSeriesDenseEncoderForecastingTrainingJob
Class to train Time series Dense Encoder (TiDE) forecasting models.
The TimeSeriesDenseEncoderForecastingTrainingJob
class uses the
Time-series Dense Encoder (TiDE) training method to train and run a
forecasting model. TiDE uses a
multi-layer perceptron (MLP) to provide
the speed of forecasting linear models with covariates and non-linear
dependencies. For more information about TiDE, see
Recent advances in deep long-horizon forecasting
and this
TiDE blog post.
VideoDataset
A managed video dataset resource for Vertex AI.
Use this class to work with a managed video dataset. To create a video dataset, you need a datasource in CSV format and a schema in YAML format. The CSV file and the schema are accessed in Cloud Storage buckets.
Use video data for the following objectives:
Classification. For more information, see Classification schema files. Action recognition. For more information, see Action recognition schema files. Object tracking. For more information, see Object tracking schema files. The following code shows you how to create and import a dataset to train a video classification model. The schema file you use depends on whether you use your video dataset for action classification, recognition, or object tracking.
my_dataset = aiplatform.VideoDataset.create(
gcs_source=['gs://path/to/my/dataset.csv'],
import_schema_uri=['gs://aip.schema.dataset.ioformat.video.classification.yaml']
)
ExperimentModel
An artifact representing a Vertex Experiment Model.
DefaultSerializer
Default serializer for serialization and deserialization for prediction.
Handler
Interface for Handler class to handle prediction requests.
LocalEndpoint
Class that represents a local endpoint.
LocalModel
Class that represents a local model.
PredictionHandler
Default prediction handler for the prediction requests sent to the application.
Predictor
Interface of the Predictor class for Custom Prediction Routines.
The Predictor is responsible for the ML logic for processing a prediction request. Specifically, the Predictor must define: (1) How to load all model artifacts used during prediction into memory. (2) The logic that should be executed at predict time.
When using the default PredictionHandler
, the Predictor
will be invoked as
follows:
predictor.postprocess(predictor.predict(predictor.preprocess(prediction_input)))
Serializer
Interface to implement serialization and deserialization for prediction.
ImageClassificationPredictionInstance
Prediction input format for Image Classification.
ImageObjectDetectionPredictionInstance
Prediction input format for Image Object Detection.
ImageSegmentationPredictionInstance
Prediction input format for Image Segmentation.
TextClassificationPredictionInstance
Prediction input format for Text Classification.
TextExtractionPredictionInstance
Prediction input format for Text Extraction.
TextSentimentPredictionInstance
Prediction input format for Text Sentiment.
VideoActionRecognitionPredictionInstance
Prediction input format for Video Action Recognition.
VideoClassificationPredictionInstance
Prediction input format for Video Classification.
VideoObjectTrackingPredictionInstance
Prediction input format for Video Object Tracking.
ImageClassificationPredictionParams
Prediction model parameters for Image Classification.
ImageObjectDetectionPredictionParams
Prediction model parameters for Image Object Detection.
ImageSegmentationPredictionParams
Prediction model parameters for Image Segmentation.
VideoActionRecognitionPredictionParams
Prediction model parameters for Video Action Recognition.
VideoClassificationPredictionParams
Prediction model parameters for Video Classification.
VideoObjectTrackingPredictionParams
Prediction model parameters for Video Object Tracking.
ClassificationPredictionResult
Prediction output format for Image and Text Classification.
ImageObjectDetectionPredictionResult
Prediction output format for Image Object Detection.
ImageSegmentationPredictionResult
Prediction output format for Image Segmentation.
TabularClassificationPredictionResult
Prediction output format for Tabular Classification.
TabularRegressionPredictionResult
Prediction output format for Tabular Regression.
TextExtractionPredictionResult
Prediction output format for Text Extraction.
TextSentimentPredictionResult
Prediction output format for Text Sentiment
VideoActionRecognitionPredictionResult
Prediction output format for Video Action Recognition.
VideoClassificationPredictionResult
Prediction output format for Video Classification.
VideoObjectTrackingPredictionResult
Prediction output format for Video Object Tracking.
Frame
The fields xMin
, xMax
, yMin
, and yMax
refer to a
bounding box, i.e. the rectangle over the video frame pinpointing
the found AnnotationSpec. The coordinates are relative to the frame
size, and the point 0,0 is in the top left of the frame.
AutoMlImageClassification
A TrainingJob that trains and uploads an AutoML Image Classification Model.
AutoMlImageClassificationInputs
ModelType
AutoMlImageClassificationMetadata
SuccessfulStopReason
AutoMlImageObjectDetection
A TrainingJob that trains and uploads an AutoML Image Object Detection Model.
AutoMlImageObjectDetectionInputs
ModelType
AutoMlImageObjectDetectionMetadata
SuccessfulStopReason
AutoMlImageSegmentation
A TrainingJob that trains and uploads an AutoML Image Segmentation Model.
AutoMlImageSegmentationInputs
ModelType
AutoMlImageSegmentationMetadata
SuccessfulStopReason
AutoMlTables
A TrainingJob that trains and uploads an AutoML Tables Model.
AutoMlTablesInputs
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Transformation
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
CategoricalArrayTransformation
Treats the column as categorical array and performs following transformation functions.
- For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Empty arrays treated as an embedding of zeroes.
CategoricalTransformation
Training pipeline will perform following transformation functions.
- The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
- Convert the category name to a dictionary lookup index and generate an embedding for each index.
- Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
NumericArrayTransformation
Treats the column as numerical array and performs following transformation functions.
- All transformations for Numerical types applied to the average of the all elements.
- The average of empty arrays is treated as zero.
NumericTransformation
Training pipeline will perform following transformation functions.
- The value converted to float32.
- The z_score of the value.
- log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- A boolean value that indicates whether the value is valid.
TextArrayTransformation
Treats the column as text array and performs following transformation functions.
- Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns.
- Empty arrays treated as an empty text.
TextTransformation
Training pipeline will perform following transformation functions.
- The text as is--no change to case, punctuation, spelling, tense, and so on.
- Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Tokenization is based on unicode script boundaries.
- Missing values get their own lookup index and resulting embedding.
- Stop-words receive no special treatment and are not removed.
TimestampTransformation
Training pipeline will perform following transformation functions.
- Apply the transformation functions for Numerical columns.
- Determine the year, month, day,and weekday. Treat each value from the
- timestamp as a Categorical column.
- Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
AutoMlTablesMetadata
Model metadata specific to AutoML Tables.
AutoMlTextClassification
A TrainingJob that trains and uploads an AutoML Text Classification Model.
AutoMlTextClassificationInputs
AutoMlTextExtraction
A TrainingJob that trains and uploads an AutoML Text Extraction Model.
AutoMlTextExtractionInputs
API documentation for aiplatform.v1.schema.trainingjob.definition_v1.types.AutoMlTextExtractionInputs
class.
AutoMlTextSentiment
A TrainingJob that trains and uploads an AutoML Text Sentiment Model.
AutoMlTextSentimentInputs
AutoMlVideoActionRecognition
A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.
AutoMlVideoActionRecognitionInputs
ModelType
AutoMlVideoClassification
A TrainingJob that trains and uploads an AutoML Video Classification Model.
AutoMlVideoClassificationInputs
ModelType
AutoMlVideoObjectTracking
A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.
AutoMlVideoObjectTrackingInputs
ModelType
ExportEvaluatedDataItemsConfig
Configuration for exporting test set predictions to a BigQuery table.
ImageClassificationPredictionInstance
Prediction input format for Image Classification.
ImageObjectDetectionPredictionInstance
Prediction input format for Image Object Detection.
ImageSegmentationPredictionInstance
Prediction input format for Image Segmentation.
TextClassificationPredictionInstance
Prediction input format for Text Classification.
TextExtractionPredictionInstance
Prediction input format for Text Extraction.
TextSentimentPredictionInstance
Prediction input format for Text Sentiment.
VideoActionRecognitionPredictionInstance
Prediction input format for Video Action Recognition.
VideoClassificationPredictionInstance
Prediction input format for Video Classification.
VideoObjectTrackingPredictionInstance
Prediction input format for Video Object Tracking.
ImageClassificationPredictionParams
Prediction model parameters for Image Classification.
ImageObjectDetectionPredictionParams
Prediction model parameters for Image Object Detection.
ImageSegmentationPredictionParams
Prediction model parameters for Image Segmentation.
VideoActionRecognitionPredictionParams
Prediction model parameters for Video Action Recognition.
VideoClassificationPredictionParams
Prediction model parameters for Video Classification.
VideoObjectTrackingPredictionParams
Prediction model parameters for Video Object Tracking.
ClassificationPredictionResult
Prediction output format for Image and Text Classification.
ImageObjectDetectionPredictionResult
Prediction output format for Image Object Detection.
ImageSegmentationPredictionResult
Prediction output format for Image Segmentation.
TabularClassificationPredictionResult
Prediction output format for Tabular Classification.
TabularRegressionPredictionResult
Prediction output format for Tabular Regression.
TextExtractionPredictionResult
Prediction output format for Text Extraction.
TextSentimentPredictionResult
Prediction output format for Text Sentiment
TimeSeriesForecastingPredictionResult
Prediction output format for Time Series Forecasting.
VideoActionRecognitionPredictionResult
Prediction output format for Video Action Recognition.
VideoClassificationPredictionResult
Prediction output format for Video Classification.
VideoObjectTrackingPredictionResult
Prediction output format for Video Object Tracking.
Frame
The fields xMin
, xMax
, yMin
, and yMax
refer to a
bounding box, i.e. the rectangle over the video frame pinpointing
the found AnnotationSpec. The coordinates are relative to the frame
size, and the point 0,0 is in the top left of the frame.
AutoMlForecasting
A TrainingJob that trains and uploads an AutoML Forecasting Model.
AutoMlForecastingInputs
Granularity
A duration of time expressed in time granularity units.
Transformation
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
CategoricalTransformation
Training pipeline will perform following transformation functions.
The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
NumericTransformation
Training pipeline will perform following transformation functions.
The value converted to float32.
The z_score of the value.
log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
A boolean value that indicates whether the value is valid.
TextTransformation
Training pipeline will perform following transformation functions.
The text as is--no change to case, punctuation, spelling, tense, and so on.
Convert the category name to a dictionary lookup index and generate an embedding for each index.
TimestampTransformation
Training pipeline will perform following transformation functions.
Apply the transformation functions for Numerical columns.
Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column.
Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
AutoMlForecastingMetadata
Model metadata specific to AutoML Forecasting.
AutoMlImageClassification
A TrainingJob that trains and uploads an AutoML Image Classification Model.
AutoMlImageClassificationInputs
ModelType
AutoMlImageClassificationMetadata
SuccessfulStopReason
AutoMlImageObjectDetection
A TrainingJob that trains and uploads an AutoML Image Object Detection Model.
AutoMlImageObjectDetectionInputs
ModelType
AutoMlImageObjectDetectionMetadata
SuccessfulStopReason
AutoMlImageSegmentation
A TrainingJob that trains and uploads an AutoML Image Segmentation Model.
AutoMlImageSegmentationInputs
ModelType
AutoMlImageSegmentationMetadata
SuccessfulStopReason
AutoMlTables
A TrainingJob that trains and uploads an AutoML Tables Model.
AutoMlTablesInputs
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Transformation
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
CategoricalArrayTransformation
Treats the column as categorical array and performs following transformation functions.
- For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Empty arrays treated as an embedding of zeroes.
CategoricalTransformation
Training pipeline will perform following transformation functions.
- The categorical string as is--no change to case, punctuation, spelling, tense, and so on.
- Convert the category name to a dictionary lookup index and generate an embedding for each index.
- Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding.
NumericArrayTransformation
Treats the column as numerical array and performs following transformation functions.
- All transformations for Numerical types applied to the average of the all elements.
- The average of empty arrays is treated as zero.
NumericTransformation
Training pipeline will perform following transformation functions.
- The value converted to float32.
- The z_score of the value.
- log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value.
- A boolean value that indicates whether the value is valid.
TextArrayTransformation
Treats the column as text array and performs following transformation functions.
- Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns.
- Empty arrays treated as an empty text.
TextTransformation
Training pipeline will perform following transformation functions.
- The text as is--no change to case, punctuation, spelling, tense, and so on.
- Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean.
- Tokenization is based on unicode script boundaries.
- Missing values get their own lookup index and resulting embedding.
- Stop-words receive no special treatment and are not removed.
TimestampTransformation
Training pipeline will perform following transformation functions.
- Apply the transformation functions for Numerical columns.
- Determine the year, month, day,and weekday. Treat each value from the
- timestamp as a Categorical column.
- Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed.
AutoMlTablesMetadata
Model metadata specific to AutoML Tables.
AutoMlTextClassification
A TrainingJob that trains and uploads an AutoML Text Classification Model.
AutoMlTextClassificationInputs
AutoMlTextExtraction
A TrainingJob that trains and uploads an AutoML Text Extraction Model.
AutoMlTextExtractionInputs
API documentation for aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types.AutoMlTextExtractionInputs
class.
AutoMlTextSentiment
A TrainingJob that trains and uploads an AutoML Text Sentiment Model.
AutoMlTextSentimentInputs
AutoMlVideoActionRecognition
A TrainingJob that trains and uploads an AutoML Video Action Recognition Model.
AutoMlVideoActionRecognitionInputs
ModelType
AutoMlVideoClassification
A TrainingJob that trains and uploads an AutoML Video Classification Model.
AutoMlVideoClassificationInputs
ModelType
AutoMlVideoObjectTracking
A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model.
AutoMlVideoObjectTrackingInputs
ModelType
ExportEvaluatedDataItemsConfig
Configuration for exporting test set predictions to a BigQuery table.
DatasetServiceAsyncClient
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceClient
The service that manages Vertex AI Dataset and its child resources.
ListAnnotationsAsyncPager
A pager for iterating through list_annotations
requests.
This class thinly wraps an initial
ListAnnotationsResponse object, and
provides an __aiter__
method to iterate through its
annotations
field.
If there are more pages, the __aiter__
method will make additional
ListAnnotations
requests and continue to iterate
through the annotations
field on the
corresponding responses.
All the usual ListAnnotationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListAnnotationsPager
A pager for iterating through list_annotations
requests.
This class thinly wraps an initial
ListAnnotationsResponse object, and
provides an __iter__
method to iterate through its
annotations
field.
If there are more pages, the __iter__
method will make additional
ListAnnotations
requests and continue to iterate
through the annotations
field on the
corresponding responses.
All the usual ListAnnotationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataItemsAsyncPager
A pager for iterating through list_data_items
requests.
This class thinly wraps an initial
ListDataItemsResponse object, and
provides an __aiter__
method to iterate through its
data_items
field.
If there are more pages, the __aiter__
method will make additional
ListDataItems
requests and continue to iterate
through the data_items
field on the
corresponding responses.
All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataItemsPager
A pager for iterating through list_data_items
requests.
This class thinly wraps an initial
ListDataItemsResponse object, and
provides an __iter__
method to iterate through its
data_items
field.
If there are more pages, the __iter__
method will make additional
ListDataItems
requests and continue to iterate
through the data_items
field on the
corresponding responses.
All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetVersionsAsyncPager
A pager for iterating through list_dataset_versions
requests.
This class thinly wraps an initial
ListDatasetVersionsResponse object, and
provides an __aiter__
method to iterate through its
dataset_versions
field.
If there are more pages, the __aiter__
method will make additional
ListDatasetVersions
requests and continue to iterate
through the dataset_versions
field on the
corresponding responses.
All the usual ListDatasetVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetVersionsPager
A pager for iterating through list_dataset_versions
requests.
This class thinly wraps an initial
ListDatasetVersionsResponse object, and
provides an __iter__
method to iterate through its
dataset_versions
field.
If there are more pages, the __iter__
method will make additional
ListDatasetVersions
requests and continue to iterate
through the dataset_versions
field on the
corresponding responses.
All the usual ListDatasetVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetsAsyncPager
A pager for iterating through list_datasets
requests.
This class thinly wraps an initial
ListDatasetsResponse object, and
provides an __aiter__
method to iterate through its
datasets
field.
If there are more pages, the __aiter__
method will make additional
ListDatasets
requests and continue to iterate
through the datasets
field on the
corresponding responses.
All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetsPager
A pager for iterating through list_datasets
requests.
This class thinly wraps an initial
ListDatasetsResponse object, and
provides an __iter__
method to iterate through its
datasets
field.
If there are more pages, the __iter__
method will make additional
ListDatasets
requests and continue to iterate
through the datasets
field on the
corresponding responses.
All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSavedQueriesAsyncPager
A pager for iterating through list_saved_queries
requests.
This class thinly wraps an initial
ListSavedQueriesResponse object, and
provides an __aiter__
method to iterate through its
saved_queries
field.
If there are more pages, the __aiter__
method will make additional
ListSavedQueries
requests and continue to iterate
through the saved_queries
field on the
corresponding responses.
All the usual ListSavedQueriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSavedQueriesPager
A pager for iterating through list_saved_queries
requests.
This class thinly wraps an initial
ListSavedQueriesResponse object, and
provides an __iter__
method to iterate through its
saved_queries
field.
If there are more pages, the __iter__
method will make additional
ListSavedQueries
requests and continue to iterate
through the saved_queries
field on the
corresponding responses.
All the usual ListSavedQueriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchDataItemsAsyncPager
A pager for iterating through search_data_items
requests.
This class thinly wraps an initial
SearchDataItemsResponse object, and
provides an __aiter__
method to iterate through its
data_item_views
field.
If there are more pages, the __aiter__
method will make additional
SearchDataItems
requests and continue to iterate
through the data_item_views
field on the
corresponding responses.
All the usual SearchDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchDataItemsPager
A pager for iterating through search_data_items
requests.
This class thinly wraps an initial
SearchDataItemsResponse object, and
provides an __iter__
method to iterate through its
data_item_views
field.
If there are more pages, the __iter__
method will make additional
SearchDataItems
requests and continue to iterate
through the data_item_views
field on the
corresponding responses.
All the usual SearchDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
DeploymentResourcePoolServiceAsyncClient
A service that manages the DeploymentResourcePool resource.
DeploymentResourcePoolServiceClient
A service that manages the DeploymentResourcePool resource.
ListDeploymentResourcePoolsAsyncPager
A pager for iterating through list_deployment_resource_pools
requests.
This class thinly wraps an initial
ListDeploymentResourcePoolsResponse object, and
provides an __aiter__
method to iterate through its
deployment_resource_pools
field.
If there are more pages, the __aiter__
method will make additional
ListDeploymentResourcePools
requests and continue to iterate
through the deployment_resource_pools
field on the
corresponding responses.
All the usual ListDeploymentResourcePoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDeploymentResourcePoolsPager
A pager for iterating through list_deployment_resource_pools
requests.
This class thinly wraps an initial
ListDeploymentResourcePoolsResponse object, and
provides an __iter__
method to iterate through its
deployment_resource_pools
field.
If there are more pages, the __iter__
method will make additional
ListDeploymentResourcePools
requests and continue to iterate
through the deployment_resource_pools
field on the
corresponding responses.
All the usual ListDeploymentResourcePoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
QueryDeployedModelsAsyncPager
A pager for iterating through query_deployed_models
requests.
This class thinly wraps an initial
QueryDeployedModelsResponse object, and
provides an __aiter__
method to iterate through its
deployed_models
field.
If there are more pages, the __aiter__
method will make additional
QueryDeployedModels
requests and continue to iterate
through the deployed_models
field on the
corresponding responses.
All the usual QueryDeployedModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
QueryDeployedModelsPager
A pager for iterating through query_deployed_models
requests.
This class thinly wraps an initial
QueryDeployedModelsResponse object, and
provides an __iter__
method to iterate through its
deployed_models
field.
If there are more pages, the __iter__
method will make additional
QueryDeployedModels
requests and continue to iterate
through the deployed_models
field on the
corresponding responses.
All the usual QueryDeployedModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
EndpointServiceAsyncClient
A service for managing Vertex AI's Endpoints.
EndpointServiceClient
A service for managing Vertex AI's Endpoints.
ListEndpointsAsyncPager
A pager for iterating through list_endpoints
requests.
This class thinly wraps an initial
ListEndpointsResponse object, and
provides an __aiter__
method to iterate through its
endpoints
field.
If there are more pages, the __aiter__
method will make additional
ListEndpoints
requests and continue to iterate
through the endpoints
field on the
corresponding responses.
All the usual ListEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListEndpointsPager
A pager for iterating through list_endpoints
requests.
This class thinly wraps an initial
ListEndpointsResponse object, and
provides an __iter__
method to iterate through its
endpoints
field.
If there are more pages, the __iter__
method will make additional
ListEndpoints
requests and continue to iterate
through the endpoints
field on the
corresponding responses.
All the usual ListEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeatureOnlineStoreAdminServiceAsyncClient
The service that handles CRUD and List for resources for FeatureOnlineStore.
FeatureOnlineStoreAdminServiceClient
The service that handles CRUD and List for resources for FeatureOnlineStore.
ListFeatureOnlineStoresAsyncPager
A pager for iterating through list_feature_online_stores
requests.
This class thinly wraps an initial
ListFeatureOnlineStoresResponse object, and
provides an __aiter__
method to iterate through its
feature_online_stores
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureOnlineStores
requests and continue to iterate
through the feature_online_stores
field on the
corresponding responses.
All the usual ListFeatureOnlineStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureOnlineStoresPager
A pager for iterating through list_feature_online_stores
requests.
This class thinly wraps an initial
ListFeatureOnlineStoresResponse object, and
provides an __iter__
method to iterate through its
feature_online_stores
field.
If there are more pages, the __iter__
method will make additional
ListFeatureOnlineStores
requests and continue to iterate
through the feature_online_stores
field on the
corresponding responses.
All the usual ListFeatureOnlineStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewSyncsAsyncPager
A pager for iterating through list_feature_view_syncs
requests.
This class thinly wraps an initial
ListFeatureViewSyncsResponse object, and
provides an __aiter__
method to iterate through its
feature_view_syncs
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureViewSyncs
requests and continue to iterate
through the feature_view_syncs
field on the
corresponding responses.
All the usual ListFeatureViewSyncsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewSyncsPager
A pager for iterating through list_feature_view_syncs
requests.
This class thinly wraps an initial
ListFeatureViewSyncsResponse object, and
provides an __iter__
method to iterate through its
feature_view_syncs
field.
If there are more pages, the __iter__
method will make additional
ListFeatureViewSyncs
requests and continue to iterate
through the feature_view_syncs
field on the
corresponding responses.
All the usual ListFeatureViewSyncsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewsAsyncPager
A pager for iterating through list_feature_views
requests.
This class thinly wraps an initial
ListFeatureViewsResponse object, and
provides an __aiter__
method to iterate through its
feature_views
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureViews
requests and continue to iterate
through the feature_views
field on the
corresponding responses.
All the usual ListFeatureViewsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewsPager
A pager for iterating through list_feature_views
requests.
This class thinly wraps an initial
ListFeatureViewsResponse object, and
provides an __iter__
method to iterate through its
feature_views
field.
If there are more pages, the __iter__
method will make additional
ListFeatureViews
requests and continue to iterate
through the feature_views
field on the
corresponding responses.
All the usual ListFeatureViewsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeatureOnlineStoreServiceAsyncClient
A service for fetching feature values from the online store.
FeatureOnlineStoreServiceClient
A service for fetching feature values from the online store.
FeatureRegistryServiceAsyncClient
The service that handles CRUD and List for resources for FeatureRegistry.
FeatureRegistryServiceClient
The service that handles CRUD and List for resources for FeatureRegistry.
ListFeatureGroupsAsyncPager
A pager for iterating through list_feature_groups
requests.
This class thinly wraps an initial
ListFeatureGroupsResponse object, and
provides an __aiter__
method to iterate through its
feature_groups
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureGroups
requests and continue to iterate
through the feature_groups
field on the
corresponding responses.
All the usual ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureGroupsPager
A pager for iterating through list_feature_groups
requests.
This class thinly wraps an initial
ListFeatureGroupsResponse object, and
provides an __iter__
method to iterate through its
feature_groups
field.
If there are more pages, the __iter__
method will make additional
ListFeatureGroups
requests and continue to iterate
through the feature_groups
field on the
corresponding responses.
All the usual ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesAsyncPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeaturestoreOnlineServingServiceAsyncClient
A service for serving online feature values.
FeaturestoreOnlineServingServiceClient
A service for serving online feature values.
FeaturestoreServiceAsyncClient
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceClient
The service that handles CRUD and List for resources for Featurestore.
ListEntityTypesAsyncPager
A pager for iterating through list_entity_types
requests.
This class thinly wraps an initial
ListEntityTypesResponse object, and
provides an __aiter__
method to iterate through its
entity_types
field.
If there are more pages, the __aiter__
method will make additional
ListEntityTypes
requests and continue to iterate
through the entity_types
field on the
corresponding responses.
All the usual ListEntityTypesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListEntityTypesPager
A pager for iterating through list_entity_types
requests.
This class thinly wraps an initial
ListEntityTypesResponse object, and
provides an __iter__
method to iterate through its
entity_types
field.
If there are more pages, the __iter__
method will make additional
ListEntityTypes
requests and continue to iterate
through the entity_types
field on the
corresponding responses.
All the usual ListEntityTypesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesAsyncPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturestoresAsyncPager
A pager for iterating through list_featurestores
requests.
This class thinly wraps an initial
ListFeaturestoresResponse object, and
provides an __aiter__
method to iterate through its
featurestores
field.
If there are more pages, the __aiter__
method will make additional
ListFeaturestores
requests and continue to iterate
through the featurestores
field on the
corresponding responses.
All the usual ListFeaturestoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturestoresPager
A pager for iterating through list_featurestores
requests.
This class thinly wraps an initial
ListFeaturestoresResponse object, and
provides an __iter__
method to iterate through its
featurestores
field.
If there are more pages, the __iter__
method will make additional
ListFeaturestores
requests and continue to iterate
through the featurestores
field on the
corresponding responses.
All the usual ListFeaturestoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchFeaturesAsyncPager
A pager for iterating through search_features
requests.
This class thinly wraps an initial
SearchFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
SearchFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual SearchFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchFeaturesPager
A pager for iterating through search_features
requests.
This class thinly wraps an initial
SearchFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
SearchFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual SearchFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
GenAiTuningServiceAsyncClient
A service for creating and managing GenAI Tuning Jobs.
GenAiTuningServiceClient
A service for creating and managing GenAI Tuning Jobs.
ListTuningJobsAsyncPager
A pager for iterating through list_tuning_jobs
requests.
This class thinly wraps an initial
ListTuningJobsResponse object, and
provides an __aiter__
method to iterate through its
tuning_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListTuningJobs
requests and continue to iterate
through the tuning_jobs
field on the
corresponding responses.
All the usual ListTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTuningJobsPager
A pager for iterating through list_tuning_jobs
requests.
This class thinly wraps an initial
ListTuningJobsResponse object, and
provides an __iter__
method to iterate through its
tuning_jobs
field.
If there are more pages, the __iter__
method will make additional
ListTuningJobs
requests and continue to iterate
through the tuning_jobs
field on the
corresponding responses.
All the usual ListTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
IndexEndpointServiceAsyncClient
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceClient
A service for managing Vertex AI's IndexEndpoints.
ListIndexEndpointsAsyncPager
A pager for iterating through list_index_endpoints
requests.
This class thinly wraps an initial
ListIndexEndpointsResponse object, and
provides an __aiter__
method to iterate through its
index_endpoints
field.
If there are more pages, the __aiter__
method will make additional
ListIndexEndpoints
requests and continue to iterate
through the index_endpoints
field on the
corresponding responses.
All the usual ListIndexEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListIndexEndpointsPager
A pager for iterating through list_index_endpoints
requests.
This class thinly wraps an initial
ListIndexEndpointsResponse object, and
provides an __iter__
method to iterate through its
index_endpoints
field.
If there are more pages, the __iter__
method will make additional
ListIndexEndpoints
requests and continue to iterate
through the index_endpoints
field on the
corresponding responses.
All the usual ListIndexEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
IndexServiceAsyncClient
A service for creating and managing Vertex AI's Index resources.
IndexServiceClient
A service for creating and managing Vertex AI's Index resources.
ListIndexesAsyncPager
A pager for iterating through list_indexes
requests.
This class thinly wraps an initial
ListIndexesResponse object, and
provides an __aiter__
method to iterate through its
indexes
field.
If there are more pages, the __aiter__
method will make additional
ListIndexes
requests and continue to iterate
through the indexes
field on the
corresponding responses.
All the usual ListIndexesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListIndexesPager
A pager for iterating through list_indexes
requests.
This class thinly wraps an initial
ListIndexesResponse object, and
provides an __iter__
method to iterate through its
indexes
field.
If there are more pages, the __iter__
method will make additional
ListIndexes
requests and continue to iterate
through the indexes
field on the
corresponding responses.
All the usual ListIndexesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
JobServiceAsyncClient
A service for creating and managing Vertex AI's jobs.
JobServiceClient
A service for creating and managing Vertex AI's jobs.
ListBatchPredictionJobsAsyncPager
A pager for iterating through list_batch_prediction_jobs
requests.
This class thinly wraps an initial
ListBatchPredictionJobsResponse object, and
provides an __aiter__
method to iterate through its
batch_prediction_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListBatchPredictionJobs
requests and continue to iterate
through the batch_prediction_jobs
field on the
corresponding responses.
All the usual ListBatchPredictionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListBatchPredictionJobsPager
A pager for iterating through list_batch_prediction_jobs
requests.
This class thinly wraps an initial
ListBatchPredictionJobsResponse object, and
provides an __iter__
method to iterate through its
batch_prediction_jobs
field.
If there are more pages, the __iter__
method will make additional
ListBatchPredictionJobs
requests and continue to iterate
through the batch_prediction_jobs
field on the
corresponding responses.
All the usual ListBatchPredictionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListCustomJobsAsyncPager
A pager for iterating through list_custom_jobs
requests.
This class thinly wraps an initial
ListCustomJobsResponse object, and
provides an __aiter__
method to iterate through its
custom_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListCustomJobs
requests and continue to iterate
through the custom_jobs
field on the
corresponding responses.
All the usual ListCustomJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListCustomJobsPager
A pager for iterating through list_custom_jobs
requests.
This class thinly wraps an initial
ListCustomJobsResponse object, and
provides an __iter__
method to iterate through its
custom_jobs
field.
If there are more pages, the __iter__
method will make additional
ListCustomJobs
requests and continue to iterate
through the custom_jobs
field on the
corresponding responses.
All the usual ListCustomJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataLabelingJobsAsyncPager
A pager for iterating through list_data_labeling_jobs
requests.
This class thinly wraps an initial
ListDataLabelingJobsResponse object, and
provides an __aiter__
method to iterate through its
data_labeling_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListDataLabelingJobs
requests and continue to iterate
through the data_labeling_jobs
field on the
corresponding responses.
All the usual ListDataLabelingJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataLabelingJobsPager
A pager for iterating through list_data_labeling_jobs
requests.
This class thinly wraps an initial
ListDataLabelingJobsResponse object, and
provides an __iter__
method to iterate through its
data_labeling_jobs
field.
If there are more pages, the __iter__
method will make additional
ListDataLabelingJobs
requests and continue to iterate
through the data_labeling_jobs
field on the
corresponding responses.
All the usual ListDataLabelingJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListHyperparameterTuningJobsAsyncPager
A pager for iterating through list_hyperparameter_tuning_jobs
requests.
This class thinly wraps an initial
ListHyperparameterTuningJobsResponse object, and
provides an __aiter__
method to iterate through its
hyperparameter_tuning_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListHyperparameterTuningJobs
requests and continue to iterate
through the hyperparameter_tuning_jobs
field on the
corresponding responses.
All the usual ListHyperparameterTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListHyperparameterTuningJobsPager
A pager for iterating through list_hyperparameter_tuning_jobs
requests.
This class thinly wraps an initial
ListHyperparameterTuningJobsResponse object, and
provides an __iter__
method to iterate through its
hyperparameter_tuning_jobs
field.
If there are more pages, the __iter__
method will make additional
ListHyperparameterTuningJobs
requests and continue to iterate
through the hyperparameter_tuning_jobs
field on the
corresponding responses.
All the usual ListHyperparameterTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelDeploymentMonitoringJobsAsyncPager
A pager for iterating through list_model_deployment_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelDeploymentMonitoringJobsResponse object, and
provides an __aiter__
method to iterate through its
model_deployment_monitoring_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListModelDeploymentMonitoringJobs
requests and continue to iterate
through the model_deployment_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelDeploymentMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelDeploymentMonitoringJobsPager
A pager for iterating through list_model_deployment_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelDeploymentMonitoringJobsResponse object, and
provides an __iter__
method to iterate through its
model_deployment_monitoring_jobs
field.
If there are more pages, the __iter__
method will make additional
ListModelDeploymentMonitoringJobs
requests and continue to iterate
through the model_deployment_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelDeploymentMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasJobsAsyncPager
A pager for iterating through list_nas_jobs
requests.
This class thinly wraps an initial
ListNasJobsResponse object, and
provides an __aiter__
method to iterate through its
nas_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListNasJobs
requests and continue to iterate
through the nas_jobs
field on the
corresponding responses.
All the usual ListNasJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasJobsPager
A pager for iterating through list_nas_jobs
requests.
This class thinly wraps an initial
ListNasJobsResponse object, and
provides an __iter__
method to iterate through its
nas_jobs
field.
If there are more pages, the __iter__
method will make additional
ListNasJobs
requests and continue to iterate
through the nas_jobs
field on the
corresponding responses.
All the usual ListNasJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasTrialDetailsAsyncPager
A pager for iterating through list_nas_trial_details
requests.
This class thinly wraps an initial
ListNasTrialDetailsResponse object, and
provides an __aiter__
method to iterate through its
nas_trial_details
field.
If there are more pages, the __aiter__
method will make additional
ListNasTrialDetails
requests and continue to iterate
through the nas_trial_details
field on the
corresponding responses.
All the usual ListNasTrialDetailsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasTrialDetailsPager
A pager for iterating through list_nas_trial_details
requests.
This class thinly wraps an initial
ListNasTrialDetailsResponse object, and
provides an __iter__
method to iterate through its
nas_trial_details
field.
If there are more pages, the __iter__
method will make additional
ListNasTrialDetails
requests and continue to iterate
through the nas_trial_details
field on the
corresponding responses.
All the usual ListNasTrialDetailsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelDeploymentMonitoringStatsAnomaliesAsyncPager
A pager for iterating through search_model_deployment_monitoring_stats_anomalies
requests.
This class thinly wraps an initial
SearchModelDeploymentMonitoringStatsAnomaliesResponse object, and
provides an __aiter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __aiter__
method will make additional
SearchModelDeploymentMonitoringStatsAnomalies
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelDeploymentMonitoringStatsAnomaliesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelDeploymentMonitoringStatsAnomaliesPager
A pager for iterating through search_model_deployment_monitoring_stats_anomalies
requests.
This class thinly wraps an initial
SearchModelDeploymentMonitoringStatsAnomaliesResponse object, and
provides an __iter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __iter__
method will make additional
SearchModelDeploymentMonitoringStatsAnomalies
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelDeploymentMonitoringStatsAnomaliesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
LlmUtilityServiceAsyncClient
Service for LLM related utility functions.
LlmUtilityServiceClient
Service for LLM related utility functions.
MatchServiceAsyncClient
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceClient
MatchService is a Google managed service for efficient vector similarity search at scale.
MetadataServiceAsyncClient
Service for reading and writing metadata entries.
MetadataServiceClient
Service for reading and writing metadata entries.
ListArtifactsAsyncPager
A pager for iterating through list_artifacts
requests.
This class thinly wraps an initial
ListArtifactsResponse object, and
provides an __aiter__
method to iterate through its
artifacts
field.
If there are more pages, the __aiter__
method will make additional
ListArtifacts
requests and continue to iterate
through the artifacts
field on the
corresponding responses.
All the usual ListArtifactsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListArtifactsPager
A pager for iterating through list_artifacts
requests.
This class thinly wraps an initial
ListArtifactsResponse object, and
provides an __iter__
method to iterate through its
artifacts
field.
If there are more pages, the __iter__
method will make additional
ListArtifacts
requests and continue to iterate
through the artifacts
field on the
corresponding responses.
All the usual ListArtifactsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListContextsAsyncPager
A pager for iterating through list_contexts
requests.
This class thinly wraps an initial
ListContextsResponse object, and
provides an __aiter__
method to iterate through its
contexts
field.
If there are more pages, the __aiter__
method will make additional
ListContexts
requests and continue to iterate
through the contexts
field on the
corresponding responses.
All the usual ListContextsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListContextsPager
A pager for iterating through list_contexts
requests.
This class thinly wraps an initial
ListContextsResponse object, and
provides an __iter__
method to iterate through its
contexts
field.
If there are more pages, the __iter__
method will make additional
ListContexts
requests and continue to iterate
through the contexts
field on the
corresponding responses.
All the usual ListContextsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListExecutionsAsyncPager
A pager for iterating through list_executions
requests.
This class thinly wraps an initial
ListExecutionsResponse object, and
provides an __aiter__
method to iterate through its
executions
field.
If there are more pages, the __aiter__
method will make additional
ListExecutions
requests and continue to iterate
through the executions
field on the
corresponding responses.
All the usual ListExecutionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListExecutionsPager
A pager for iterating through list_executions
requests.
This class thinly wraps an initial
ListExecutionsResponse object, and
provides an __iter__
method to iterate through its
executions
field.
If there are more pages, the __iter__
method will make additional
ListExecutions
requests and continue to iterate
through the executions
field on the
corresponding responses.
All the usual ListExecutionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataSchemasAsyncPager
A pager for iterating through list_metadata_schemas
requests.
This class thinly wraps an initial
ListMetadataSchemasResponse object, and
provides an __aiter__
method to iterate through its
metadata_schemas
field.
If there are more pages, the __aiter__
method will make additional
ListMetadataSchemas
requests and continue to iterate
through the metadata_schemas
field on the
corresponding responses.
All the usual ListMetadataSchemasResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataSchemasPager
A pager for iterating through list_metadata_schemas
requests.
This class thinly wraps an initial
ListMetadataSchemasResponse object, and
provides an __iter__
method to iterate through its
metadata_schemas
field.
If there are more pages, the __iter__
method will make additional
ListMetadataSchemas
requests and continue to iterate
through the metadata_schemas
field on the
corresponding responses.
All the usual ListMetadataSchemasResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataStoresAsyncPager
A pager for iterating through list_metadata_stores
requests.
This class thinly wraps an initial
ListMetadataStoresResponse object, and
provides an __aiter__
method to iterate through its
metadata_stores
field.
If there are more pages, the __aiter__
method will make additional
ListMetadataStores
requests and continue to iterate
through the metadata_stores
field on the
corresponding responses.
All the usual ListMetadataStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataStoresPager
A pager for iterating through list_metadata_stores
requests.
This class thinly wraps an initial
ListMetadataStoresResponse object, and
provides an __iter__
method to iterate through its
metadata_stores
field.
If there are more pages, the __iter__
method will make additional
ListMetadataStores
requests and continue to iterate
through the metadata_stores
field on the
corresponding responses.
All the usual ListMetadataStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
MigrationServiceAsyncClient
A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
MigrationServiceClient
A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
SearchMigratableResourcesAsyncPager
A pager for iterating through search_migratable_resources
requests.
This class thinly wraps an initial
SearchMigratableResourcesResponse object, and
provides an __aiter__
method to iterate through its
migratable_resources
field.
If there are more pages, the __aiter__
method will make additional
SearchMigratableResources
requests and continue to iterate
through the migratable_resources
field on the
corresponding responses.
All the usual SearchMigratableResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchMigratableResourcesPager
A pager for iterating through search_migratable_resources
requests.
This class thinly wraps an initial
SearchMigratableResourcesResponse object, and
provides an __iter__
method to iterate through its
migratable_resources
field.
If there are more pages, the __iter__
method will make additional
SearchMigratableResources
requests and continue to iterate
through the migratable_resources
field on the
corresponding responses.
All the usual SearchMigratableResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ModelGardenServiceAsyncClient
The interface of Model Garden Service.
ModelGardenServiceClient
The interface of Model Garden Service.
ModelServiceAsyncClient
A service for managing Vertex AI's machine learning Models.
ModelServiceClient
A service for managing Vertex AI's machine learning Models.
ListModelEvaluationSlicesAsyncPager
A pager for iterating through list_model_evaluation_slices
requests.
This class thinly wraps an initial
ListModelEvaluationSlicesResponse object, and
provides an __aiter__
method to iterate through its
model_evaluation_slices
field.
If there are more pages, the __aiter__
method will make additional
ListModelEvaluationSlices
requests and continue to iterate
through the model_evaluation_slices
field on the
corresponding responses.
All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationSlicesPager
A pager for iterating through list_model_evaluation_slices
requests.
This class thinly wraps an initial
ListModelEvaluationSlicesResponse object, and
provides an __iter__
method to iterate through its
model_evaluation_slices
field.
If there are more pages, the __iter__
method will make additional
ListModelEvaluationSlices
requests and continue to iterate
through the model_evaluation_slices
field on the
corresponding responses.
All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationsAsyncPager
A pager for iterating through list_model_evaluations
requests.
This class thinly wraps an initial
ListModelEvaluationsResponse object, and
provides an __aiter__
method to iterate through its
model_evaluations
field.
If there are more pages, the __aiter__
method will make additional
ListModelEvaluations
requests and continue to iterate
through the model_evaluations
field on the
corresponding responses.
All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationsPager
A pager for iterating through list_model_evaluations
requests.
This class thinly wraps an initial
ListModelEvaluationsResponse object, and
provides an __iter__
method to iterate through its
model_evaluations
field.
If there are more pages, the __iter__
method will make additional
ListModelEvaluations
requests and continue to iterate
through the model_evaluations
field on the
corresponding responses.
All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelVersionsAsyncPager
A pager for iterating through list_model_versions
requests.
This class thinly wraps an initial
ListModelVersionsResponse object, and
provides an __aiter__
method to iterate through its
models
field.
If there are more pages, the __aiter__
method will make additional
ListModelVersions
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelVersionsPager
A pager for iterating through list_model_versions
requests.
This class thinly wraps an initial
ListModelVersionsResponse object, and
provides an __iter__
method to iterate through its
models
field.
If there are more pages, the __iter__
method will make additional
ListModelVersions
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelsAsyncPager
A pager for iterating through list_models
requests.
This class thinly wraps an initial
ListModelsResponse object, and
provides an __aiter__
method to iterate through its
models
field.
If there are more pages, the __aiter__
method will make additional
ListModels
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelsPager
A pager for iterating through list_models
requests.
This class thinly wraps an initial
ListModelsResponse object, and
provides an __iter__
method to iterate through its
models
field.
If there are more pages, the __iter__
method will make additional
ListModels
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
NotebookServiceAsyncClient
The interface for Vertex Notebook service (a.k.a. Colab on Workbench).
NotebookServiceClient
The interface for Vertex Notebook service (a.k.a. Colab on Workbench).
ListNotebookRuntimeTemplatesAsyncPager
A pager for iterating through list_notebook_runtime_templates
requests.
This class thinly wraps an initial
ListNotebookRuntimeTemplatesResponse object, and
provides an __aiter__
method to iterate through its
notebook_runtime_templates
field.
If there are more pages, the __aiter__
method will make additional
ListNotebookRuntimeTemplates
requests and continue to iterate
through the notebook_runtime_templates
field on the
corresponding responses.
All the usual ListNotebookRuntimeTemplatesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimeTemplatesPager
A pager for iterating through list_notebook_runtime_templates
requests.
This class thinly wraps an initial
ListNotebookRuntimeTemplatesResponse object, and
provides an __iter__
method to iterate through its
notebook_runtime_templates
field.
If there are more pages, the __iter__
method will make additional
ListNotebookRuntimeTemplates
requests and continue to iterate
through the notebook_runtime_templates
field on the
corresponding responses.
All the usual ListNotebookRuntimeTemplatesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimesAsyncPager
A pager for iterating through list_notebook_runtimes
requests.
This class thinly wraps an initial
ListNotebookRuntimesResponse object, and
provides an __aiter__
method to iterate through its
notebook_runtimes
field.
If there are more pages, the __aiter__
method will make additional
ListNotebookRuntimes
requests and continue to iterate
through the notebook_runtimes
field on the
corresponding responses.
All the usual ListNotebookRuntimesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimesPager
A pager for iterating through list_notebook_runtimes
requests.
This class thinly wraps an initial
ListNotebookRuntimesResponse object, and
provides an __iter__
method to iterate through its
notebook_runtimes
field.
If there are more pages, the __iter__
method will make additional
ListNotebookRuntimes
requests and continue to iterate
through the notebook_runtimes
field on the
corresponding responses.
All the usual ListNotebookRuntimesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PersistentResourceServiceAsyncClient
A service for managing Vertex AI's machine learning PersistentResource.
PersistentResourceServiceClient
A service for managing Vertex AI's machine learning PersistentResource.
ListPersistentResourcesAsyncPager
A pager for iterating through list_persistent_resources
requests.
This class thinly wraps an initial
ListPersistentResourcesResponse object, and
provides an __aiter__
method to iterate through its
persistent_resources
field.
If there are more pages, the __aiter__
method will make additional
ListPersistentResources
requests and continue to iterate
through the persistent_resources
field on the
corresponding responses.
All the usual ListPersistentResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListPersistentResourcesPager
A pager for iterating through list_persistent_resources
requests.
This class thinly wraps an initial
ListPersistentResourcesResponse object, and
provides an __iter__
method to iterate through its
persistent_resources
field.
If there are more pages, the __iter__
method will make additional
ListPersistentResources
requests and continue to iterate
through the persistent_resources
field on the
corresponding responses.
All the usual ListPersistentResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PipelineServiceAsyncClient
A service for creating and managing Vertex AI's pipelines. This
includes both TrainingPipeline
resources (used for AutoML and
custom training) and PipelineJob
resources (used for Vertex AI
Pipelines).
PipelineServiceClient
A service for creating and managing Vertex AI's pipelines. This
includes both TrainingPipeline
resources (used for AutoML and
custom training) and PipelineJob
resources (used for Vertex AI
Pipelines).
ListPipelineJobsAsyncPager
A pager for iterating through list_pipeline_jobs
requests.
This class thinly wraps an initial
ListPipelineJobsResponse object, and
provides an __aiter__
method to iterate through its
pipeline_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListPipelineJobs
requests and continue to iterate
through the pipeline_jobs
field on the
corresponding responses.
All the usual ListPipelineJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListPipelineJobsPager
A pager for iterating through list_pipeline_jobs
requests.
This class thinly wraps an initial
ListPipelineJobsResponse object, and
provides an __iter__
method to iterate through its
pipeline_jobs
field.
If there are more pages, the __iter__
method will make additional
ListPipelineJobs
requests and continue to iterate
through the pipeline_jobs
field on the
corresponding responses.
All the usual ListPipelineJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrainingPipelinesAsyncPager
A pager for iterating through list_training_pipelines
requests.
This class thinly wraps an initial
ListTrainingPipelinesResponse object, and
provides an __aiter__
method to iterate through its
training_pipelines
field.
If there are more pages, the __aiter__
method will make additional
ListTrainingPipelines
requests and continue to iterate
through the training_pipelines
field on the
corresponding responses.
All the usual ListTrainingPipelinesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrainingPipelinesPager
A pager for iterating through list_training_pipelines
requests.
This class thinly wraps an initial
ListTrainingPipelinesResponse object, and
provides an __iter__
method to iterate through its
training_pipelines
field.
If there are more pages, the __iter__
method will make additional
ListTrainingPipelines
requests and continue to iterate
through the training_pipelines
field on the
corresponding responses.
All the usual ListTrainingPipelinesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PredictionServiceAsyncClient
A service for online predictions and explanations.
PredictionServiceClient
A service for online predictions and explanations.
ScheduleServiceAsyncClient
A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.
ScheduleServiceClient
A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.
ListSchedulesAsyncPager
A pager for iterating through list_schedules
requests.
This class thinly wraps an initial
ListSchedulesResponse object, and
provides an __aiter__
method to iterate through its
schedules
field.
If there are more pages, the __aiter__
method will make additional
ListSchedules
requests and continue to iterate
through the schedules
field on the
corresponding responses.
All the usual ListSchedulesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSchedulesPager
A pager for iterating through list_schedules
requests.
This class thinly wraps an initial
ListSchedulesResponse object, and
provides an __iter__
method to iterate through its
schedules
field.
If there are more pages, the __iter__
method will make additional
ListSchedules
requests and continue to iterate
through the schedules
field on the
corresponding responses.
All the usual ListSchedulesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SpecialistPoolServiceAsyncClient
A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.
SpecialistPoolServiceClient
A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.
ListSpecialistPoolsAsyncPager
A pager for iterating through list_specialist_pools
requests.
This class thinly wraps an initial
ListSpecialistPoolsResponse object, and
provides an __aiter__
method to iterate through its
specialist_pools
field.
If there are more pages, the __aiter__
method will make additional
ListSpecialistPools
requests and continue to iterate
through the specialist_pools
field on the
corresponding responses.
All the usual ListSpecialistPoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSpecialistPoolsPager
A pager for iterating through list_specialist_pools
requests.
This class thinly wraps an initial
ListSpecialistPoolsResponse object, and
provides an __iter__
method to iterate through its
specialist_pools
field.
If there are more pages, the __iter__
method will make additional
ListSpecialistPools
requests and continue to iterate
through the specialist_pools
field on the
corresponding responses.
All the usual ListSpecialistPoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
TensorboardServiceAsyncClient
TensorboardService
TensorboardServiceClient
TensorboardService
ExportTensorboardTimeSeriesDataAsyncPager
A pager for iterating through export_tensorboard_time_series_data
requests.
This class thinly wraps an initial
ExportTensorboardTimeSeriesDataResponse object, and
provides an __aiter__
method to iterate through its
time_series_data_points
field.
If there are more pages, the __aiter__
method will make additional
ExportTensorboardTimeSeriesData
requests and continue to iterate
through the time_series_data_points
field on the
corresponding responses.
All the usual ExportTensorboardTimeSeriesDataResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ExportTensorboardTimeSeriesDataPager
A pager for iterating through export_tensorboard_time_series_data
requests.
This class thinly wraps an initial
ExportTensorboardTimeSeriesDataResponse object, and
provides an __iter__
method to iterate through its
time_series_data_points
field.
If there are more pages, the __iter__
method will make additional
ExportTensorboardTimeSeriesData
requests and continue to iterate
through the time_series_data_points
field on the
corresponding responses.
All the usual ExportTensorboardTimeSeriesDataResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardExperimentsAsyncPager
A pager for iterating through list_tensorboard_experiments
requests.
This class thinly wraps an initial
ListTensorboardExperimentsResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_experiments
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardExperiments
requests and continue to iterate
through the tensorboard_experiments
field on the
corresponding responses.
All the usual ListTensorboardExperimentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardExperimentsPager
A pager for iterating through list_tensorboard_experiments
requests.
This class thinly wraps an initial
ListTensorboardExperimentsResponse object, and
provides an __iter__
method to iterate through its
tensorboard_experiments
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardExperiments
requests and continue to iterate
through the tensorboard_experiments
field on the
corresponding responses.
All the usual ListTensorboardExperimentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardRunsAsyncPager
A pager for iterating through list_tensorboard_runs
requests.
This class thinly wraps an initial
ListTensorboardRunsResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_runs
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardRuns
requests and continue to iterate
through the tensorboard_runs
field on the
corresponding responses.
All the usual ListTensorboardRunsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardRunsPager
A pager for iterating through list_tensorboard_runs
requests.
This class thinly wraps an initial
ListTensorboardRunsResponse object, and
provides an __iter__
method to iterate through its
tensorboard_runs
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardRuns
requests and continue to iterate
through the tensorboard_runs
field on the
corresponding responses.
All the usual ListTensorboardRunsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardTimeSeriesAsyncPager
A pager for iterating through list_tensorboard_time_series
requests.
This class thinly wraps an initial
ListTensorboardTimeSeriesResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_time_series
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardTimeSeries
requests and continue to iterate
through the tensorboard_time_series
field on the
corresponding responses.
All the usual ListTensorboardTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardTimeSeriesPager
A pager for iterating through list_tensorboard_time_series
requests.
This class thinly wraps an initial
ListTensorboardTimeSeriesResponse object, and
provides an __iter__
method to iterate through its
tensorboard_time_series
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardTimeSeries
requests and continue to iterate
through the tensorboard_time_series
field on the
corresponding responses.
All the usual ListTensorboardTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardsAsyncPager
A pager for iterating through list_tensorboards
requests.
This class thinly wraps an initial
ListTensorboardsResponse object, and
provides an __aiter__
method to iterate through its
tensorboards
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboards
requests and continue to iterate
through the tensorboards
field on the
corresponding responses.
All the usual ListTensorboardsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardsPager
A pager for iterating through list_tensorboards
requests.
This class thinly wraps an initial
ListTensorboardsResponse object, and
provides an __iter__
method to iterate through its
tensorboards
field.
If there are more pages, the __iter__
method will make additional
ListTensorboards
requests and continue to iterate
through the tensorboards
field on the
corresponding responses.
All the usual ListTensorboardsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
VizierServiceAsyncClient
Vertex AI Vizier API.
Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.
VizierServiceClient
Vertex AI Vizier API.
Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.
ListStudiesAsyncPager
A pager for iterating through list_studies
requests.
This class thinly wraps an initial
ListStudiesResponse object, and
provides an __aiter__
method to iterate through its
studies
field.
If there are more pages, the __aiter__
method will make additional
ListStudies
requests and continue to iterate
through the studies
field on the
corresponding responses.
All the usual ListStudiesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListStudiesPager
A pager for iterating through list_studies
requests.
This class thinly wraps an initial
ListStudiesResponse object, and
provides an __iter__
method to iterate through its
studies
field.
If there are more pages, the __iter__
method will make additional
ListStudies
requests and continue to iterate
through the studies
field on the
corresponding responses.
All the usual ListStudiesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrialsAsyncPager
A pager for iterating through list_trials
requests.
This class thinly wraps an initial
ListTrialsResponse object, and
provides an __aiter__
method to iterate through its
trials
field.
If there are more pages, the __aiter__
method will make additional
ListTrials
requests and continue to iterate
through the trials
field on the
corresponding responses.
All the usual ListTrialsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrialsPager
A pager for iterating through list_trials
requests.
This class thinly wraps an initial
ListTrialsResponse object, and
provides an __iter__
method to iterate through its
trials
field.
If there are more pages, the __iter__
method will make additional
ListTrials
requests and continue to iterate
through the trials
field on the
corresponding responses.
All the usual ListTrialsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
AcceleratorType
Represents a hardware accelerator type.
ActiveLearningConfig
Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AddContextArtifactsAndExecutionsRequest
Request message for MetadataService.AddContextArtifactsAndExecutions.
AddContextArtifactsAndExecutionsResponse
Response message for MetadataService.AddContextArtifactsAndExecutions.
AddContextChildrenRequest
Request message for MetadataService.AddContextChildren.
AddContextChildrenResponse
Response message for MetadataService.AddContextChildren.
AddExecutionEventsRequest
Request message for MetadataService.AddExecutionEvents.
AddExecutionEventsResponse
Response message for MetadataService.AddExecutionEvents.
AddTrialMeasurementRequest
Request message for VizierService.AddTrialMeasurement.
Annotation
Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
LabelsEntry
The abstract base class for a message.
AnnotationSpec
Identifies a concept with which DataItems may be annotated with.
Artifact
Instance of a general artifact.
LabelsEntry
The abstract base class for a message.
State
Describes the state of the Artifact.
AssignNotebookRuntimeOperationMetadata
Metadata information for NotebookService.AssignNotebookRuntime.
AssignNotebookRuntimeRequest
Request message for NotebookService.AssignNotebookRuntime.
Attribution
Attribution that explains a particular prediction output.
AutomaticResources
A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.
AutoscalingMetricSpec
The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.
AvroSource
The storage details for Avro input content.
BatchCancelPipelineJobsOperationMetadata
Runtime operation information for PipelineService.BatchCancelPipelineJobs.
BatchCancelPipelineJobsRequest
Request message for PipelineService.BatchCancelPipelineJobs.
BatchCancelPipelineJobsResponse
Response message for PipelineService.BatchCancelPipelineJobs.
BatchCreateFeaturesOperationMetadata
Details of operations that perform batch create Features.
BatchCreateFeaturesRequest
Request message for FeaturestoreService.BatchCreateFeatures.
BatchCreateFeaturesResponse
Response message for FeaturestoreService.BatchCreateFeatures.
BatchCreateTensorboardRunsRequest
Request message for TensorboardService.BatchCreateTensorboardRuns.
BatchCreateTensorboardRunsResponse
Response message for TensorboardService.BatchCreateTensorboardRuns.
BatchCreateTensorboardTimeSeriesRequest
Request message for TensorboardService.BatchCreateTensorboardTimeSeries.
BatchCreateTensorboardTimeSeriesResponse
Response message for TensorboardService.BatchCreateTensorboardTimeSeries.
BatchDedicatedResources
A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
BatchDeletePipelineJobsRequest
Request message for PipelineService.BatchDeletePipelineJobs.
BatchDeletePipelineJobsResponse
Response message for PipelineService.BatchDeletePipelineJobs.
BatchImportEvaluatedAnnotationsRequest
Request message for ModelService.BatchImportEvaluatedAnnotations
BatchImportEvaluatedAnnotationsResponse
Response message for ModelService.BatchImportEvaluatedAnnotations
BatchImportModelEvaluationSlicesRequest
Request message for ModelService.BatchImportModelEvaluationSlices
BatchImportModelEvaluationSlicesResponse
Response message for ModelService.BatchImportModelEvaluationSlices
BatchMigrateResourcesOperationMetadata
Runtime operation information for MigrationService.BatchMigrateResources.
PartialResult
Represents a partial result in batch migration operation for one MigrateResourceRequest.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BatchMigrateResourcesRequest
Request message for MigrationService.BatchMigrateResources.
BatchMigrateResourcesResponse
Response message for MigrationService.BatchMigrateResources.
BatchPredictionJob
A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.
InputConfig
Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
InstanceConfig
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
LabelsEntry
The abstract base class for a message.
OutputConfig
Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OutputInfo
Further describes this job's output. Supplements output_config.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BatchReadFeatureValuesOperationMetadata
Details of operations that batch reads Feature values.
BatchReadFeatureValuesRequest
Request message for FeaturestoreService.BatchReadFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EntityTypeSpec
Selects Features of an EntityType to read values of and specifies read settings.
PassThroughField
Describe pass-through fields in read_instance source.
BatchReadFeatureValuesResponse
Response message for FeaturestoreService.BatchReadFeatureValues.
BatchReadTensorboardTimeSeriesDataRequest
Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.
BatchReadTensorboardTimeSeriesDataResponse
Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.
BigQueryDestination
The BigQuery location for the output content.
BigQuerySource
The BigQuery location for the input content.
Blob
Content blob.
It's preferred to send as text directly rather than raw bytes.
BlurBaselineConfig
Config for blur baseline.
When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here:
BoolArray
A list of boolean values.
CancelBatchPredictionJobRequest
Request message for JobService.CancelBatchPredictionJob.
CancelCustomJobRequest
Request message for JobService.CancelCustomJob.
CancelDataLabelingJobRequest
Request message for JobService.CancelDataLabelingJob.
CancelHyperparameterTuningJobRequest
Request message for JobService.CancelHyperparameterTuningJob.
CancelNasJobRequest
Request message for JobService.CancelNasJob.
CancelPipelineJobRequest
Request message for PipelineService.CancelPipelineJob.
CancelTrainingPipelineRequest
Request message for PipelineService.CancelTrainingPipeline.
CancelTuningJobRequest
Request message for GenAiTuningService.CancelTuningJob.
Candidate
A response candidate generated from the model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FinishReason
The reason why the model stopped generating tokens. If empty, the model has not stopped generating the tokens.
CheckTrialEarlyStoppingStateMetatdata
This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
CheckTrialEarlyStoppingStateRequest
Request message for VizierService.CheckTrialEarlyStoppingState.
CheckTrialEarlyStoppingStateResponse
Response message for VizierService.CheckTrialEarlyStoppingState.
Citation
Source attributions for content.
CitationMetadata
A collection of source attributions for a piece of content.
CompleteTrialRequest
Request message for VizierService.CompleteTrial.
CompletionStats
Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
ComputeTokensRequest
Request message for ComputeTokens RPC call.
ComputeTokensResponse
Response message for ComputeTokens RPC call.
ContainerRegistryDestination
The Container Registry location for the container image.
ContainerSpec
The spec of a Container.
Content
The base structured datatype containing multi-part content of a message.
A Content
includes a role
field designating the producer of
the Content
and a parts
field containing multi-part data
that contains the content of the message turn.
Context
Instance of a general context.
LabelsEntry
The abstract base class for a message.
CopyModelOperationMetadata
Details of ModelService.CopyModel operation.
CopyModelRequest
Request message for ModelService.CopyModel.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CopyModelResponse
Response message of ModelService.CopyModel operation.
CountTokensRequest
Request message for [PredictionService.CountTokens][].
CountTokensResponse
Response message for [PredictionService.CountTokens][].
CreateArtifactRequest
Request message for MetadataService.CreateArtifact.
CreateBatchPredictionJobRequest
Request message for JobService.CreateBatchPredictionJob.
CreateContextRequest
Request message for MetadataService.CreateContext.
CreateCustomJobRequest
Request message for JobService.CreateCustomJob.
CreateDataLabelingJobRequest
Request message for JobService.CreateDataLabelingJob.
CreateDatasetOperationMetadata
Runtime operation information for DatasetService.CreateDataset.
CreateDatasetRequest
Request message for DatasetService.CreateDataset.
CreateDatasetVersionOperationMetadata
Runtime operation information for DatasetService.CreateDatasetVersion.
CreateDatasetVersionRequest
Request message for DatasetService.CreateDatasetVersion.
CreateDeploymentResourcePoolOperationMetadata
Runtime operation information for CreateDeploymentResourcePool method.
CreateDeploymentResourcePoolRequest
Request message for CreateDeploymentResourcePool method.
CreateEndpointOperationMetadata
Runtime operation information for EndpointService.CreateEndpoint.
CreateEndpointRequest
Request message for EndpointService.CreateEndpoint.
CreateEntityTypeOperationMetadata
Details of operations that perform create EntityType.
CreateEntityTypeRequest
Request message for FeaturestoreService.CreateEntityType.
CreateExecutionRequest
Request message for MetadataService.CreateExecution.
CreateFeatureGroupOperationMetadata
Details of operations that perform create FeatureGroup.
CreateFeatureGroupRequest
Request message for FeatureRegistryService.CreateFeatureGroup.
CreateFeatureOnlineStoreOperationMetadata
Details of operations that perform create FeatureOnlineStore.
CreateFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.CreateFeatureOnlineStore.
CreateFeatureOperationMetadata
Details of operations that perform create Feature.
CreateFeatureRequest
Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.
CreateFeatureViewOperationMetadata
Details of operations that perform create FeatureView.
CreateFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.CreateFeatureView.
CreateFeaturestoreOperationMetadata
Details of operations that perform create Featurestore.
CreateFeaturestoreRequest
Request message for FeaturestoreService.CreateFeaturestore.
CreateHyperparameterTuningJobRequest
Request message for JobService.CreateHyperparameterTuningJob.
CreateIndexEndpointOperationMetadata
Runtime operation information for IndexEndpointService.CreateIndexEndpoint.
CreateIndexEndpointRequest
Request message for IndexEndpointService.CreateIndexEndpoint.
CreateIndexOperationMetadata
Runtime operation information for IndexService.CreateIndex.
CreateIndexRequest
Request message for IndexService.CreateIndex.
CreateMetadataSchemaRequest
Request message for MetadataService.CreateMetadataSchema.
CreateMetadataStoreOperationMetadata
Details of operations that perform MetadataService.CreateMetadataStore.
CreateMetadataStoreRequest
Request message for MetadataService.CreateMetadataStore.
CreateModelDeploymentMonitoringJobRequest
Request message for JobService.CreateModelDeploymentMonitoringJob.
CreateNasJobRequest
Request message for JobService.CreateNasJob.
CreateNotebookRuntimeTemplateOperationMetadata
Metadata information for NotebookService.CreateNotebookRuntimeTemplate.
CreateNotebookRuntimeTemplateRequest
Request message for NotebookService.CreateNotebookRuntimeTemplate.
CreatePersistentResourceOperationMetadata
Details of operations that perform create PersistentResource.
CreatePersistentResourceRequest
Request message for PersistentResourceService.CreatePersistentResource.
CreatePipelineJobRequest
Request message for PipelineService.CreatePipelineJob.
CreateRegistryFeatureOperationMetadata
Details of operations that perform create FeatureGroup.
CreateScheduleRequest
Request message for ScheduleService.CreateSchedule.
CreateSpecialistPoolOperationMetadata
Runtime operation information for SpecialistPoolService.CreateSpecialistPool.
CreateSpecialistPoolRequest
Request message for SpecialistPoolService.CreateSpecialistPool.
CreateStudyRequest
Request message for VizierService.CreateStudy.
CreateTensorboardExperimentRequest
Request message for TensorboardService.CreateTensorboardExperiment.
CreateTensorboardOperationMetadata
Details of operations that perform create Tensorboard.
CreateTensorboardRequest
Request message for TensorboardService.CreateTensorboard.
CreateTensorboardRunRequest
Request message for TensorboardService.CreateTensorboardRun.
CreateTensorboardTimeSeriesRequest
Request message for TensorboardService.CreateTensorboardTimeSeries.
CreateTrainingPipelineRequest
Request message for PipelineService.CreateTrainingPipeline.
CreateTrialRequest
Request message for VizierService.CreateTrial.
CreateTuningJobRequest
Request message for GenAiTuningService.CreateTuningJob.
CsvDestination
The storage details for CSV output content.
CsvSource
The storage details for CSV input content.
CustomJob
Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).
LabelsEntry
The abstract base class for a message.
WebAccessUrisEntry
The abstract base class for a message.
CustomJobSpec
Represents the spec of a CustomJob.
DataItem
A piece of data in a Dataset. Could be an image, a video, a document or plain text.
LabelsEntry
The abstract base class for a message.
DataItemView
A container for a single DataItem and Annotations on it.
DataLabelingJob
DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
AnnotationLabelsEntry
The abstract base class for a message.
LabelsEntry
The abstract base class for a message.
Dataset
A collection of DataItems and Annotations on them.
LabelsEntry
The abstract base class for a message.
DatasetVersion
Describes the dataset version.
DedicatedResources
A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
DeleteArtifactRequest
Request message for MetadataService.DeleteArtifact.
DeleteBatchPredictionJobRequest
Request message for JobService.DeleteBatchPredictionJob.
DeleteContextRequest
Request message for MetadataService.DeleteContext.
DeleteCustomJobRequest
Request message for JobService.DeleteCustomJob.
DeleteDataLabelingJobRequest
Request message for JobService.DeleteDataLabelingJob.
DeleteDatasetRequest
Request message for DatasetService.DeleteDataset.
DeleteDatasetVersionRequest
Request message for DatasetService.DeleteDatasetVersion.
DeleteDeploymentResourcePoolRequest
Request message for DeleteDeploymentResourcePool method.
DeleteEndpointRequest
Request message for EndpointService.DeleteEndpoint.
DeleteEntityTypeRequest
Request message for [FeaturestoreService.DeleteEntityTypes][].
DeleteExecutionRequest
Request message for MetadataService.DeleteExecution.
DeleteFeatureGroupRequest
Request message for FeatureRegistryService.DeleteFeatureGroup.
DeleteFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore.
DeleteFeatureRequest
Request message for FeaturestoreService.DeleteFeature. Request message for FeatureRegistryService.DeleteFeature.
DeleteFeatureValuesOperationMetadata
Details of operations that delete Feature values.
DeleteFeatureValuesRequest
Request message for FeaturestoreService.DeleteFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SelectEntity
Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.
SelectTimeRangeAndFeature
Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.
DeleteFeatureValuesResponse
Response message for FeaturestoreService.DeleteFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SelectEntity
Response message if the request uses the SelectEntity option.
SelectTimeRangeAndFeature
Response message if the request uses the SelectTimeRangeAndFeature option.
DeleteFeatureViewRequest
Request message for [FeatureOnlineStoreAdminService.DeleteFeatureViews][].
DeleteFeaturestoreRequest
Request message for FeaturestoreService.DeleteFeaturestore.
DeleteHyperparameterTuningJobRequest
Request message for JobService.DeleteHyperparameterTuningJob.
DeleteIndexEndpointRequest
Request message for IndexEndpointService.DeleteIndexEndpoint.
DeleteIndexRequest
Request message for IndexService.DeleteIndex.
DeleteMetadataStoreOperationMetadata
Details of operations that perform MetadataService.DeleteMetadataStore.
DeleteMetadataStoreRequest
Request message for MetadataService.DeleteMetadataStore.
DeleteModelDeploymentMonitoringJobRequest
Request message for JobService.DeleteModelDeploymentMonitoringJob.
DeleteModelRequest
Request message for ModelService.DeleteModel.
DeleteModelVersionRequest
Request message for ModelService.DeleteModelVersion.
DeleteNasJobRequest
Request message for JobService.DeleteNasJob.
DeleteNotebookRuntimeRequest
Request message for NotebookService.DeleteNotebookRuntime.
DeleteNotebookRuntimeTemplateRequest
Request message for NotebookService.DeleteNotebookRuntimeTemplate.
DeleteOperationMetadata
Details of operations that perform deletes of any entities.
DeletePersistentResourceRequest
Request message for PersistentResourceService.DeletePersistentResource.
DeletePipelineJobRequest
Request message for PipelineService.DeletePipelineJob.
DeleteSavedQueryRequest
Request message for DatasetService.DeleteSavedQuery.
DeleteScheduleRequest
Request message for ScheduleService.DeleteSchedule.
DeleteSpecialistPoolRequest
Request message for SpecialistPoolService.DeleteSpecialistPool.
DeleteStudyRequest
Request message for VizierService.DeleteStudy.
DeleteTensorboardExperimentRequest
Request message for TensorboardService.DeleteTensorboardExperiment.
DeleteTensorboardRequest
Request message for TensorboardService.DeleteTensorboard.
DeleteTensorboardRunRequest
Request message for TensorboardService.DeleteTensorboardRun.
DeleteTensorboardTimeSeriesRequest
Request message for TensorboardService.DeleteTensorboardTimeSeries.
DeleteTrainingPipelineRequest
Request message for PipelineService.DeleteTrainingPipeline.
DeleteTrialRequest
Request message for VizierService.DeleteTrial.
DeployIndexOperationMetadata
Runtime operation information for IndexEndpointService.DeployIndex.
DeployIndexRequest
Request message for IndexEndpointService.DeployIndex.
DeployIndexResponse
Response message for IndexEndpointService.DeployIndex.
DeployModelOperationMetadata
Runtime operation information for EndpointService.DeployModel.
DeployModelRequest
Request message for EndpointService.DeployModel.
TrafficSplitEntry
The abstract base class for a message.
DeployModelResponse
Response message for EndpointService.DeployModel.
DeployedIndex
A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
DeployedIndexAuthConfig
Used to set up the auth on the DeployedIndex's private endpoint.
AuthProvider
Configuration for an authentication provider, including support for
JSON Web Token
(JWT) <https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32>
__.
DeployedIndexRef
Points to a DeployedIndex.
DeployedModel
A deployment of a Model. Endpoints contain one or more DeployedModels.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DeployedModelRef
Points to a DeployedModel.
DeploymentResourcePool
A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.
DestinationFeatureSetting
DirectPredictRequest
Request message for PredictionService.DirectPredict.
DirectPredictResponse
Response message for PredictionService.DirectPredict.
DirectRawPredictRequest
Request message for PredictionService.DirectRawPredict.
DirectRawPredictResponse
Response message for PredictionService.DirectRawPredict.
DiskSpec
Represents the spec of disk options.
DoubleArray
A list of double values.
EncryptionSpec
Represents a customer-managed encryption key spec that can be applied to a top-level resource.
Endpoint
Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
LabelsEntry
The abstract base class for a message.
TrafficSplitEntry
The abstract base class for a message.
EntityIdSelector
Selector for entityId. Getting ids from the given source.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EntityType
An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.
LabelsEntry
The abstract base class for a message.
EnvVar
Represents an environment variable present in a Container or Python Module.
ErrorAnalysisAnnotation
Model error analysis for each annotation.
AttributedItem
Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.
QueryType
The query type used for finding the attributed items.
EvaluatedAnnotation
True positive, false positive, or false negative.
EvaluatedAnnotation is only available under ModelEvaluationSlice
with slice of annotationSpec
dimension.
EvaluatedAnnotationType
Describes the type of the EvaluatedAnnotation. The type is determined
EvaluatedAnnotationExplanation
Explanation result of the prediction produced by the Model.
Event
An edge describing the relationship between an Artifact and an Execution in a lineage graph.
LabelsEntry
The abstract base class for a message.
Type
Describes whether an Event's Artifact is the Execution's input or output.
Examples
Example-based explainability that returns the nearest neighbors from the provided dataset.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExampleGcsSource
The Cloud Storage input instances.
DataFormat
The format of the input example instances.
ExamplesOverride
Overrides for example-based explanations.
DataFormat
Data format enum.
ExamplesRestrictionsNamespace
Restrictions namespace for example-based explanations overrides.
Execution
Instance of a general execution.
LabelsEntry
The abstract base class for a message.
State
Describes the state of the Execution.
ExplainRequest
Request message for PredictionService.Explain.
ExplainResponse
Response message for PredictionService.Explain.
Explanation
Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.
ExplanationMetadata
Metadata describing the Model's input and output for explanation.
InputMetadata
Metadata of the input of a feature.
Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.
Encoding
Defines how a feature is encoded. Defaults to IDENTITY.
::
input = [27, 6.0, 150]
index_feature_mapping = ["age", "height", "weight"]
BAG_OF_FEATURES_SPARSE (3):
The tensor represents a bag of features where each index
maps to a feature. Zero values in the tensor indicates
feature being non-existent.
<xref uid="google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.index_feature_mapping">InputMetadata.index_feature_mapping</xref>
must be provided for this encoding. For example:
::
input = [2, 0, 5, 0, 1]
index_feature_mapping = ["a", "b", "c", "d", "e"]
INDICATOR (4):
The tensor is a list of binaries representing whether a
feature exists or not (1 indicates existence).
<xref uid="google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.index_feature_mapping">InputMetadata.index_feature_mapping</xref>
must be provided for this encoding. For example:
::
input = [1, 0, 1, 0, 1]
index_feature_mapping = ["a", "b", "c", "d", "e"]
COMBINED_EMBEDDING (5):
The tensor is encoded into a 1-dimensional array represented
by an encoded tensor.
<xref uid="google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoded_tensor_name">InputMetadata.encoded_tensor_name</xref>
must be provided for this encoding. For example:
::
input = ["This", "is", "a", "test", "."]
encoded = [0.1, 0.2, 0.3, 0.4, 0.5]
CONCAT_EMBEDDING (6):
Select this encoding when the input tensor is encoded into a
2-dimensional array represented by an encoded tensor.
<xref uid="google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoded_tensor_name">InputMetadata.encoded_tensor_name</xref>
must be provided for this encoding. The first dimension of
the encoded tensor's shape is the same as the input tensor's
shape. For example:
::
input = ["This", "is", "a", "test", "."]
encoded = [[0.1, 0.2, 0.3, 0.4, 0.5],
[0.2, 0.1, 0.4, 0.3, 0.5],
[0.5, 0.1, 0.3, 0.5, 0.4],
[0.5, 0.3, 0.1, 0.2, 0.4],
[0.4, 0.3, 0.2, 0.5, 0.1]]
FeatureValueDomain
Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained.
Visualization
Visualization configurations for image explanation.
ColorMap
The color scheme used for highlighting areas.
OverlayType
How the original image is displayed in the visualization.
Polarity
Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.
Type
Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
InputsEntry
The abstract base class for a message.
OutputMetadata
Metadata of the prediction output to be explained.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OutputsEntry
The abstract base class for a message.
ExplanationMetadataOverride
The ExplanationMetadata entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
InputMetadataOverride
The [input metadata][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata] entries to be overridden.
InputsEntry
The abstract base class for a message.
ExplanationParameters
Parameters to configure explaining for Model's predictions.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExplanationSpec
Specification of Model explanation.
ExplanationSpecOverride
The ExplanationSpec entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
ExportDataConfig
Describes what part of the Dataset is to be exported, the destination of the export and how to export.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExportUse
ExportUse indicates the usage of the exported files. It restricts file destination, format, annotations to be exported, whether to allow unannotated data to be exported and whether to clone files to temp Cloud Storage bucket.
ExportDataOperationMetadata
Runtime operation information for DatasetService.ExportData.
ExportDataRequest
Request message for DatasetService.ExportData.
ExportDataResponse
Response message for DatasetService.ExportData.
ExportFeatureValuesOperationMetadata
Details of operations that exports Features values.
ExportFeatureValuesRequest
Request message for FeaturestoreService.ExportFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FullExport
Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].
SnapshotExport
Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].
ExportFeatureValuesResponse
Response message for FeaturestoreService.ExportFeatureValues.
ExportFilterSplit
Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).
Supported only for unstructured Datasets.
ExportFractionSplit
Assigns the input data to training, validation, and test sets as per
the given fractions. Any of training_fraction
,
validation_fraction
and test_fraction
may optionally be
provided, they must sum to up to 1. If the provided ones sum to less
than 1, the remainder is assigned to sets as decided by Vertex AI.
If none of the fractions are set, by default roughly 80% of data is
used for training, 10% for validation, and 10% for test.
ExportModelOperationMetadata
Details of ModelService.ExportModel operation.
OutputInfo
Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.
ExportModelRequest
Request message for ModelService.ExportModel.
OutputConfig
Output configuration for the Model export.
ExportModelResponse
Response message of ModelService.ExportModel operation.
ExportTensorboardTimeSeriesDataRequest
Request message for TensorboardService.ExportTensorboardTimeSeriesData.
ExportTensorboardTimeSeriesDataResponse
Response message for TensorboardService.ExportTensorboardTimeSeriesData.
Feature
Feature Metadata information. For example, color is a feature that describes an apple.
LabelsEntry
The abstract base class for a message.
MonitoringStatsAnomaly
A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.
Objective
If the objective in the request is both Import Feature Analysis and Snapshot Analysis, this objective could be one of them. Otherwise, this objective should be the same as the objective in the request.
ValueType
Only applicable for Vertex AI Legacy Feature Store. An enum representing the value type of a feature.
FeatureGroup
Vertex AI Feature Group.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BigQuery
Input source type for BigQuery Tables and Views.
LabelsEntry
The abstract base class for a message.
FeatureNoiseSigma
Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.
NoiseSigmaForFeature
Noise sigma for a single feature.
FeatureOnlineStore
Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Bigtable
AutoScaling
DedicatedServingEndpoint
The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default.
LabelsEntry
The abstract base class for a message.
Optimized
Optimized storage type
State
Possible states a featureOnlineStore can have.
FeatureSelector
Selector for Features of an EntityType.
FeatureStatsAnomaly
Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.
FeatureValue
Value for a feature.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Metadata
Metadata of feature value.
FeatureValueDestination
A destination location for Feature values and format.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureValueList
Container for list of values.
FeatureView
FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BigQuerySource
FeatureRegistrySource
A Feature Registry source for features that need to be synced to Online Store.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureGroup
Features belonging to a single feature group that will be synced to Online Store.
IndexConfig
Configuration for vector indexing.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BruteForceConfig
Configuration options for using brute force search.
DistanceMeasureType
The distance measure used in nearest neighbor search.
We strongly suggest using DOT_PRODUCT_DISTANCE +
UNIT_L2_NORM instead of COSINE distance. Our algorithms have
been more optimized for DOT_PRODUCT distance which, when
combined with UNIT_L2_NORM, is mathematically equivalent to
COSINE distance and results in the same ranking.
DOT_PRODUCT_DISTANCE (3):
Dot Product Distance. Defined as a negative
of the dot product.
TreeAHConfig
Configuration options for the tree-AH algorithm.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
LabelsEntry
The abstract base class for a message.
SyncConfig
Configuration for Sync. Only one option is set.
FeatureViewDataFormat
Format of the data in the Feature View.
FeatureViewDataKey
Lookup key for a feature view.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CompositeKey
ID that is comprised from several parts (columns).
FeatureViewSync
FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.
SyncSummary
Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync.
Featurestore
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.
LabelsEntry
The abstract base class for a message.
OnlineServingConfig
OnlineServingConfig specifies the details for provisioning online serving resources.
Scaling
Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).
State
Possible states a featurestore can have.
FeaturestoreMonitoringConfig
Configuration of how features in Featurestore are monitored.
ImportFeaturesAnalysis
Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.
Baseline
Defines the baseline to do anomaly detection for feature values imported by each ImportFeatureValues operation.
State
The state defines whether to enable ImportFeature analysis.
SnapshotAnalysis
Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.
ThresholdConfig
The config for Featurestore Monitoring threshold.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FetchFeatureValuesRequest
Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.
FetchFeatureValuesResponse
Response message for FeatureOnlineStoreService.FetchFeatureValues
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureNameValuePairList
Response structure in the format of key (feature name) and (feature) value pair.
FeatureNameValuePair
Feature name & value pair.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FileData
URI based data.
FilterSplit
Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).
Supported only for unstructured Datasets.
FindNeighborsRequest
The request message for MatchService.FindNeighbors.
Query
A query to find a number of the nearest neighbors (most similar vectors) of a vector.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RRF
Parameters for RRF algorithm that combines search results.
FindNeighborsResponse
The response message for MatchService.FindNeighbors.
NearestNeighbors
Nearest neighbors for one query.
Neighbor
A neighbor of the query vector.
FractionSplit
Assigns the input data to training, validation, and test sets as per
the given fractions. Any of training_fraction
,
validation_fraction
and test_fraction
may optionally be
provided, they must sum to up to 1. If the provided ones sum to less
than 1, the remainder is assigned to sets as decided by Vertex AI.
If none of the fractions are set, by default roughly 80% of data is
used for training, 10% for validation, and 10% for test.
FunctionCall
A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values.
FunctionCallingConfig
Function calling config.
Mode
Function calling mode.
FunctionDeclaration
Structured representation of a function declaration as defined by
the OpenAPI 3.0
specification <https://spec.openapis.org/oas/v3.0.3>
__. Included in
this declaration are the function name and parameters. This
FunctionDeclaration is a representation of a block of code that can
be used as a Tool
by the model and executed by the client.
FunctionResponse
The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.
GcsDestination
The Google Cloud Storage location where the output is to be written to.
GcsSource
The Google Cloud Storage location for the input content.
GenerateContentRequest
Request message for [PredictionService.GenerateContent].
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GenerateContentResponse
Response message for [PredictionService.GenerateContent].
PromptFeedback
Content filter results for a prompt sent in the request.
BlockedReason
Blocked reason enumeration.
UsageMetadata
Usage metadata about response(s).
GenerationConfig
Generation config.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GenericOperationMetadata
Generic Metadata shared by all operations.
GenieSource
Contains information about the source of the models generated from Generative AI Studio.
GetAnnotationSpecRequest
Request message for DatasetService.GetAnnotationSpec.
GetArtifactRequest
Request message for MetadataService.GetArtifact.
GetBatchPredictionJobRequest
Request message for JobService.GetBatchPredictionJob.
GetContextRequest
Request message for MetadataService.GetContext.
GetCustomJobRequest
Request message for JobService.GetCustomJob.
GetDataLabelingJobRequest
Request message for JobService.GetDataLabelingJob.
GetDatasetRequest
Request message for DatasetService.GetDataset.
GetDatasetVersionRequest
Request message for DatasetService.GetDatasetVersion.
GetDeploymentResourcePoolRequest
Request message for GetDeploymentResourcePool method.
GetEndpointRequest
Request message for EndpointService.GetEndpoint
GetEntityTypeRequest
Request message for FeaturestoreService.GetEntityType.
GetExecutionRequest
Request message for MetadataService.GetExecution.
GetFeatureGroupRequest
Request message for FeatureRegistryService.GetFeatureGroup.
GetFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureOnlineStore.
GetFeatureRequest
Request message for FeaturestoreService.GetFeature. Request message for FeatureRegistryService.GetFeature.
GetFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureView.
GetFeatureViewSyncRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureViewSync.
GetFeaturestoreRequest
Request message for FeaturestoreService.GetFeaturestore.
GetHyperparameterTuningJobRequest
Request message for JobService.GetHyperparameterTuningJob.
GetIndexEndpointRequest
Request message for IndexEndpointService.GetIndexEndpoint
GetIndexRequest
Request message for IndexService.GetIndex
GetMetadataSchemaRequest
Request message for MetadataService.GetMetadataSchema.
GetMetadataStoreRequest
Request message for MetadataService.GetMetadataStore.
GetModelDeploymentMonitoringJobRequest
Request message for JobService.GetModelDeploymentMonitoringJob.
GetModelEvaluationRequest
Request message for ModelService.GetModelEvaluation.
GetModelEvaluationSliceRequest
Request message for ModelService.GetModelEvaluationSlice.
GetModelRequest
Request message for ModelService.GetModel.
GetNasJobRequest
Request message for JobService.GetNasJob.
GetNasTrialDetailRequest
Request message for JobService.GetNasTrialDetail.
GetNotebookRuntimeRequest
Request message for NotebookService.GetNotebookRuntime
GetNotebookRuntimeTemplateRequest
Request message for NotebookService.GetNotebookRuntimeTemplate
GetPersistentResourceRequest
Request message for PersistentResourceService.GetPersistentResource.
GetPipelineJobRequest
Request message for PipelineService.GetPipelineJob.
GetPublisherModelRequest
Request message for ModelGardenService.GetPublisherModel
GetScheduleRequest
Request message for ScheduleService.GetSchedule.
GetSpecialistPoolRequest
Request message for SpecialistPoolService.GetSpecialistPool.
GetStudyRequest
Request message for VizierService.GetStudy.
GetTensorboardExperimentRequest
Request message for TensorboardService.GetTensorboardExperiment.
GetTensorboardRequest
Request message for TensorboardService.GetTensorboard.
GetTensorboardRunRequest
Request message for TensorboardService.GetTensorboardRun.
GetTensorboardTimeSeriesRequest
Request message for TensorboardService.GetTensorboardTimeSeries.
GetTrainingPipelineRequest
Request message for PipelineService.GetTrainingPipeline.
GetTrialRequest
Request message for VizierService.GetTrial.
GetTuningJobRequest
Request message for GenAiTuningService.GetTuningJob.
GoogleSearchRetrieval
Tool to retrieve public web data for grounding, powered by Google.
GroundingMetadata
Metadata returned to client when grounding is enabled.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
HarmCategory
Harm categories that will block the content.
HyperparameterTuningJob
Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
LabelsEntry
The abstract base class for a message.
IdMatcher
Matcher for Features of an EntityType by Feature ID.
ImportDataConfig
Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AnnotationLabelsEntry
The abstract base class for a message.
DataItemLabelsEntry
The abstract base class for a message.
ImportDataOperationMetadata
Runtime operation information for DatasetService.ImportData.
ImportDataRequest
Request message for DatasetService.ImportData.
ImportDataResponse
Response message for DatasetService.ImportData.
ImportFeatureValuesOperationMetadata
Details of operations that perform import Feature values.
ImportFeatureValuesRequest
Request message for FeaturestoreService.ImportFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureSpec
Defines the Feature value(s) to import.
ImportFeatureValuesResponse
Response message for FeaturestoreService.ImportFeatureValues.
ImportModelEvaluationRequest
Request message for ModelService.ImportModelEvaluation
Index
A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.
IndexUpdateMethod
The update method of an Index.
LabelsEntry
The abstract base class for a message.
IndexDatapoint
A datapoint of Index.
CrowdingTag
Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.
NumericRestriction
This field allows restricts to be based on numeric comparisons rather than categorical tokens.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Operator
Which comparison operator to use. Should be specified for queries only; specifying this for a datapoint is an error.
Datapoints for which Operator is true relative to the query's Value field will be allowlisted.
Restriction
Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).
SparseEmbedding
Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions.
IndexEndpoint
Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
LabelsEntry
The abstract base class for a message.
IndexPrivateEndpoints
IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.
IndexStats
Stats of the Index.
InputDataConfig
Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Int64Array
A list of int64 values.
IntegratedGradientsAttribution
An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
JobState
Describes the state of a job.
LargeModelReference
Contains information about the Large Model.
LineageSubgraph
A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
ListAnnotationsRequest
Request message for DatasetService.ListAnnotations.
ListAnnotationsResponse
Response message for DatasetService.ListAnnotations.
ListArtifactsRequest
Request message for MetadataService.ListArtifacts.
ListArtifactsResponse
Response message for MetadataService.ListArtifacts.
ListBatchPredictionJobsRequest
Request message for JobService.ListBatchPredictionJobs.
ListBatchPredictionJobsResponse
Response message for JobService.ListBatchPredictionJobs
ListContextsRequest
Request message for MetadataService.ListContexts
ListContextsResponse
Response message for MetadataService.ListContexts.
ListCustomJobsRequest
Request message for JobService.ListCustomJobs.
ListCustomJobsResponse
Response message for JobService.ListCustomJobs
ListDataItemsRequest
Request message for DatasetService.ListDataItems.
ListDataItemsResponse
Response message for DatasetService.ListDataItems.
ListDataLabelingJobsRequest
Request message for JobService.ListDataLabelingJobs.
ListDataLabelingJobsResponse
Response message for JobService.ListDataLabelingJobs.
ListDatasetVersionsRequest
Request message for DatasetService.ListDatasetVersions.
ListDatasetVersionsResponse
Response message for DatasetService.ListDatasetVersions.
ListDatasetsRequest
Request message for DatasetService.ListDatasets.
ListDatasetsResponse
Response message for DatasetService.ListDatasets.
ListDeploymentResourcePoolsRequest
Request message for ListDeploymentResourcePools method.
ListDeploymentResourcePoolsResponse
Response message for ListDeploymentResourcePools method.
ListEndpointsRequest
Request message for EndpointService.ListEndpoints.
ListEndpointsResponse
Response message for EndpointService.ListEndpoints.
ListEntityTypesRequest
Request message for FeaturestoreService.ListEntityTypes.
ListEntityTypesResponse
Response message for FeaturestoreService.ListEntityTypes.
ListExecutionsRequest
Request message for MetadataService.ListExecutions.
ListExecutionsResponse
Response message for MetadataService.ListExecutions.
ListFeatureGroupsRequest
Request message for FeatureRegistryService.ListFeatureGroups.
ListFeatureGroupsResponse
Response message for FeatureRegistryService.ListFeatureGroups.
ListFeatureOnlineStoresRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.
ListFeatureOnlineStoresResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.
ListFeatureViewSyncsRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.
ListFeatureViewSyncsResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.
ListFeatureViewsRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureViews.
ListFeatureViewsResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureViews.
ListFeaturesRequest
Request message for FeaturestoreService.ListFeatures. Request message for FeatureRegistryService.ListFeatures.
ListFeaturesResponse
Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.
ListFeaturestoresRequest
Request message for FeaturestoreService.ListFeaturestores.
ListFeaturestoresResponse
Response message for FeaturestoreService.ListFeaturestores.
ListHyperparameterTuningJobsRequest
Request message for JobService.ListHyperparameterTuningJobs.
ListHyperparameterTuningJobsResponse
Response message for JobService.ListHyperparameterTuningJobs
ListIndexEndpointsRequest
Request message for IndexEndpointService.ListIndexEndpoints.
ListIndexEndpointsResponse
Response message for IndexEndpointService.ListIndexEndpoints.
ListIndexesRequest
Request message for IndexService.ListIndexes.
ListIndexesResponse
Response message for IndexService.ListIndexes.
ListMetadataSchemasRequest
Request message for MetadataService.ListMetadataSchemas.
ListMetadataSchemasResponse
Response message for MetadataService.ListMetadataSchemas.
ListMetadataStoresRequest
Request message for MetadataService.ListMetadataStores.
ListMetadataStoresResponse
Response message for MetadataService.ListMetadataStores.
ListModelDeploymentMonitoringJobsRequest
Request message for JobService.ListModelDeploymentMonitoringJobs.
ListModelDeploymentMonitoringJobsResponse
Response message for JobService.ListModelDeploymentMonitoringJobs.
ListModelEvaluationSlicesRequest
Request message for ModelService.ListModelEvaluationSlices.
ListModelEvaluationSlicesResponse
Response message for ModelService.ListModelEvaluationSlices.
ListModelEvaluationsRequest
Request message for ModelService.ListModelEvaluations.
ListModelEvaluationsResponse
Response message for ModelService.ListModelEvaluations.
ListModelVersionsRequest
Request message for ModelService.ListModelVersions.
ListModelVersionsResponse
Response message for ModelService.ListModelVersions
ListModelsRequest
Request message for ModelService.ListModels.
ListModelsResponse
Response message for ModelService.ListModels
ListNasJobsRequest
Request message for JobService.ListNasJobs.
ListNasJobsResponse
Response message for JobService.ListNasJobs
ListNasTrialDetailsRequest
Request message for JobService.ListNasTrialDetails.
ListNasTrialDetailsResponse
Response message for JobService.ListNasTrialDetails
ListNotebookRuntimeTemplatesRequest
Request message for NotebookService.ListNotebookRuntimeTemplates.
ListNotebookRuntimeTemplatesResponse
Response message for NotebookService.ListNotebookRuntimeTemplates.
ListNotebookRuntimesRequest
Request message for NotebookService.ListNotebookRuntimes.
ListNotebookRuntimesResponse
Response message for NotebookService.ListNotebookRuntimes.
ListOptimalTrialsRequest
Request message for VizierService.ListOptimalTrials.
ListOptimalTrialsResponse
Response message for VizierService.ListOptimalTrials.
ListPersistentResourcesRequest
Request message for [PersistentResourceService.ListPersistentResource][].
ListPersistentResourcesResponse
Response message for PersistentResourceService.ListPersistentResources
ListPipelineJobsRequest
Request message for PipelineService.ListPipelineJobs.
ListPipelineJobsResponse
Response message for PipelineService.ListPipelineJobs
ListSavedQueriesRequest
Request message for DatasetService.ListSavedQueries.
ListSavedQueriesResponse
Response message for DatasetService.ListSavedQueries.
ListSchedulesRequest
Request message for ScheduleService.ListSchedules.
ListSchedulesResponse
Response message for ScheduleService.ListSchedules
ListSpecialistPoolsRequest
Request message for SpecialistPoolService.ListSpecialistPools.
ListSpecialistPoolsResponse
Response message for SpecialistPoolService.ListSpecialistPools.
ListStudiesRequest
Request message for VizierService.ListStudies.
ListStudiesResponse
Response message for VizierService.ListStudies.
ListTensorboardExperimentsRequest
Request message for TensorboardService.ListTensorboardExperiments.
ListTensorboardExperimentsResponse
Response message for TensorboardService.ListTensorboardExperiments.
ListTensorboardRunsRequest
Request message for TensorboardService.ListTensorboardRuns.
ListTensorboardRunsResponse
Response message for TensorboardService.ListTensorboardRuns.
ListTensorboardTimeSeriesRequest
Request message for TensorboardService.ListTensorboardTimeSeries.
ListTensorboardTimeSeriesResponse
Response message for TensorboardService.ListTensorboardTimeSeries.
ListTensorboardsRequest
Request message for TensorboardService.ListTensorboards.
ListTensorboardsResponse
Response message for TensorboardService.ListTensorboards.
ListTrainingPipelinesRequest
Request message for PipelineService.ListTrainingPipelines.
ListTrainingPipelinesResponse
Response message for PipelineService.ListTrainingPipelines
ListTrialsRequest
Request message for VizierService.ListTrials.
ListTrialsResponse
Response message for VizierService.ListTrials.
ListTuningJobsRequest
Request message for GenAiTuningService.ListTuningJobs.
ListTuningJobsResponse
Response message for GenAiTuningService.ListTuningJobs
LookupStudyRequest
Request message for VizierService.LookupStudy.
MachineSpec
Specification of a single machine.
ManualBatchTuningParameters
Manual batch tuning parameters.
Measurement
A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
Metric
A message representing a metric in the measurement.
MergeVersionAliasesRequest
Request message for ModelService.MergeVersionAliases.
MetadataSchema
Instance of a general MetadataSchema.
MetadataSchemaType
Describes the type of the MetadataSchema.
MetadataStore
Instance of a metadata store. Contains a set of metadata that can be queried.
DataplexConfig
Represents Dataplex integration settings.
MetadataStoreState
Represents state information for a MetadataStore.
MigratableResource
Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutomlDataset
Represents one Dataset in automl.googleapis.com.
AutomlModel
Represents one Model in automl.googleapis.com.
DataLabelingDataset
Represents one Dataset in datalabeling.googleapis.com.
DataLabelingAnnotatedDataset
Represents one AnnotatedDataset in datalabeling.googleapis.com.
MlEngineModelVersion
Represents one model Version in ml.googleapis.com.
MigrateResourceRequest
Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MigrateAutomlDatasetConfig
Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.
MigrateAutomlModelConfig
Config for migrating Model in automl.googleapis.com to Vertex AI's Model.
MigrateDataLabelingDatasetConfig
Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.
MigrateDataLabelingAnnotatedDatasetConfig
Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.
MigrateMlEngineModelVersionConfig
Config for migrating version in ml.googleapis.com to Vertex AI's Model.
MigrateResourceResponse
Describes a successfully migrated resource.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Model
A trained machine learning Model.
BaseModelSource
User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DataStats
Stats of data used for train or evaluate the Model.
DeploymentResourcesType
Identifies a type of Model's prediction resources.
ExportFormat
Represents export format supported by the Model. All formats export to Google Cloud Storage.
ExportableContent
The Model content that can be exported.
LabelsEntry
The abstract base class for a message.
OriginalModelInfo
Contains information about the original Model if this Model is a copy.
ModelContainerSpec
Specification of a container for serving predictions. Some fields in
this message correspond to fields in the Kubernetes Container v1
core
specification <https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core>
__.
ModelDeploymentMonitoringBigQueryTable
ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.
LogSource
Indicates where does the log come from.
LogType
Indicates what type of traffic does the log belong to.
ModelDeploymentMonitoringJob
Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.
LabelsEntry
The abstract base class for a message.
LatestMonitoringPipelineMetadata
All metadata of most recent monitoring pipelines.
MonitoringScheduleState
The state to Specify the monitoring pipeline.
ModelDeploymentMonitoringObjectiveConfig
ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.
ModelDeploymentMonitoringObjectiveType
The Model Monitoring Objective types.
ModelDeploymentMonitoringScheduleConfig
The config for scheduling monitoring job.
ModelEvaluation
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
ModelEvaluationExplanationSpec
ModelEvaluationSlice
A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.
Slice
Definition of a slice.
SliceSpec
Specification for how the data should be sliced.
ConfigsEntry
The abstract base class for a message.
Range
A range of values for slice(s). low
is inclusive, high
is
exclusive.
SliceConfig
Specification message containing the config for this SliceSpec. When
kind
is selected as value
and/or range
, only a single
slice will be computed. When all_values
is present, a separate
slice will be computed for each possible label/value for the
corresponding key in config
. Examples, with feature zip_code
with values 12345, 23334, 88888 and feature country with values
"US", "Canada", "Mexico" in the dataset:
Example 1:
::
{
"zip_code": { "value": { "float_value": 12345.0 } }
}
A single slice for any data with zip_code 12345 in the dataset.
Example 2:
::
{
"zip_code": { "range": { "low": 12345, "high": 20000 } }
}
A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice.
Example 3:
::
{
"zip_code": { "range": { "low": 10000, "high": 20000 } },
"country": { "value": { "string_value": "US" } }
}
A single slice containing data where the zip_codes between 10000 and 20000 has the country "US". For this example, data with the zip_code of 12345 and country "US" will be in this slice.
Example 4:
::
{ "country": {"all_values": { "value": true } } }
Three slices are computed, one for each unique country in the dataset.
Example 5:
::
{
"country": { "all_values": { "value": true } },
"zip_code": { "value": { "float_value": 12345.0 } }
}
Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country "US" will be in one slice, zip_code 12345 and country "Canada" in another slice, and zip_code 12345 and country "Mexico" in another slice, totaling 3 slices.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Value
Single value that supports strings and floats.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelExplanation
Aggregated explanation metrics for a Model over a set of instances.
ModelGardenSource
Contains information about the source of the models generated from Model Garden.
ModelMonitoringAlertConfig
The alert config for model monitoring.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EmailAlertConfig
The config for email alert.
ModelMonitoringObjectiveConfig
The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.
ExplanationConfig
The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.
ExplanationBaseline
Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PredictionFormat
The storage format of the predictions generated BatchPrediction job.
PredictionDriftDetectionConfig
The config for Prediction data drift detection.
AttributionScoreDriftThresholdsEntry
The abstract base class for a message.
DriftThresholdsEntry
The abstract base class for a message.
TrainingDataset
Training Dataset information.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TrainingPredictionSkewDetectionConfig
The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.
AttributionScoreSkewThresholdsEntry
The abstract base class for a message.
SkewThresholdsEntry
The abstract base class for a message.
ModelMonitoringStatsAnomalies
Statistics and anomalies generated by Model Monitoring.
FeatureHistoricStatsAnomalies
Historical Stats (and Anomalies) for a specific Feature.
ModelSourceInfo
Detail description of the source information of the model.
ModelSourceType
Source of the model. Different from objective
field, this
ModelSourceType
enum indicates the source from which the model
was accessed or obtained, whereas the objective
indicates the
overall aim or function of this model.
MutateDeployedIndexOperationMetadata
Runtime operation information for IndexEndpointService.MutateDeployedIndex.
MutateDeployedIndexRequest
Request message for IndexEndpointService.MutateDeployedIndex.
MutateDeployedIndexResponse
Response message for IndexEndpointService.MutateDeployedIndex.
MutateDeployedModelOperationMetadata
Runtime operation information for EndpointService.MutateDeployedModel.
MutateDeployedModelRequest
Request message for EndpointService.MutateDeployedModel.
MutateDeployedModelResponse
Response message for EndpointService.MutateDeployedModel.
NasJob
Represents a Neural Architecture Search (NAS) job.
LabelsEntry
The abstract base class for a message.
NasJobOutput
Represents a uCAIP NasJob output.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MultiTrialJobOutput
The output of a multi-trial Neural Architecture Search (NAS) jobs.
NasJobSpec
Represents the spec of a NasJob.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MultiTrialAlgorithmSpec
The spec of multi-trial Neural Architecture Search (NAS).
MetricSpec
Represents a metric to optimize.
GoalType
The available types of optimization goals.
MultiTrialAlgorithm
The available types of multi-trial algorithms.
SearchTrialSpec
Represent spec for search trials.
TrainTrialSpec
Represent spec for train trials.
NasTrial
Represents a uCAIP NasJob trial.
State
Describes a NasTrial state.
NasTrialDetail
Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.
NearestNeighborQuery
A query to find a number of similar entities.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Embedding
The embedding vector.
Parameters
Parameters that can be overrided in each query to tune query latency and recall.
StringFilter
String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.
NearestNeighborSearchOperationMetadata
Runtime operation metadata with regard to Matching Engine Index.
ContentValidationStats
RecordError
RecordErrorType
NearestNeighbors
Nearest neighbors for one query.
Neighbor
A neighbor of the query vector.
Neighbor
Neighbors for example-based explanations.
NetworkSpec
Network spec.
NfsMount
Represents a mount configuration for Network File System (NFS) to mount.
NotebookEucConfig
The euc configuration of NotebookRuntimeTemplate.
NotebookIdleShutdownConfig
The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.
NotebookRuntime
A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.
HealthState
The substate of the NotebookRuntime to display health information.
LabelsEntry
The abstract base class for a message.
RuntimeState
The substate of the NotebookRuntime to display state of runtime. The resource of NotebookRuntime is in ACTIVE state for these sub state.
NotebookRuntimeTemplate
A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.
LabelsEntry
The abstract base class for a message.
NotebookRuntimeTemplateRef
Points to a NotebookRuntimeTemplateRef.
NotebookRuntimeType
Represents a notebook runtime type.
Part
A datatype containing media that is part of a multi-part Content
message.
A Part
consists of data which has an associated datatype. A
Part
can only contain one of the accepted types in
Part.data
.
A Part
must have a fixed IANA MIME type identifying the type and
subtype of the media if inline_data
or file_data
field is
filled with raw bytes.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PauseModelDeploymentMonitoringJobRequest
Request message for JobService.PauseModelDeploymentMonitoringJob.
PauseScheduleRequest
Request message for ScheduleService.PauseSchedule.
PersistentDiskSpec
Represents the spec of [persistent disk][https://cloud.google.com/compute/docs/disks/persistent-disks] options.
PersistentResource
Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.
LabelsEntry
The abstract base class for a message.
State
Describes the PersistentResource state.
PipelineFailurePolicy
Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
PipelineJob
An instance of a machine learning PipelineJob.
LabelsEntry
The abstract base class for a message.
RuntimeConfig
The runtime config of a PipelineJob.
InputArtifact
The type of an input artifact.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
InputArtifactsEntry
The abstract base class for a message.
ParameterValuesEntry
The abstract base class for a message.
ParametersEntry
The abstract base class for a message.
PipelineJobDetail
The runtime detail of PipelineJob.
PipelineState
Describes the state of a pipeline.
PipelineTaskDetail
The runtime detail of a task execution.
ArtifactList
A list of artifact metadata.
InputsEntry
The abstract base class for a message.
OutputsEntry
The abstract base class for a message.
PipelineTaskStatus
A single record of the task status.
State
Specifies state of TaskExecution
PipelineTaskExecutorDetail
The runtime detail of a pipeline executor.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ContainerDetail
The detail of a container execution. It contains the job names of the lifecycle of a container execution.
CustomJobDetail
The detailed info for a custom job executor.
PipelineTemplateMetadata
Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.
Port
Represents a network port in a container.
PredefinedSplit
Assigns input data to training, validation, and test sets based on the value of a provided key.
Supported only for tabular Datasets.
PredictRequest
Request message for PredictionService.Predict.
PredictRequestResponseLoggingConfig
Configuration for logging request-response to a BigQuery table.
PredictResponse
Response message for PredictionService.Predict.
PredictSchemata
Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.
Presets
Preset configuration for example-based explanations
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Modality
Preset option controlling parameters for different modalities
Query
Preset option controlling parameters for query speed-precision trade-off
PrivateEndpoints
PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.
PrivateServiceConnectConfig
Represents configuration for private service connect.
Probe
Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExecAction
ExecAction specifies a command to execute.
PscAutomatedEndpoints
PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.
PublisherModel
A Model Garden Publisher Model.
CallToAction
Actions could take on this Publisher Model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Deploy
Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DeployMetadata
Metadata information about the deployment for managing deployment config.
LabelsEntry
The abstract base class for a message.
DeployGke
Configurations for PublisherModel GKE deployment
OpenFineTuningPipelines
Open fine tuning pipelines.
OpenNotebooks
Open notebooks.
RegionalResourceReferences
The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc..
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ReferencesEntry
The abstract base class for a message.
ViewRestApi
Rest API docs.
Documentation
A named piece of documentation.
LaunchStage
An enum representing the launch stage of a PublisherModel.
OpenSourceCategory
An enum representing the open source category of a PublisherModel.
ResourceReference
Reference to a resource.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VersionState
An enum representing the state of the PublicModelVersion.
PublisherModelView
View enumeration of PublisherModel.
PurgeArtifactsMetadata
Details of operations that perform MetadataService.PurgeArtifacts.
PurgeArtifactsRequest
Request message for MetadataService.PurgeArtifacts.
PurgeArtifactsResponse
Response message for MetadataService.PurgeArtifacts.
PurgeContextsMetadata
Details of operations that perform MetadataService.PurgeContexts.
PurgeContextsRequest
Request message for MetadataService.PurgeContexts.
PurgeContextsResponse
Response message for MetadataService.PurgeContexts.
PurgeExecutionsMetadata
Details of operations that perform MetadataService.PurgeExecutions.
PurgeExecutionsRequest
Request message for MetadataService.PurgeExecutions.
PurgeExecutionsResponse
Response message for MetadataService.PurgeExecutions.
PythonPackageSpec
The spec of a Python packaged code.
QueryArtifactLineageSubgraphRequest
Request message for MetadataService.QueryArtifactLineageSubgraph.
QueryContextLineageSubgraphRequest
Request message for MetadataService.QueryContextLineageSubgraph.
QueryDeployedModelsRequest
Request message for QueryDeployedModels method.
QueryDeployedModelsResponse
Response message for QueryDeployedModels method.
QueryExecutionInputsAndOutputsRequest
Request message for MetadataService.QueryExecutionInputsAndOutputs.
RawPredictRequest
Request message for PredictionService.RawPredict.
RayMetricSpec
Configuration for the Ray metrics.
RaySpec
Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.
ResourcePoolImagesEntry
The abstract base class for a message.
ReadFeatureValuesRequest
Request message for FeaturestoreOnlineServingService.ReadFeatureValues.
ReadFeatureValuesResponse
Response message for FeaturestoreOnlineServingService.ReadFeatureValues.
EntityView
Entity view with Feature values.
Data
Container to hold value(s), successive in time, for one Feature from the request.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureDescriptor
Metadata for requested Features.
Header
Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features.
ReadIndexDatapointsRequest
The request message for MatchService.ReadIndexDatapoints.
ReadIndexDatapointsResponse
The response message for MatchService.ReadIndexDatapoints.
ReadTensorboardBlobDataRequest
Request message for TensorboardService.ReadTensorboardBlobData.
ReadTensorboardBlobDataResponse
Response message for TensorboardService.ReadTensorboardBlobData.
ReadTensorboardSizeRequest
Request message for TensorboardService.ReadTensorboardSize.
ReadTensorboardSizeResponse
Response message for TensorboardService.ReadTensorboardSize.
ReadTensorboardTimeSeriesDataRequest
Request message for TensorboardService.ReadTensorboardTimeSeriesData.
ReadTensorboardTimeSeriesDataResponse
Response message for TensorboardService.ReadTensorboardTimeSeriesData.
ReadTensorboardUsageRequest
Request message for TensorboardService.ReadTensorboardUsage.
ReadTensorboardUsageResponse
Response message for TensorboardService.ReadTensorboardUsage.
MonthlyUsageDataEntry
The abstract base class for a message.
PerMonthUsageData
Per month usage data
PerUserUsageData
Per user usage data.
RebootPersistentResourceOperationMetadata
Details of operations that perform reboot PersistentResource.
RebootPersistentResourceRequest
Request message for PersistentResourceService.RebootPersistentResource.
RemoveContextChildrenRequest
Request message for [MetadataService.DeleteContextChildrenRequest][].
RemoveContextChildrenResponse
Response message for MetadataService.RemoveContextChildren.
RemoveDatapointsRequest
Request message for IndexService.RemoveDatapoints
RemoveDatapointsResponse
Response message for IndexService.RemoveDatapoints
ResourcePool
Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutoscalingSpec
The min/max number of replicas allowed if enabling autoscaling
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ResourceRuntime
Persistent Cluster runtime information as output
AccessUrisEntry
The abstract base class for a message.
ResourceRuntimeSpec
Configuration for the runtime on a PersistentResource instance, including but not limited to:
- Service accounts used to run the workloads.
- Whether to make it a dedicated Ray Cluster.
ResourcesConsumed
Statistics information about resource consumption.
RestoreDatasetVersionOperationMetadata
Runtime operation information for DatasetService.RestoreDatasetVersion.
RestoreDatasetVersionRequest
Request message for DatasetService.RestoreDatasetVersion.
ResumeModelDeploymentMonitoringJobRequest
Request message for JobService.ResumeModelDeploymentMonitoringJob.
ResumeScheduleRequest
Request message for ScheduleService.ResumeSchedule.
Retrieval
Defines a retrieval tool that model can call to access external knowledge.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SafetyRating
Safety rating corresponding to the generated content.
HarmProbability
Harm probability levels in the content.
HarmSeverity
Harm severity levels.
SafetySetting
Safety settings.
HarmBlockMethod
Probability vs severity.
HarmBlockThreshold
Probability based thresholds levels for blocking.
SampleConfig
Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SampleStrategy
Sample strategy decides which subset of DataItems should be selected for human labeling in every batch.
SampledShapleyAttribution
An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
SamplingStrategy
Sampling Strategy for logging, can be for both training and prediction dataset.
RandomSampleConfig
Requests are randomly selected.
SavedQuery
A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
Scalar
One point viewable on a scalar metric plot.
Schedule
An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RunResponse
Status of a scheduled run.
State
Possible state of the schedule.
Scheduling
All parameters related to queuing and scheduling of custom jobs.
Schema
Schema is used to define the format of input/output data. Represents
a select subset of an OpenAPI 3.0 schema
object <https://spec.openapis.org/oas/v3.0.3#schema>
__. More fields
may be added in the future as needed.
PropertiesEntry
The abstract base class for a message.
SearchDataItemsRequest
Request message for DatasetService.SearchDataItems.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OrderByAnnotation
Expression that allows ranking results based on annotation's property.
SearchDataItemsResponse
Response message for DatasetService.SearchDataItems.
SearchEntryPoint
Google search entry point.
SearchFeaturesRequest
Request message for FeaturestoreService.SearchFeatures.
SearchFeaturesResponse
Response message for FeaturestoreService.SearchFeatures.
SearchMigratableResourcesRequest
Request message for MigrationService.SearchMigratableResources.
SearchMigratableResourcesResponse
Response message for MigrationService.SearchMigratableResources.
SearchModelDeploymentMonitoringStatsAnomaliesRequest
Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.
StatsAnomaliesObjective
Stats requested for specific objective.
SearchModelDeploymentMonitoringStatsAnomaliesResponse
Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.
SearchNearestEntitiesRequest
The request message for FeatureOnlineStoreService.SearchNearestEntities.
SearchNearestEntitiesResponse
Response message for FeatureOnlineStoreService.SearchNearestEntities
ServiceAccountSpec
Configuration for the use of custom service account to run the workloads.
ShieldedVmConfig
A set of Shielded Instance options. See Images using supported
Shielded VM
features <https://cloud.google.com/compute/docs/instances/modifying-shielded-vm>
__.
SmoothGradConfig
Config for SmoothGrad approximation of gradients.
When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details:
https://arxiv.org/pdf/1706.03825.pdf
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SpecialistPool
SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.
StartNotebookRuntimeOperationMetadata
Metadata information for NotebookService.StartNotebookRuntime.
StartNotebookRuntimeRequest
Request message for NotebookService.StartNotebookRuntime.
StartNotebookRuntimeResponse
Response message for NotebookService.StartNotebookRuntime.
StopTrialRequest
Request message for VizierService.StopTrial.
StratifiedSplit
Assigns input data to the training, validation, and test sets so
that the distribution of values found in the categorical column (as
specified by the key
field) is mirrored within each split. The
fraction values determine the relative sizes of the splits.
For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C".
Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned.
Supported only for tabular Datasets.
StreamDirectPredictRequest
Request message for PredictionService.StreamDirectPredict.
The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
StreamDirectPredictResponse
Response message for PredictionService.StreamDirectPredict.
StreamDirectRawPredictRequest
Request message for PredictionService.StreamDirectRawPredict.
The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
StreamDirectRawPredictResponse
Response message for PredictionService.StreamDirectRawPredict.
StreamRawPredictRequest
Request message for PredictionService.StreamRawPredict.
StreamingPredictRequest
Request message for PredictionService.StreamingPredict.
The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
StreamingPredictResponse
Response message for PredictionService.StreamingPredict.
StreamingRawPredictRequest
Request message for PredictionService.StreamingRawPredict.
The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
StreamingRawPredictResponse
Response message for PredictionService.StreamingRawPredict.
StreamingReadFeatureValuesRequest
Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].
StringArray
A list of string values.
StructFieldValue
One field of a Struct (or object) type feature value.
StructValue
Struct (or object) type feature value.
Study
A message representing a Study.
State
Describes the Study state.
StudySpec
Represents specification of a Study.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Algorithm
The available search algorithms for the Study.
ConvexAutomatedStoppingSpec
Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DecayCurveAutomatedStoppingSpec
The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.
MeasurementSelectionType
This indicates which measurement to use if/when the service automatically selects the final measurement from previously reported intermediate measurements. Choose this based on two considerations: A) Do you expect your measurements to monotonically improve? If so, choose LAST_MEASUREMENT. On the other hand, if you're in a situation where your system can "over-train" and you expect the performance to get better for a while but then start declining, choose BEST_MEASUREMENT. B) Are your measurements significantly noisy and/or irreproducible? If so, BEST_MEASUREMENT will tend to be over-optimistic, and it may be better to choose LAST_MEASUREMENT. If both or neither of (A) and (B) apply, it doesn't matter which selection type is chosen.
MedianAutomatedStoppingSpec
The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.
MetricSpec
Represents a metric to optimize.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GoalType
The available types of optimization goals.
SafetyMetricConfig
Used in safe optimization to specify threshold levels and risk tolerance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ObservationNoise
Describes the noise level of the repeated observations.
"Noisy" means that the repeated observations with the same Trial parameters may lead to different metric evaluations.
ParameterSpec
Represents a single parameter to optimize.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CategoricalValueSpec
Value specification for a parameter in CATEGORICAL
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ConditionalParameterSpec
Represents a parameter spec with condition from its parent parameter.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CategoricalValueCondition
Represents the spec to match categorical values from parent parameter.
DiscreteValueCondition
Represents the spec to match discrete values from parent parameter.
IntValueCondition
Represents the spec to match integer values from parent parameter.
DiscreteValueSpec
Value specification for a parameter in DISCRETE
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DoubleValueSpec
Value specification for a parameter in DOUBLE
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
IntegerValueSpec
Value specification for a parameter in INTEGER
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ScaleType
The type of scaling that should be applied to this parameter.
StudyStoppingConfig
The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.
StudyTimeConstraint
Time-based Constraint for Study
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SuggestTrialsMetadata
Details of operations that perform Trials suggestion.
SuggestTrialsRequest
Request message for VizierService.SuggestTrials.
SuggestTrialsResponse
Response message for VizierService.SuggestTrials.
SupervisedHyperParameters
Hyperparameters for SFT.
AdapterSize
Supported adapter sizes for tuning.
SupervisedTuningDataStats
Tuning data statistics for Supervised Tuning.
SupervisedTuningDatasetDistribution
Dataset distribution for Supervised Tuning.
DatasetBucket
Dataset bucket used to create a histogram for the distribution given a population of values.
SupervisedTuningSpec
Tuning Spec for Supervised Tuning.
SyncFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.SyncFeatureView.
SyncFeatureViewResponse
Respose message for FeatureOnlineStoreAdminService.SyncFeatureView.
TFRecordDestination
The storage details for TFRecord output content.
Tensor
A tensor value type.
DataType
Data type of the tensor.
StructValEntry
The abstract base class for a message.
Tensorboard
Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.
LabelsEntry
The abstract base class for a message.
TensorboardBlob
One blob (e.g, image, graph) viewable on a blob metric plot.
TensorboardBlobSequence
One point viewable on a blob metric plot, but mostly just a wrapper
message to work around repeated fields can't be used directly within
oneof
fields.
TensorboardExperiment
A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.
LabelsEntry
The abstract base class for a message.
TensorboardRun
TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
LabelsEntry
The abstract base class for a message.
TensorboardTensor
One point viewable on a tensor metric plot.
TensorboardTimeSeries
TensorboardTimeSeries maps to times series produced in training runs
Metadata
Describes metadata for a TensorboardTimeSeries.
ValueType
An enum representing the value type of a TensorboardTimeSeries.
ThresholdConfig
The config for feature monitoring threshold.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TimeSeriesData
All the data stored in a TensorboardTimeSeries.
TimeSeriesDataPoint
A TensorboardTimeSeries data point.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TimestampSplit
Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set.
Supported only for tabular Datasets.
TokensInfo
Tokens info with a list of tokens and the corresponding list of token ids.
Tool
Tool details that the model may use to generate response.
A Tool
is a piece of code that enables the system to interact
with external systems to perform an action, or set of actions,
outside of knowledge and scope of the model. A Tool object should
contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval
or GoogleSearchRetrieval).
ToolConfig
Tool config. This config is shared for all tools provided in the request.
TrainingConfig
CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
TrainingPipeline
The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.
LabelsEntry
The abstract base class for a message.
Trial
A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.
Parameter
A message representing a parameter to be tuned.
State
Describes a Trial state.
WebAccessUrisEntry
The abstract base class for a message.
TrialContext
Next ID: 3
TunedModel
The Model Registry Model and Online Prediction Endpoint assiociated with this TuningJob.
TuningDataStats
The tuning data statistic values for TuningJob.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TuningJob
Represents a TuningJob that runs with Google owned models.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
LabelsEntry
The abstract base class for a message.
Type
Type contains the list of OpenAPI data types as defined by https://swagger.io/docs/specification/data-models/data-types/
UndeployIndexOperationMetadata
Runtime operation information for IndexEndpointService.UndeployIndex.
UndeployIndexRequest
Request message for IndexEndpointService.UndeployIndex.
UndeployIndexResponse
Response message for IndexEndpointService.UndeployIndex.
UndeployModelOperationMetadata
Runtime operation information for EndpointService.UndeployModel.
UndeployModelRequest
Request message for EndpointService.UndeployModel.
TrafficSplitEntry
The abstract base class for a message.
UndeployModelResponse
Response message for EndpointService.UndeployModel.
UnmanagedContainerModel
Contains model information necessary to perform batch prediction without requiring a full model import.
UpdateArtifactRequest
Request message for MetadataService.UpdateArtifact.
UpdateContextRequest
Request message for MetadataService.UpdateContext.
UpdateDatasetRequest
Request message for DatasetService.UpdateDataset.
UpdateDatasetVersionRequest
Request message for DatasetService.UpdateDatasetVersion.
UpdateDeploymentResourcePoolOperationMetadata
Runtime operation information for UpdateDeploymentResourcePool method.
UpdateDeploymentResourcePoolRequest
Request message for UpdateDeploymentResourcePool method.
UpdateEndpointRequest
Request message for EndpointService.UpdateEndpoint.
UpdateEntityTypeRequest
Request message for FeaturestoreService.UpdateEntityType.
UpdateExecutionRequest
Request message for MetadataService.UpdateExecution.
UpdateExplanationDatasetOperationMetadata
Runtime operation information for ModelService.UpdateExplanationDataset.
UpdateExplanationDatasetRequest
Request message for ModelService.UpdateExplanationDataset.
UpdateExplanationDatasetResponse
Response message of ModelService.UpdateExplanationDataset operation.
UpdateFeatureGroupOperationMetadata
Details of operations that perform update FeatureGroup.
UpdateFeatureGroupRequest
Request message for FeatureRegistryService.UpdateFeatureGroup.
UpdateFeatureOnlineStoreOperationMetadata
Details of operations that perform update FeatureOnlineStore.
UpdateFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore.
UpdateFeatureOperationMetadata
Details of operations that perform update Feature.
UpdateFeatureRequest
Request message for FeaturestoreService.UpdateFeature. Request message for FeatureRegistryService.UpdateFeature.
UpdateFeatureViewOperationMetadata
Details of operations that perform update FeatureView.
UpdateFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.UpdateFeatureView.
UpdateFeaturestoreOperationMetadata
Details of operations that perform update Featurestore.
UpdateFeaturestoreRequest
Request message for FeaturestoreService.UpdateFeaturestore.
UpdateIndexEndpointRequest
Request message for IndexEndpointService.UpdateIndexEndpoint.
UpdateIndexOperationMetadata
Runtime operation information for IndexService.UpdateIndex.
UpdateIndexRequest
Request message for IndexService.UpdateIndex.
UpdateModelDeploymentMonitoringJobOperationMetadata
Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.
UpdateModelDeploymentMonitoringJobRequest
Request message for JobService.UpdateModelDeploymentMonitoringJob.
UpdateModelRequest
Request message for ModelService.UpdateModel.
UpdateNotebookRuntimeTemplateRequest
Request message for NotebookService.UpdateNotebookRuntimeTemplate.
UpdatePersistentResourceOperationMetadata
Details of operations that perform update PersistentResource.
UpdatePersistentResourceRequest
Request message for UpdatePersistentResource method.
UpdateScheduleRequest
Request message for ScheduleService.UpdateSchedule.
UpdateSpecialistPoolOperationMetadata
Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool.
UpdateSpecialistPoolRequest
Request message for SpecialistPoolService.UpdateSpecialistPool.
UpdateTensorboardExperimentRequest
Request message for TensorboardService.UpdateTensorboardExperiment.
UpdateTensorboardOperationMetadata
Details of operations that perform update Tensorboard.
UpdateTensorboardRequest
Request message for TensorboardService.UpdateTensorboard.
UpdateTensorboardRunRequest
Request message for TensorboardService.UpdateTensorboardRun.
UpdateTensorboardTimeSeriesRequest
Request message for TensorboardService.UpdateTensorboardTimeSeries.
UpgradeNotebookRuntimeOperationMetadata
Metadata information for NotebookService.UpgradeNotebookRuntime.
UpgradeNotebookRuntimeRequest
Request message for NotebookService.UpgradeNotebookRuntime.
UpgradeNotebookRuntimeResponse
Response message for NotebookService.UpgradeNotebookRuntime.
UploadModelOperationMetadata
Details of ModelService.UploadModel operation.
UploadModelRequest
Request message for ModelService.UploadModel.
UploadModelResponse
Response message of ModelService.UploadModel operation.
UpsertDatapointsRequest
Request message for IndexService.UpsertDatapoints
UpsertDatapointsResponse
Response message for IndexService.UpsertDatapoints
UserActionReference
References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Value
Value is the value of the field.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VertexAISearch
Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation
VideoMetadata
Metadata describes the input video content.
WorkerPoolSpec
Represents the spec of a worker pool in a job.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
WriteFeatureValuesPayload
Contains Feature values to be written for a specific entity.
FeatureValuesEntry
The abstract base class for a message.
WriteFeatureValuesRequest
Request message for FeaturestoreOnlineServingService.WriteFeatureValues.
WriteFeatureValuesResponse
Response message for FeaturestoreOnlineServingService.WriteFeatureValues.
WriteTensorboardExperimentDataRequest
Request message for TensorboardService.WriteTensorboardExperimentData.
WriteTensorboardExperimentDataResponse
Response message for TensorboardService.WriteTensorboardExperimentData.
WriteTensorboardRunDataRequest
Request message for TensorboardService.WriteTensorboardRunData.
WriteTensorboardRunDataResponse
Response message for TensorboardService.WriteTensorboardRunData.
XraiAttribution
An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details:
https://arxiv.org/abs/1906.02825
Supported only by image Models.
DatasetServiceAsyncClient
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceClient
The service that manages Vertex AI Dataset and its child resources.
ListAnnotationsAsyncPager
A pager for iterating through list_annotations
requests.
This class thinly wraps an initial
ListAnnotationsResponse object, and
provides an __aiter__
method to iterate through its
annotations
field.
If there are more pages, the __aiter__
method will make additional
ListAnnotations
requests and continue to iterate
through the annotations
field on the
corresponding responses.
All the usual ListAnnotationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListAnnotationsPager
A pager for iterating through list_annotations
requests.
This class thinly wraps an initial
ListAnnotationsResponse object, and
provides an __iter__
method to iterate through its
annotations
field.
If there are more pages, the __iter__
method will make additional
ListAnnotations
requests and continue to iterate
through the annotations
field on the
corresponding responses.
All the usual ListAnnotationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataItemsAsyncPager
A pager for iterating through list_data_items
requests.
This class thinly wraps an initial
ListDataItemsResponse object, and
provides an __aiter__
method to iterate through its
data_items
field.
If there are more pages, the __aiter__
method will make additional
ListDataItems
requests and continue to iterate
through the data_items
field on the
corresponding responses.
All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataItemsPager
A pager for iterating through list_data_items
requests.
This class thinly wraps an initial
ListDataItemsResponse object, and
provides an __iter__
method to iterate through its
data_items
field.
If there are more pages, the __iter__
method will make additional
ListDataItems
requests and continue to iterate
through the data_items
field on the
corresponding responses.
All the usual ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetVersionsAsyncPager
A pager for iterating through list_dataset_versions
requests.
This class thinly wraps an initial
ListDatasetVersionsResponse object, and
provides an __aiter__
method to iterate through its
dataset_versions
field.
If there are more pages, the __aiter__
method will make additional
ListDatasetVersions
requests and continue to iterate
through the dataset_versions
field on the
corresponding responses.
All the usual ListDatasetVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetVersionsPager
A pager for iterating through list_dataset_versions
requests.
This class thinly wraps an initial
ListDatasetVersionsResponse object, and
provides an __iter__
method to iterate through its
dataset_versions
field.
If there are more pages, the __iter__
method will make additional
ListDatasetVersions
requests and continue to iterate
through the dataset_versions
field on the
corresponding responses.
All the usual ListDatasetVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetsAsyncPager
A pager for iterating through list_datasets
requests.
This class thinly wraps an initial
ListDatasetsResponse object, and
provides an __aiter__
method to iterate through its
datasets
field.
If there are more pages, the __aiter__
method will make additional
ListDatasets
requests and continue to iterate
through the datasets
field on the
corresponding responses.
All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDatasetsPager
A pager for iterating through list_datasets
requests.
This class thinly wraps an initial
ListDatasetsResponse object, and
provides an __iter__
method to iterate through its
datasets
field.
If there are more pages, the __iter__
method will make additional
ListDatasets
requests and continue to iterate
through the datasets
field on the
corresponding responses.
All the usual ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSavedQueriesAsyncPager
A pager for iterating through list_saved_queries
requests.
This class thinly wraps an initial
ListSavedQueriesResponse object, and
provides an __aiter__
method to iterate through its
saved_queries
field.
If there are more pages, the __aiter__
method will make additional
ListSavedQueries
requests and continue to iterate
through the saved_queries
field on the
corresponding responses.
All the usual ListSavedQueriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSavedQueriesPager
A pager for iterating through list_saved_queries
requests.
This class thinly wraps an initial
ListSavedQueriesResponse object, and
provides an __iter__
method to iterate through its
saved_queries
field.
If there are more pages, the __iter__
method will make additional
ListSavedQueries
requests and continue to iterate
through the saved_queries
field on the
corresponding responses.
All the usual ListSavedQueriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchDataItemsAsyncPager
A pager for iterating through search_data_items
requests.
This class thinly wraps an initial
SearchDataItemsResponse object, and
provides an __aiter__
method to iterate through its
data_item_views
field.
If there are more pages, the __aiter__
method will make additional
SearchDataItems
requests and continue to iterate
through the data_item_views
field on the
corresponding responses.
All the usual SearchDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchDataItemsPager
A pager for iterating through search_data_items
requests.
This class thinly wraps an initial
SearchDataItemsResponse object, and
provides an __iter__
method to iterate through its
data_item_views
field.
If there are more pages, the __iter__
method will make additional
SearchDataItems
requests and continue to iterate
through the data_item_views
field on the
corresponding responses.
All the usual SearchDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
DeploymentResourcePoolServiceAsyncClient
A service that manages the DeploymentResourcePool resource.
DeploymentResourcePoolServiceClient
A service that manages the DeploymentResourcePool resource.
ListDeploymentResourcePoolsAsyncPager
A pager for iterating through list_deployment_resource_pools
requests.
This class thinly wraps an initial
ListDeploymentResourcePoolsResponse object, and
provides an __aiter__
method to iterate through its
deployment_resource_pools
field.
If there are more pages, the __aiter__
method will make additional
ListDeploymentResourcePools
requests and continue to iterate
through the deployment_resource_pools
field on the
corresponding responses.
All the usual ListDeploymentResourcePoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDeploymentResourcePoolsPager
A pager for iterating through list_deployment_resource_pools
requests.
This class thinly wraps an initial
ListDeploymentResourcePoolsResponse object, and
provides an __iter__
method to iterate through its
deployment_resource_pools
field.
If there are more pages, the __iter__
method will make additional
ListDeploymentResourcePools
requests and continue to iterate
through the deployment_resource_pools
field on the
corresponding responses.
All the usual ListDeploymentResourcePoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
QueryDeployedModelsAsyncPager
A pager for iterating through query_deployed_models
requests.
This class thinly wraps an initial
QueryDeployedModelsResponse object, and
provides an __aiter__
method to iterate through its
deployed_models
field.
If there are more pages, the __aiter__
method will make additional
QueryDeployedModels
requests and continue to iterate
through the deployed_models
field on the
corresponding responses.
All the usual QueryDeployedModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
QueryDeployedModelsPager
A pager for iterating through query_deployed_models
requests.
This class thinly wraps an initial
QueryDeployedModelsResponse object, and
provides an __iter__
method to iterate through its
deployed_models
field.
If there are more pages, the __iter__
method will make additional
QueryDeployedModels
requests and continue to iterate
through the deployed_models
field on the
corresponding responses.
All the usual QueryDeployedModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
EndpointServiceAsyncClient
A service for managing Vertex AI's Endpoints.
EndpointServiceClient
A service for managing Vertex AI's Endpoints.
ListEndpointsAsyncPager
A pager for iterating through list_endpoints
requests.
This class thinly wraps an initial
ListEndpointsResponse object, and
provides an __aiter__
method to iterate through its
endpoints
field.
If there are more pages, the __aiter__
method will make additional
ListEndpoints
requests and continue to iterate
through the endpoints
field on the
corresponding responses.
All the usual ListEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListEndpointsPager
A pager for iterating through list_endpoints
requests.
This class thinly wraps an initial
ListEndpointsResponse object, and
provides an __iter__
method to iterate through its
endpoints
field.
If there are more pages, the __iter__
method will make additional
ListEndpoints
requests and continue to iterate
through the endpoints
field on the
corresponding responses.
All the usual ListEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
EvaluationServiceAsyncClient
Vertex AI Online Evaluation Service.
EvaluationServiceClient
Vertex AI Online Evaluation Service.
ExtensionExecutionServiceAsyncClient
A service for Extension execution.
ExtensionExecutionServiceClient
A service for Extension execution.
ExtensionRegistryServiceAsyncClient
A service for managing Vertex AI's Extension registry.
ExtensionRegistryServiceClient
A service for managing Vertex AI's Extension registry.
ListExtensionsAsyncPager
A pager for iterating through list_extensions
requests.
This class thinly wraps an initial
ListExtensionsResponse object, and
provides an __aiter__
method to iterate through its
extensions
field.
If there are more pages, the __aiter__
method will make additional
ListExtensions
requests and continue to iterate
through the extensions
field on the
corresponding responses.
All the usual ListExtensionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListExtensionsPager
A pager for iterating through list_extensions
requests.
This class thinly wraps an initial
ListExtensionsResponse object, and
provides an __iter__
method to iterate through its
extensions
field.
If there are more pages, the __iter__
method will make additional
ListExtensions
requests and continue to iterate
through the extensions
field on the
corresponding responses.
All the usual ListExtensionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeatureOnlineStoreAdminServiceAsyncClient
The service that handles CRUD and List for resources for FeatureOnlineStore.
FeatureOnlineStoreAdminServiceClient
The service that handles CRUD and List for resources for FeatureOnlineStore.
ListFeatureOnlineStoresAsyncPager
A pager for iterating through list_feature_online_stores
requests.
This class thinly wraps an initial
ListFeatureOnlineStoresResponse object, and
provides an __aiter__
method to iterate through its
feature_online_stores
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureOnlineStores
requests and continue to iterate
through the feature_online_stores
field on the
corresponding responses.
All the usual ListFeatureOnlineStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureOnlineStoresPager
A pager for iterating through list_feature_online_stores
requests.
This class thinly wraps an initial
ListFeatureOnlineStoresResponse object, and
provides an __iter__
method to iterate through its
feature_online_stores
field.
If there are more pages, the __iter__
method will make additional
ListFeatureOnlineStores
requests and continue to iterate
through the feature_online_stores
field on the
corresponding responses.
All the usual ListFeatureOnlineStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewSyncsAsyncPager
A pager for iterating through list_feature_view_syncs
requests.
This class thinly wraps an initial
ListFeatureViewSyncsResponse object, and
provides an __aiter__
method to iterate through its
feature_view_syncs
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureViewSyncs
requests and continue to iterate
through the feature_view_syncs
field on the
corresponding responses.
All the usual ListFeatureViewSyncsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewSyncsPager
A pager for iterating through list_feature_view_syncs
requests.
This class thinly wraps an initial
ListFeatureViewSyncsResponse object, and
provides an __iter__
method to iterate through its
feature_view_syncs
field.
If there are more pages, the __iter__
method will make additional
ListFeatureViewSyncs
requests and continue to iterate
through the feature_view_syncs
field on the
corresponding responses.
All the usual ListFeatureViewSyncsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewsAsyncPager
A pager for iterating through list_feature_views
requests.
This class thinly wraps an initial
ListFeatureViewsResponse object, and
provides an __aiter__
method to iterate through its
feature_views
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureViews
requests and continue to iterate
through the feature_views
field on the
corresponding responses.
All the usual ListFeatureViewsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureViewsPager
A pager for iterating through list_feature_views
requests.
This class thinly wraps an initial
ListFeatureViewsResponse object, and
provides an __iter__
method to iterate through its
feature_views
field.
If there are more pages, the __iter__
method will make additional
ListFeatureViews
requests and continue to iterate
through the feature_views
field on the
corresponding responses.
All the usual ListFeatureViewsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeatureOnlineStoreServiceAsyncClient
A service for fetching feature values from the online store.
FeatureOnlineStoreServiceClient
A service for fetching feature values from the online store.
FeatureRegistryServiceAsyncClient
The service that handles CRUD and List for resources for FeatureRegistry.
FeatureRegistryServiceClient
The service that handles CRUD and List for resources for FeatureRegistry.
ListFeatureGroupsAsyncPager
A pager for iterating through list_feature_groups
requests.
This class thinly wraps an initial
ListFeatureGroupsResponse object, and
provides an __aiter__
method to iterate through its
feature_groups
field.
If there are more pages, the __aiter__
method will make additional
ListFeatureGroups
requests and continue to iterate
through the feature_groups
field on the
corresponding responses.
All the usual ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeatureGroupsPager
A pager for iterating through list_feature_groups
requests.
This class thinly wraps an initial
ListFeatureGroupsResponse object, and
provides an __iter__
method to iterate through its
feature_groups
field.
If there are more pages, the __iter__
method will make additional
ListFeatureGroups
requests and continue to iterate
through the feature_groups
field on the
corresponding responses.
All the usual ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesAsyncPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
FeaturestoreOnlineServingServiceAsyncClient
A service for serving online feature values.
FeaturestoreOnlineServingServiceClient
A service for serving online feature values.
FeaturestoreServiceAsyncClient
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceClient
The service that handles CRUD and List for resources for Featurestore.
ListEntityTypesAsyncPager
A pager for iterating through list_entity_types
requests.
This class thinly wraps an initial
ListEntityTypesResponse object, and
provides an __aiter__
method to iterate through its
entity_types
field.
If there are more pages, the __aiter__
method will make additional
ListEntityTypes
requests and continue to iterate
through the entity_types
field on the
corresponding responses.
All the usual ListEntityTypesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListEntityTypesPager
A pager for iterating through list_entity_types
requests.
This class thinly wraps an initial
ListEntityTypesResponse object, and
provides an __iter__
method to iterate through its
entity_types
field.
If there are more pages, the __iter__
method will make additional
ListEntityTypes
requests and continue to iterate
through the entity_types
field on the
corresponding responses.
All the usual ListEntityTypesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesAsyncPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturesPager
A pager for iterating through list_features
requests.
This class thinly wraps an initial
ListFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
ListFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturestoresAsyncPager
A pager for iterating through list_featurestores
requests.
This class thinly wraps an initial
ListFeaturestoresResponse object, and
provides an __aiter__
method to iterate through its
featurestores
field.
If there are more pages, the __aiter__
method will make additional
ListFeaturestores
requests and continue to iterate
through the featurestores
field on the
corresponding responses.
All the usual ListFeaturestoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListFeaturestoresPager
A pager for iterating through list_featurestores
requests.
This class thinly wraps an initial
ListFeaturestoresResponse object, and
provides an __iter__
method to iterate through its
featurestores
field.
If there are more pages, the __iter__
method will make additional
ListFeaturestores
requests and continue to iterate
through the featurestores
field on the
corresponding responses.
All the usual ListFeaturestoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchFeaturesAsyncPager
A pager for iterating through search_features
requests.
This class thinly wraps an initial
SearchFeaturesResponse object, and
provides an __aiter__
method to iterate through its
features
field.
If there are more pages, the __aiter__
method will make additional
SearchFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual SearchFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchFeaturesPager
A pager for iterating through search_features
requests.
This class thinly wraps an initial
SearchFeaturesResponse object, and
provides an __iter__
method to iterate through its
features
field.
If there are more pages, the __iter__
method will make additional
SearchFeatures
requests and continue to iterate
through the features
field on the
corresponding responses.
All the usual SearchFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
GenAiCacheServiceAsyncClient
Service for managing Vertex AI's CachedContent resource.
GenAiCacheServiceClient
Service for managing Vertex AI's CachedContent resource.
ListCachedContentsAsyncPager
A pager for iterating through list_cached_contents
requests.
This class thinly wraps an initial
ListCachedContentsResponse object, and
provides an __aiter__
method to iterate through its
cached_contents
field.
If there are more pages, the __aiter__
method will make additional
ListCachedContents
requests and continue to iterate
through the cached_contents
field on the
corresponding responses.
All the usual ListCachedContentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListCachedContentsPager
A pager for iterating through list_cached_contents
requests.
This class thinly wraps an initial
ListCachedContentsResponse object, and
provides an __iter__
method to iterate through its
cached_contents
field.
If there are more pages, the __iter__
method will make additional
ListCachedContents
requests and continue to iterate
through the cached_contents
field on the
corresponding responses.
All the usual ListCachedContentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
GenAiTuningServiceAsyncClient
A service for creating and managing GenAI Tuning Jobs.
GenAiTuningServiceClient
A service for creating and managing GenAI Tuning Jobs.
ListTuningJobsAsyncPager
A pager for iterating through list_tuning_jobs
requests.
This class thinly wraps an initial
ListTuningJobsResponse object, and
provides an __aiter__
method to iterate through its
tuning_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListTuningJobs
requests and continue to iterate
through the tuning_jobs
field on the
corresponding responses.
All the usual ListTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTuningJobsPager
A pager for iterating through list_tuning_jobs
requests.
This class thinly wraps an initial
ListTuningJobsResponse object, and
provides an __iter__
method to iterate through its
tuning_jobs
field.
If there are more pages, the __iter__
method will make additional
ListTuningJobs
requests and continue to iterate
through the tuning_jobs
field on the
corresponding responses.
All the usual ListTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
IndexEndpointServiceAsyncClient
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceClient
A service for managing Vertex AI's IndexEndpoints.
ListIndexEndpointsAsyncPager
A pager for iterating through list_index_endpoints
requests.
This class thinly wraps an initial
ListIndexEndpointsResponse object, and
provides an __aiter__
method to iterate through its
index_endpoints
field.
If there are more pages, the __aiter__
method will make additional
ListIndexEndpoints
requests and continue to iterate
through the index_endpoints
field on the
corresponding responses.
All the usual ListIndexEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListIndexEndpointsPager
A pager for iterating through list_index_endpoints
requests.
This class thinly wraps an initial
ListIndexEndpointsResponse object, and
provides an __iter__
method to iterate through its
index_endpoints
field.
If there are more pages, the __iter__
method will make additional
ListIndexEndpoints
requests and continue to iterate
through the index_endpoints
field on the
corresponding responses.
All the usual ListIndexEndpointsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
IndexServiceAsyncClient
A service for creating and managing Vertex AI's Index resources.
IndexServiceClient
A service for creating and managing Vertex AI's Index resources.
ListIndexesAsyncPager
A pager for iterating through list_indexes
requests.
This class thinly wraps an initial
ListIndexesResponse object, and
provides an __aiter__
method to iterate through its
indexes
field.
If there are more pages, the __aiter__
method will make additional
ListIndexes
requests and continue to iterate
through the indexes
field on the
corresponding responses.
All the usual ListIndexesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListIndexesPager
A pager for iterating through list_indexes
requests.
This class thinly wraps an initial
ListIndexesResponse object, and
provides an __iter__
method to iterate through its
indexes
field.
If there are more pages, the __iter__
method will make additional
ListIndexes
requests and continue to iterate
through the indexes
field on the
corresponding responses.
All the usual ListIndexesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
JobServiceAsyncClient
A service for creating and managing Vertex AI's jobs.
JobServiceClient
A service for creating and managing Vertex AI's jobs.
ListBatchPredictionJobsAsyncPager
A pager for iterating through list_batch_prediction_jobs
requests.
This class thinly wraps an initial
ListBatchPredictionJobsResponse object, and
provides an __aiter__
method to iterate through its
batch_prediction_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListBatchPredictionJobs
requests and continue to iterate
through the batch_prediction_jobs
field on the
corresponding responses.
All the usual ListBatchPredictionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListBatchPredictionJobsPager
A pager for iterating through list_batch_prediction_jobs
requests.
This class thinly wraps an initial
ListBatchPredictionJobsResponse object, and
provides an __iter__
method to iterate through its
batch_prediction_jobs
field.
If there are more pages, the __iter__
method will make additional
ListBatchPredictionJobs
requests and continue to iterate
through the batch_prediction_jobs
field on the
corresponding responses.
All the usual ListBatchPredictionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListCustomJobsAsyncPager
A pager for iterating through list_custom_jobs
requests.
This class thinly wraps an initial
ListCustomJobsResponse object, and
provides an __aiter__
method to iterate through its
custom_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListCustomJobs
requests and continue to iterate
through the custom_jobs
field on the
corresponding responses.
All the usual ListCustomJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListCustomJobsPager
A pager for iterating through list_custom_jobs
requests.
This class thinly wraps an initial
ListCustomJobsResponse object, and
provides an __iter__
method to iterate through its
custom_jobs
field.
If there are more pages, the __iter__
method will make additional
ListCustomJobs
requests and continue to iterate
through the custom_jobs
field on the
corresponding responses.
All the usual ListCustomJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataLabelingJobsAsyncPager
A pager for iterating through list_data_labeling_jobs
requests.
This class thinly wraps an initial
ListDataLabelingJobsResponse object, and
provides an __aiter__
method to iterate through its
data_labeling_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListDataLabelingJobs
requests and continue to iterate
through the data_labeling_jobs
field on the
corresponding responses.
All the usual ListDataLabelingJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListDataLabelingJobsPager
A pager for iterating through list_data_labeling_jobs
requests.
This class thinly wraps an initial
ListDataLabelingJobsResponse object, and
provides an __iter__
method to iterate through its
data_labeling_jobs
field.
If there are more pages, the __iter__
method will make additional
ListDataLabelingJobs
requests and continue to iterate
through the data_labeling_jobs
field on the
corresponding responses.
All the usual ListDataLabelingJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListHyperparameterTuningJobsAsyncPager
A pager for iterating through list_hyperparameter_tuning_jobs
requests.
This class thinly wraps an initial
ListHyperparameterTuningJobsResponse object, and
provides an __aiter__
method to iterate through its
hyperparameter_tuning_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListHyperparameterTuningJobs
requests and continue to iterate
through the hyperparameter_tuning_jobs
field on the
corresponding responses.
All the usual ListHyperparameterTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListHyperparameterTuningJobsPager
A pager for iterating through list_hyperparameter_tuning_jobs
requests.
This class thinly wraps an initial
ListHyperparameterTuningJobsResponse object, and
provides an __iter__
method to iterate through its
hyperparameter_tuning_jobs
field.
If there are more pages, the __iter__
method will make additional
ListHyperparameterTuningJobs
requests and continue to iterate
through the hyperparameter_tuning_jobs
field on the
corresponding responses.
All the usual ListHyperparameterTuningJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelDeploymentMonitoringJobsAsyncPager
A pager for iterating through list_model_deployment_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelDeploymentMonitoringJobsResponse object, and
provides an __aiter__
method to iterate through its
model_deployment_monitoring_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListModelDeploymentMonitoringJobs
requests and continue to iterate
through the model_deployment_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelDeploymentMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelDeploymentMonitoringJobsPager
A pager for iterating through list_model_deployment_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelDeploymentMonitoringJobsResponse object, and
provides an __iter__
method to iterate through its
model_deployment_monitoring_jobs
field.
If there are more pages, the __iter__
method will make additional
ListModelDeploymentMonitoringJobs
requests and continue to iterate
through the model_deployment_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelDeploymentMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasJobsAsyncPager
A pager for iterating through list_nas_jobs
requests.
This class thinly wraps an initial
ListNasJobsResponse object, and
provides an __aiter__
method to iterate through its
nas_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListNasJobs
requests and continue to iterate
through the nas_jobs
field on the
corresponding responses.
All the usual ListNasJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasJobsPager
A pager for iterating through list_nas_jobs
requests.
This class thinly wraps an initial
ListNasJobsResponse object, and
provides an __iter__
method to iterate through its
nas_jobs
field.
If there are more pages, the __iter__
method will make additional
ListNasJobs
requests and continue to iterate
through the nas_jobs
field on the
corresponding responses.
All the usual ListNasJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasTrialDetailsAsyncPager
A pager for iterating through list_nas_trial_details
requests.
This class thinly wraps an initial
ListNasTrialDetailsResponse object, and
provides an __aiter__
method to iterate through its
nas_trial_details
field.
If there are more pages, the __aiter__
method will make additional
ListNasTrialDetails
requests and continue to iterate
through the nas_trial_details
field on the
corresponding responses.
All the usual ListNasTrialDetailsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNasTrialDetailsPager
A pager for iterating through list_nas_trial_details
requests.
This class thinly wraps an initial
ListNasTrialDetailsResponse object, and
provides an __iter__
method to iterate through its
nas_trial_details
field.
If there are more pages, the __iter__
method will make additional
ListNasTrialDetails
requests and continue to iterate
through the nas_trial_details
field on the
corresponding responses.
All the usual ListNasTrialDetailsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelDeploymentMonitoringStatsAnomaliesAsyncPager
A pager for iterating through search_model_deployment_monitoring_stats_anomalies
requests.
This class thinly wraps an initial
SearchModelDeploymentMonitoringStatsAnomaliesResponse object, and
provides an __aiter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __aiter__
method will make additional
SearchModelDeploymentMonitoringStatsAnomalies
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelDeploymentMonitoringStatsAnomaliesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelDeploymentMonitoringStatsAnomaliesPager
A pager for iterating through search_model_deployment_monitoring_stats_anomalies
requests.
This class thinly wraps an initial
SearchModelDeploymentMonitoringStatsAnomaliesResponse object, and
provides an __iter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __iter__
method will make additional
SearchModelDeploymentMonitoringStatsAnomalies
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelDeploymentMonitoringStatsAnomaliesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
LlmUtilityServiceAsyncClient
Service for LLM related utility functions.
LlmUtilityServiceClient
Service for LLM related utility functions.
MatchServiceAsyncClient
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceClient
MatchService is a Google managed service for efficient vector similarity search at scale.
MetadataServiceAsyncClient
Service for reading and writing metadata entries.
MetadataServiceClient
Service for reading and writing metadata entries.
ListArtifactsAsyncPager
A pager for iterating through list_artifacts
requests.
This class thinly wraps an initial
ListArtifactsResponse object, and
provides an __aiter__
method to iterate through its
artifacts
field.
If there are more pages, the __aiter__
method will make additional
ListArtifacts
requests and continue to iterate
through the artifacts
field on the
corresponding responses.
All the usual ListArtifactsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListArtifactsPager
A pager for iterating through list_artifacts
requests.
This class thinly wraps an initial
ListArtifactsResponse object, and
provides an __iter__
method to iterate through its
artifacts
field.
If there are more pages, the __iter__
method will make additional
ListArtifacts
requests and continue to iterate
through the artifacts
field on the
corresponding responses.
All the usual ListArtifactsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListContextsAsyncPager
A pager for iterating through list_contexts
requests.
This class thinly wraps an initial
ListContextsResponse object, and
provides an __aiter__
method to iterate through its
contexts
field.
If there are more pages, the __aiter__
method will make additional
ListContexts
requests and continue to iterate
through the contexts
field on the
corresponding responses.
All the usual ListContextsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListContextsPager
A pager for iterating through list_contexts
requests.
This class thinly wraps an initial
ListContextsResponse object, and
provides an __iter__
method to iterate through its
contexts
field.
If there are more pages, the __iter__
method will make additional
ListContexts
requests and continue to iterate
through the contexts
field on the
corresponding responses.
All the usual ListContextsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListExecutionsAsyncPager
A pager for iterating through list_executions
requests.
This class thinly wraps an initial
ListExecutionsResponse object, and
provides an __aiter__
method to iterate through its
executions
field.
If there are more pages, the __aiter__
method will make additional
ListExecutions
requests and continue to iterate
through the executions
field on the
corresponding responses.
All the usual ListExecutionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListExecutionsPager
A pager for iterating through list_executions
requests.
This class thinly wraps an initial
ListExecutionsResponse object, and
provides an __iter__
method to iterate through its
executions
field.
If there are more pages, the __iter__
method will make additional
ListExecutions
requests and continue to iterate
through the executions
field on the
corresponding responses.
All the usual ListExecutionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataSchemasAsyncPager
A pager for iterating through list_metadata_schemas
requests.
This class thinly wraps an initial
ListMetadataSchemasResponse object, and
provides an __aiter__
method to iterate through its
metadata_schemas
field.
If there are more pages, the __aiter__
method will make additional
ListMetadataSchemas
requests and continue to iterate
through the metadata_schemas
field on the
corresponding responses.
All the usual ListMetadataSchemasResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataSchemasPager
A pager for iterating through list_metadata_schemas
requests.
This class thinly wraps an initial
ListMetadataSchemasResponse object, and
provides an __iter__
method to iterate through its
metadata_schemas
field.
If there are more pages, the __iter__
method will make additional
ListMetadataSchemas
requests and continue to iterate
through the metadata_schemas
field on the
corresponding responses.
All the usual ListMetadataSchemasResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataStoresAsyncPager
A pager for iterating through list_metadata_stores
requests.
This class thinly wraps an initial
ListMetadataStoresResponse object, and
provides an __aiter__
method to iterate through its
metadata_stores
field.
If there are more pages, the __aiter__
method will make additional
ListMetadataStores
requests and continue to iterate
through the metadata_stores
field on the
corresponding responses.
All the usual ListMetadataStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListMetadataStoresPager
A pager for iterating through list_metadata_stores
requests.
This class thinly wraps an initial
ListMetadataStoresResponse object, and
provides an __iter__
method to iterate through its
metadata_stores
field.
If there are more pages, the __iter__
method will make additional
ListMetadataStores
requests and continue to iterate
through the metadata_stores
field on the
corresponding responses.
All the usual ListMetadataStoresResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
MigrationServiceAsyncClient
A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
MigrationServiceClient
A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
SearchMigratableResourcesAsyncPager
A pager for iterating through search_migratable_resources
requests.
This class thinly wraps an initial
SearchMigratableResourcesResponse object, and
provides an __aiter__
method to iterate through its
migratable_resources
field.
If there are more pages, the __aiter__
method will make additional
SearchMigratableResources
requests and continue to iterate
through the migratable_resources
field on the
corresponding responses.
All the usual SearchMigratableResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchMigratableResourcesPager
A pager for iterating through search_migratable_resources
requests.
This class thinly wraps an initial
SearchMigratableResourcesResponse object, and
provides an __iter__
method to iterate through its
migratable_resources
field.
If there are more pages, the __iter__
method will make additional
SearchMigratableResources
requests and continue to iterate
through the migratable_resources
field on the
corresponding responses.
All the usual SearchMigratableResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ModelGardenServiceAsyncClient
The interface of Model Garden Service.
ModelGardenServiceClient
The interface of Model Garden Service.
ListPublisherModelsAsyncPager
A pager for iterating through list_publisher_models
requests.
This class thinly wraps an initial
ListPublisherModelsResponse object, and
provides an __aiter__
method to iterate through its
publisher_models
field.
If there are more pages, the __aiter__
method will make additional
ListPublisherModels
requests and continue to iterate
through the publisher_models
field on the
corresponding responses.
All the usual ListPublisherModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListPublisherModelsPager
A pager for iterating through list_publisher_models
requests.
This class thinly wraps an initial
ListPublisherModelsResponse object, and
provides an __iter__
method to iterate through its
publisher_models
field.
If there are more pages, the __iter__
method will make additional
ListPublisherModels
requests and continue to iterate
through the publisher_models
field on the
corresponding responses.
All the usual ListPublisherModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ModelMonitoringServiceAsyncClient
A service for creating and managing Vertex AI Model moitoring. This
includes ModelMonitor
resources, ModelMonitoringJob
resources.
ModelMonitoringServiceClient
A service for creating and managing Vertex AI Model moitoring. This
includes ModelMonitor
resources, ModelMonitoringJob
resources.
ListModelMonitoringJobsAsyncPager
A pager for iterating through list_model_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelMonitoringJobsResponse object, and
provides an __aiter__
method to iterate through its
model_monitoring_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListModelMonitoringJobs
requests and continue to iterate
through the model_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelMonitoringJobsPager
A pager for iterating through list_model_monitoring_jobs
requests.
This class thinly wraps an initial
ListModelMonitoringJobsResponse object, and
provides an __iter__
method to iterate through its
model_monitoring_jobs
field.
If there are more pages, the __iter__
method will make additional
ListModelMonitoringJobs
requests and continue to iterate
through the model_monitoring_jobs
field on the
corresponding responses.
All the usual ListModelMonitoringJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelMonitorsAsyncPager
A pager for iterating through list_model_monitors
requests.
This class thinly wraps an initial
ListModelMonitorsResponse object, and
provides an __aiter__
method to iterate through its
model_monitors
field.
If there are more pages, the __aiter__
method will make additional
ListModelMonitors
requests and continue to iterate
through the model_monitors
field on the
corresponding responses.
All the usual ListModelMonitorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelMonitorsPager
A pager for iterating through list_model_monitors
requests.
This class thinly wraps an initial
ListModelMonitorsResponse object, and
provides an __iter__
method to iterate through its
model_monitors
field.
If there are more pages, the __iter__
method will make additional
ListModelMonitors
requests and continue to iterate
through the model_monitors
field on the
corresponding responses.
All the usual ListModelMonitorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelMonitoringAlertsAsyncPager
A pager for iterating through search_model_monitoring_alerts
requests.
This class thinly wraps an initial
SearchModelMonitoringAlertsResponse object, and
provides an __aiter__
method to iterate through its
model_monitoring_alerts
field.
If there are more pages, the __aiter__
method will make additional
SearchModelMonitoringAlerts
requests and continue to iterate
through the model_monitoring_alerts
field on the
corresponding responses.
All the usual SearchModelMonitoringAlertsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelMonitoringAlertsPager
A pager for iterating through search_model_monitoring_alerts
requests.
This class thinly wraps an initial
SearchModelMonitoringAlertsResponse object, and
provides an __iter__
method to iterate through its
model_monitoring_alerts
field.
If there are more pages, the __iter__
method will make additional
SearchModelMonitoringAlerts
requests and continue to iterate
through the model_monitoring_alerts
field on the
corresponding responses.
All the usual SearchModelMonitoringAlertsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelMonitoringStatsAsyncPager
A pager for iterating through search_model_monitoring_stats
requests.
This class thinly wraps an initial
SearchModelMonitoringStatsResponse object, and
provides an __aiter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __aiter__
method will make additional
SearchModelMonitoringStats
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelMonitoringStatsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SearchModelMonitoringStatsPager
A pager for iterating through search_model_monitoring_stats
requests.
This class thinly wraps an initial
SearchModelMonitoringStatsResponse object, and
provides an __iter__
method to iterate through its
monitoring_stats
field.
If there are more pages, the __iter__
method will make additional
SearchModelMonitoringStats
requests and continue to iterate
through the monitoring_stats
field on the
corresponding responses.
All the usual SearchModelMonitoringStatsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ModelServiceAsyncClient
A service for managing Vertex AI's machine learning Models.
ModelServiceClient
A service for managing Vertex AI's machine learning Models.
ListModelEvaluationSlicesAsyncPager
A pager for iterating through list_model_evaluation_slices
requests.
This class thinly wraps an initial
ListModelEvaluationSlicesResponse object, and
provides an __aiter__
method to iterate through its
model_evaluation_slices
field.
If there are more pages, the __aiter__
method will make additional
ListModelEvaluationSlices
requests and continue to iterate
through the model_evaluation_slices
field on the
corresponding responses.
All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationSlicesPager
A pager for iterating through list_model_evaluation_slices
requests.
This class thinly wraps an initial
ListModelEvaluationSlicesResponse object, and
provides an __iter__
method to iterate through its
model_evaluation_slices
field.
If there are more pages, the __iter__
method will make additional
ListModelEvaluationSlices
requests and continue to iterate
through the model_evaluation_slices
field on the
corresponding responses.
All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationsAsyncPager
A pager for iterating through list_model_evaluations
requests.
This class thinly wraps an initial
ListModelEvaluationsResponse object, and
provides an __aiter__
method to iterate through its
model_evaluations
field.
If there are more pages, the __aiter__
method will make additional
ListModelEvaluations
requests and continue to iterate
through the model_evaluations
field on the
corresponding responses.
All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelEvaluationsPager
A pager for iterating through list_model_evaluations
requests.
This class thinly wraps an initial
ListModelEvaluationsResponse object, and
provides an __iter__
method to iterate through its
model_evaluations
field.
If there are more pages, the __iter__
method will make additional
ListModelEvaluations
requests and continue to iterate
through the model_evaluations
field on the
corresponding responses.
All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelVersionsAsyncPager
A pager for iterating through list_model_versions
requests.
This class thinly wraps an initial
ListModelVersionsResponse object, and
provides an __aiter__
method to iterate through its
models
field.
If there are more pages, the __aiter__
method will make additional
ListModelVersions
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelVersionsPager
A pager for iterating through list_model_versions
requests.
This class thinly wraps an initial
ListModelVersionsResponse object, and
provides an __iter__
method to iterate through its
models
field.
If there are more pages, the __iter__
method will make additional
ListModelVersions
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelVersionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelsAsyncPager
A pager for iterating through list_models
requests.
This class thinly wraps an initial
ListModelsResponse object, and
provides an __aiter__
method to iterate through its
models
field.
If there are more pages, the __aiter__
method will make additional
ListModels
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListModelsPager
A pager for iterating through list_models
requests.
This class thinly wraps an initial
ListModelsResponse object, and
provides an __iter__
method to iterate through its
models
field.
If there are more pages, the __iter__
method will make additional
ListModels
requests and continue to iterate
through the models
field on the
corresponding responses.
All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
NotebookServiceAsyncClient
The interface for Vertex Notebook service (a.k.a. Colab on Workbench).
NotebookServiceClient
The interface for Vertex Notebook service (a.k.a. Colab on Workbench).
ListNotebookExecutionJobsAsyncPager
A pager for iterating through list_notebook_execution_jobs
requests.
This class thinly wraps an initial
ListNotebookExecutionJobsResponse object, and
provides an __aiter__
method to iterate through its
notebook_execution_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListNotebookExecutionJobs
requests and continue to iterate
through the notebook_execution_jobs
field on the
corresponding responses.
All the usual ListNotebookExecutionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookExecutionJobsPager
A pager for iterating through list_notebook_execution_jobs
requests.
This class thinly wraps an initial
ListNotebookExecutionJobsResponse object, and
provides an __iter__
method to iterate through its
notebook_execution_jobs
field.
If there are more pages, the __iter__
method will make additional
ListNotebookExecutionJobs
requests and continue to iterate
through the notebook_execution_jobs
field on the
corresponding responses.
All the usual ListNotebookExecutionJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimeTemplatesAsyncPager
A pager for iterating through list_notebook_runtime_templates
requests.
This class thinly wraps an initial
ListNotebookRuntimeTemplatesResponse object, and
provides an __aiter__
method to iterate through its
notebook_runtime_templates
field.
If there are more pages, the __aiter__
method will make additional
ListNotebookRuntimeTemplates
requests and continue to iterate
through the notebook_runtime_templates
field on the
corresponding responses.
All the usual ListNotebookRuntimeTemplatesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimeTemplatesPager
A pager for iterating through list_notebook_runtime_templates
requests.
This class thinly wraps an initial
ListNotebookRuntimeTemplatesResponse object, and
provides an __iter__
method to iterate through its
notebook_runtime_templates
field.
If there are more pages, the __iter__
method will make additional
ListNotebookRuntimeTemplates
requests and continue to iterate
through the notebook_runtime_templates
field on the
corresponding responses.
All the usual ListNotebookRuntimeTemplatesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimesAsyncPager
A pager for iterating through list_notebook_runtimes
requests.
This class thinly wraps an initial
ListNotebookRuntimesResponse object, and
provides an __aiter__
method to iterate through its
notebook_runtimes
field.
If there are more pages, the __aiter__
method will make additional
ListNotebookRuntimes
requests and continue to iterate
through the notebook_runtimes
field on the
corresponding responses.
All the usual ListNotebookRuntimesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListNotebookRuntimesPager
A pager for iterating through list_notebook_runtimes
requests.
This class thinly wraps an initial
ListNotebookRuntimesResponse object, and
provides an __iter__
method to iterate through its
notebook_runtimes
field.
If there are more pages, the __iter__
method will make additional
ListNotebookRuntimes
requests and continue to iterate
through the notebook_runtimes
field on the
corresponding responses.
All the usual ListNotebookRuntimesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PersistentResourceServiceAsyncClient
A service for managing Vertex AI's machine learning PersistentResource.
PersistentResourceServiceClient
A service for managing Vertex AI's machine learning PersistentResource.
ListPersistentResourcesAsyncPager
A pager for iterating through list_persistent_resources
requests.
This class thinly wraps an initial
ListPersistentResourcesResponse object, and
provides an __aiter__
method to iterate through its
persistent_resources
field.
If there are more pages, the __aiter__
method will make additional
ListPersistentResources
requests and continue to iterate
through the persistent_resources
field on the
corresponding responses.
All the usual ListPersistentResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListPersistentResourcesPager
A pager for iterating through list_persistent_resources
requests.
This class thinly wraps an initial
ListPersistentResourcesResponse object, and
provides an __iter__
method to iterate through its
persistent_resources
field.
If there are more pages, the __iter__
method will make additional
ListPersistentResources
requests and continue to iterate
through the persistent_resources
field on the
corresponding responses.
All the usual ListPersistentResourcesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PipelineServiceAsyncClient
A service for creating and managing Vertex AI's pipelines. This
includes both TrainingPipeline
resources (used for AutoML and
custom training) and PipelineJob
resources (used for Vertex AI
Pipelines).
PipelineServiceClient
A service for creating and managing Vertex AI's pipelines. This
includes both TrainingPipeline
resources (used for AutoML and
custom training) and PipelineJob
resources (used for Vertex AI
Pipelines).
ListPipelineJobsAsyncPager
A pager for iterating through list_pipeline_jobs
requests.
This class thinly wraps an initial
ListPipelineJobsResponse object, and
provides an __aiter__
method to iterate through its
pipeline_jobs
field.
If there are more pages, the __aiter__
method will make additional
ListPipelineJobs
requests and continue to iterate
through the pipeline_jobs
field on the
corresponding responses.
All the usual ListPipelineJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListPipelineJobsPager
A pager for iterating through list_pipeline_jobs
requests.
This class thinly wraps an initial
ListPipelineJobsResponse object, and
provides an __iter__
method to iterate through its
pipeline_jobs
field.
If there are more pages, the __iter__
method will make additional
ListPipelineJobs
requests and continue to iterate
through the pipeline_jobs
field on the
corresponding responses.
All the usual ListPipelineJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrainingPipelinesAsyncPager
A pager for iterating through list_training_pipelines
requests.
This class thinly wraps an initial
ListTrainingPipelinesResponse object, and
provides an __aiter__
method to iterate through its
training_pipelines
field.
If there are more pages, the __aiter__
method will make additional
ListTrainingPipelines
requests and continue to iterate
through the training_pipelines
field on the
corresponding responses.
All the usual ListTrainingPipelinesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrainingPipelinesPager
A pager for iterating through list_training_pipelines
requests.
This class thinly wraps an initial
ListTrainingPipelinesResponse object, and
provides an __iter__
method to iterate through its
training_pipelines
field.
If there are more pages, the __iter__
method will make additional
ListTrainingPipelines
requests and continue to iterate
through the training_pipelines
field on the
corresponding responses.
All the usual ListTrainingPipelinesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
PredictionServiceAsyncClient
A service for online predictions and explanations.
PredictionServiceClient
A service for online predictions and explanations.
ReasoningEngineExecutionServiceAsyncClient
A service for executing queries on Reasoning Engine.
ReasoningEngineExecutionServiceClient
A service for executing queries on Reasoning Engine.
ReasoningEngineServiceAsyncClient
A service for managing Vertex AI's Reasoning Engines.
ReasoningEngineServiceClient
A service for managing Vertex AI's Reasoning Engines.
ListReasoningEnginesAsyncPager
A pager for iterating through list_reasoning_engines
requests.
This class thinly wraps an initial
ListReasoningEnginesResponse object, and
provides an __aiter__
method to iterate through its
reasoning_engines
field.
If there are more pages, the __aiter__
method will make additional
ListReasoningEngines
requests and continue to iterate
through the reasoning_engines
field on the
corresponding responses.
All the usual ListReasoningEnginesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListReasoningEnginesPager
A pager for iterating through list_reasoning_engines
requests.
This class thinly wraps an initial
ListReasoningEnginesResponse object, and
provides an __iter__
method to iterate through its
reasoning_engines
field.
If there are more pages, the __iter__
method will make additional
ListReasoningEngines
requests and continue to iterate
through the reasoning_engines
field on the
corresponding responses.
All the usual ListReasoningEnginesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ScheduleServiceAsyncClient
A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.
ScheduleServiceClient
A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.
ListSchedulesAsyncPager
A pager for iterating through list_schedules
requests.
This class thinly wraps an initial
ListSchedulesResponse object, and
provides an __aiter__
method to iterate through its
schedules
field.
If there are more pages, the __aiter__
method will make additional
ListSchedules
requests and continue to iterate
through the schedules
field on the
corresponding responses.
All the usual ListSchedulesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSchedulesPager
A pager for iterating through list_schedules
requests.
This class thinly wraps an initial
ListSchedulesResponse object, and
provides an __iter__
method to iterate through its
schedules
field.
If there are more pages, the __iter__
method will make additional
ListSchedules
requests and continue to iterate
through the schedules
field on the
corresponding responses.
All the usual ListSchedulesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
SpecialistPoolServiceAsyncClient
A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.
SpecialistPoolServiceClient
A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.
ListSpecialistPoolsAsyncPager
A pager for iterating through list_specialist_pools
requests.
This class thinly wraps an initial
ListSpecialistPoolsResponse object, and
provides an __aiter__
method to iterate through its
specialist_pools
field.
If there are more pages, the __aiter__
method will make additional
ListSpecialistPools
requests and continue to iterate
through the specialist_pools
field on the
corresponding responses.
All the usual ListSpecialistPoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListSpecialistPoolsPager
A pager for iterating through list_specialist_pools
requests.
This class thinly wraps an initial
ListSpecialistPoolsResponse object, and
provides an __iter__
method to iterate through its
specialist_pools
field.
If there are more pages, the __iter__
method will make additional
ListSpecialistPools
requests and continue to iterate
through the specialist_pools
field on the
corresponding responses.
All the usual ListSpecialistPoolsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
TensorboardServiceAsyncClient
TensorboardService
TensorboardServiceClient
TensorboardService
ExportTensorboardTimeSeriesDataAsyncPager
A pager for iterating through export_tensorboard_time_series_data
requests.
This class thinly wraps an initial
ExportTensorboardTimeSeriesDataResponse object, and
provides an __aiter__
method to iterate through its
time_series_data_points
field.
If there are more pages, the __aiter__
method will make additional
ExportTensorboardTimeSeriesData
requests and continue to iterate
through the time_series_data_points
field on the
corresponding responses.
All the usual ExportTensorboardTimeSeriesDataResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ExportTensorboardTimeSeriesDataPager
A pager for iterating through export_tensorboard_time_series_data
requests.
This class thinly wraps an initial
ExportTensorboardTimeSeriesDataResponse object, and
provides an __iter__
method to iterate through its
time_series_data_points
field.
If there are more pages, the __iter__
method will make additional
ExportTensorboardTimeSeriesData
requests and continue to iterate
through the time_series_data_points
field on the
corresponding responses.
All the usual ExportTensorboardTimeSeriesDataResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardExperimentsAsyncPager
A pager for iterating through list_tensorboard_experiments
requests.
This class thinly wraps an initial
ListTensorboardExperimentsResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_experiments
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardExperiments
requests and continue to iterate
through the tensorboard_experiments
field on the
corresponding responses.
All the usual ListTensorboardExperimentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardExperimentsPager
A pager for iterating through list_tensorboard_experiments
requests.
This class thinly wraps an initial
ListTensorboardExperimentsResponse object, and
provides an __iter__
method to iterate through its
tensorboard_experiments
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardExperiments
requests and continue to iterate
through the tensorboard_experiments
field on the
corresponding responses.
All the usual ListTensorboardExperimentsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardRunsAsyncPager
A pager for iterating through list_tensorboard_runs
requests.
This class thinly wraps an initial
ListTensorboardRunsResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_runs
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardRuns
requests and continue to iterate
through the tensorboard_runs
field on the
corresponding responses.
All the usual ListTensorboardRunsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardRunsPager
A pager for iterating through list_tensorboard_runs
requests.
This class thinly wraps an initial
ListTensorboardRunsResponse object, and
provides an __iter__
method to iterate through its
tensorboard_runs
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardRuns
requests and continue to iterate
through the tensorboard_runs
field on the
corresponding responses.
All the usual ListTensorboardRunsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardTimeSeriesAsyncPager
A pager for iterating through list_tensorboard_time_series
requests.
This class thinly wraps an initial
ListTensorboardTimeSeriesResponse object, and
provides an __aiter__
method to iterate through its
tensorboard_time_series
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboardTimeSeries
requests and continue to iterate
through the tensorboard_time_series
field on the
corresponding responses.
All the usual ListTensorboardTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardTimeSeriesPager
A pager for iterating through list_tensorboard_time_series
requests.
This class thinly wraps an initial
ListTensorboardTimeSeriesResponse object, and
provides an __iter__
method to iterate through its
tensorboard_time_series
field.
If there are more pages, the __iter__
method will make additional
ListTensorboardTimeSeries
requests and continue to iterate
through the tensorboard_time_series
field on the
corresponding responses.
All the usual ListTensorboardTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardsAsyncPager
A pager for iterating through list_tensorboards
requests.
This class thinly wraps an initial
ListTensorboardsResponse object, and
provides an __aiter__
method to iterate through its
tensorboards
field.
If there are more pages, the __aiter__
method will make additional
ListTensorboards
requests and continue to iterate
through the tensorboards
field on the
corresponding responses.
All the usual ListTensorboardsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTensorboardsPager
A pager for iterating through list_tensorboards
requests.
This class thinly wraps an initial
ListTensorboardsResponse object, and
provides an __iter__
method to iterate through its
tensorboards
field.
If there are more pages, the __iter__
method will make additional
ListTensorboards
requests and continue to iterate
through the tensorboards
field on the
corresponding responses.
All the usual ListTensorboardsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
VertexRagDataServiceAsyncClient
A service for managing user data for RAG.
VertexRagDataServiceClient
A service for managing user data for RAG.
ListRagCorporaAsyncPager
A pager for iterating through list_rag_corpora
requests.
This class thinly wraps an initial
ListRagCorporaResponse object, and
provides an __aiter__
method to iterate through its
rag_corpora
field.
If there are more pages, the __aiter__
method will make additional
ListRagCorpora
requests and continue to iterate
through the rag_corpora
field on the
corresponding responses.
All the usual ListRagCorporaResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListRagCorporaPager
A pager for iterating through list_rag_corpora
requests.
This class thinly wraps an initial
ListRagCorporaResponse object, and
provides an __iter__
method to iterate through its
rag_corpora
field.
If there are more pages, the __iter__
method will make additional
ListRagCorpora
requests and continue to iterate
through the rag_corpora
field on the
corresponding responses.
All the usual ListRagCorporaResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListRagFilesAsyncPager
A pager for iterating through list_rag_files
requests.
This class thinly wraps an initial
ListRagFilesResponse object, and
provides an __aiter__
method to iterate through its
rag_files
field.
If there are more pages, the __aiter__
method will make additional
ListRagFiles
requests and continue to iterate
through the rag_files
field on the
corresponding responses.
All the usual ListRagFilesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListRagFilesPager
A pager for iterating through list_rag_files
requests.
This class thinly wraps an initial
ListRagFilesResponse object, and
provides an __iter__
method to iterate through its
rag_files
field.
If there are more pages, the __iter__
method will make additional
ListRagFiles
requests and continue to iterate
through the rag_files
field on the
corresponding responses.
All the usual ListRagFilesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
VertexRagServiceAsyncClient
A service for retrieving relevant contexts.
VertexRagServiceClient
A service for retrieving relevant contexts.
VizierServiceAsyncClient
Vertex AI Vizier API.
Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.
VizierServiceClient
Vertex AI Vizier API.
Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.
ListStudiesAsyncPager
A pager for iterating through list_studies
requests.
This class thinly wraps an initial
ListStudiesResponse object, and
provides an __aiter__
method to iterate through its
studies
field.
If there are more pages, the __aiter__
method will make additional
ListStudies
requests and continue to iterate
through the studies
field on the
corresponding responses.
All the usual ListStudiesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListStudiesPager
A pager for iterating through list_studies
requests.
This class thinly wraps an initial
ListStudiesResponse object, and
provides an __iter__
method to iterate through its
studies
field.
If there are more pages, the __iter__
method will make additional
ListStudies
requests and continue to iterate
through the studies
field on the
corresponding responses.
All the usual ListStudiesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrialsAsyncPager
A pager for iterating through list_trials
requests.
This class thinly wraps an initial
ListTrialsResponse object, and
provides an __aiter__
method to iterate through its
trials
field.
If there are more pages, the __aiter__
method will make additional
ListTrials
requests and continue to iterate
through the trials
field on the
corresponding responses.
All the usual ListTrialsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
ListTrialsPager
A pager for iterating through list_trials
requests.
This class thinly wraps an initial
ListTrialsResponse object, and
provides an __iter__
method to iterate through its
trials
field.
If there are more pages, the __iter__
method will make additional
ListTrials
requests and continue to iterate
through the trials
field on the
corresponding responses.
All the usual ListTrialsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.
AcceleratorType
Represents a hardware accelerator type.
ActiveLearningConfig
Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AddContextArtifactsAndExecutionsRequest
Request message for MetadataService.AddContextArtifactsAndExecutions.
AddContextArtifactsAndExecutionsResponse
Response message for MetadataService.AddContextArtifactsAndExecutions.
AddContextChildrenRequest
Request message for MetadataService.AddContextChildren.
AddContextChildrenResponse
Response message for MetadataService.AddContextChildren.
AddExecutionEventsRequest
Request message for MetadataService.AddExecutionEvents.
AddExecutionEventsResponse
Response message for MetadataService.AddExecutionEvents.
AddTrialMeasurementRequest
Request message for VizierService.AddTrialMeasurement.
Annotation
Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
LabelsEntry
The abstract base class for a message.
AnnotationSpec
Identifies a concept with which DataItems may be annotated with.
Artifact
Instance of a general artifact.
LabelsEntry
The abstract base class for a message.
State
Describes the state of the Artifact.
AssignNotebookRuntimeOperationMetadata
Metadata information for NotebookService.AssignNotebookRuntime.
AssignNotebookRuntimeRequest
Request message for NotebookService.AssignNotebookRuntime.
Attribution
Attribution that explains a particular prediction output.
AuthConfig
Auth configuration to run the extension.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ApiKeyConfig
Config for authentication with API key.
GoogleServiceAccountConfig
Config for Google Service Account Authentication.
HttpBasicAuthConfig
Config for HTTP Basic Authentication.
OauthConfig
Config for user oauth.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OidcConfig
Config for user OIDC auth.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AuthType
Type of Auth.
AutomaticResources
A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.
AutoscalingMetricSpec
The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.
AvroSource
The storage details for Avro input content.
BatchCancelPipelineJobsOperationMetadata
Runtime operation information for PipelineService.BatchCancelPipelineJobs.
BatchCancelPipelineJobsRequest
Request message for PipelineService.BatchCancelPipelineJobs.
BatchCancelPipelineJobsResponse
Response message for PipelineService.BatchCancelPipelineJobs.
BatchCreateFeaturesOperationMetadata
Details of operations that perform batch create Features.
BatchCreateFeaturesRequest
Request message for FeaturestoreService.BatchCreateFeatures.
BatchCreateFeaturesResponse
Response message for FeaturestoreService.BatchCreateFeatures.
BatchCreateTensorboardRunsRequest
Request message for TensorboardService.BatchCreateTensorboardRuns.
BatchCreateTensorboardRunsResponse
Response message for TensorboardService.BatchCreateTensorboardRuns.
BatchCreateTensorboardTimeSeriesRequest
Request message for TensorboardService.BatchCreateTensorboardTimeSeries.
BatchCreateTensorboardTimeSeriesResponse
Response message for TensorboardService.BatchCreateTensorboardTimeSeries.
BatchDedicatedResources
A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
BatchDeletePipelineJobsRequest
Request message for PipelineService.BatchDeletePipelineJobs.
BatchDeletePipelineJobsResponse
Response message for PipelineService.BatchDeletePipelineJobs.
BatchImportEvaluatedAnnotationsRequest
Request message for ModelService.BatchImportEvaluatedAnnotations
BatchImportEvaluatedAnnotationsResponse
Response message for ModelService.BatchImportEvaluatedAnnotations
BatchImportModelEvaluationSlicesRequest
Request message for ModelService.BatchImportModelEvaluationSlices
BatchImportModelEvaluationSlicesResponse
Response message for ModelService.BatchImportModelEvaluationSlices
BatchMigrateResourcesOperationMetadata
Runtime operation information for MigrationService.BatchMigrateResources.
PartialResult
Represents a partial result in batch migration operation for one MigrateResourceRequest.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BatchMigrateResourcesRequest
Request message for MigrationService.BatchMigrateResources.
BatchMigrateResourcesResponse
Response message for MigrationService.BatchMigrateResources.
BatchPredictionJob
A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.
InputConfig
Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
InstanceConfig
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
LabelsEntry
The abstract base class for a message.
OutputConfig
Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OutputInfo
Further describes this job's output. Supplements output_config.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BatchReadFeatureValuesOperationMetadata
Details of operations that batch reads Feature values.
BatchReadFeatureValuesRequest
Request message for FeaturestoreService.BatchReadFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EntityTypeSpec
Selects Features of an EntityType to read values of and specifies read settings.
PassThroughField
Describe pass-through fields in read_instance source.
BatchReadFeatureValuesResponse
Response message for FeaturestoreService.BatchReadFeatureValues.
BatchReadTensorboardTimeSeriesDataRequest
Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.
BatchReadTensorboardTimeSeriesDataResponse
Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.
BigQueryDestination
The BigQuery location for the output content.
BigQuerySource
The BigQuery location for the input content.
BleuInput
Input for bleu metric.
BleuInstance
Spec for bleu instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BleuMetricValue
Bleu metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BleuResults
Results for bleu metric.
BleuSpec
Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1.
Blob
Content blob.
It's preferred to send as text directly rather than raw bytes.
BlurBaselineConfig
Config for blur baseline.
When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here:
BoolArray
A list of boolean values.
CachedContent
A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CancelBatchPredictionJobRequest
Request message for JobService.CancelBatchPredictionJob.
CancelCustomJobRequest
Request message for JobService.CancelCustomJob.
CancelDataLabelingJobRequest
Request message for JobService.CancelDataLabelingJob.
CancelHyperparameterTuningJobRequest
Request message for JobService.CancelHyperparameterTuningJob.
CancelNasJobRequest
Request message for JobService.CancelNasJob.
CancelPipelineJobRequest
Request message for PipelineService.CancelPipelineJob.
CancelTrainingPipelineRequest
Request message for PipelineService.CancelTrainingPipeline.
CancelTuningJobRequest
Request message for GenAiTuningService.CancelTuningJob.
Candidate
A response candidate generated from the model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FinishReason
The reason why the model stopped generating tokens. If empty, the model has not stopped generating the tokens.
ChatCompletionsRequest
Request message for [PredictionService.ChatCompletions]
CheckTrialEarlyStoppingStateMetatdata
This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
CheckTrialEarlyStoppingStateRequest
Request message for VizierService.CheckTrialEarlyStoppingState.
CheckTrialEarlyStoppingStateResponse
Response message for VizierService.CheckTrialEarlyStoppingState.
Citation
Source attributions for content.
CitationMetadata
A collection of source attributions for a piece of content.
CoherenceInput
Input for coherence metric.
CoherenceInstance
Spec for coherence instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CoherenceResult
Spec for coherence result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CoherenceSpec
Spec for coherence score metric.
CompleteTrialRequest
Request message for VizierService.CompleteTrial.
CompletionStats
Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
ComputeTokensRequest
Request message for ComputeTokens RPC call.
ComputeTokensResponse
Response message for ComputeTokens RPC call.
ContainerRegistryDestination
The Container Registry location for the container image.
ContainerSpec
The spec of a Container.
Content
The base structured datatype containing multi-part content of a message.
A Content
includes a role
field designating the producer of
the Content
and a parts
field containing multi-part data
that contains the content of the message turn.
Context
Instance of a general context.
LabelsEntry
The abstract base class for a message.
CopyModelOperationMetadata
Details of ModelService.CopyModel operation.
CopyModelRequest
Request message for ModelService.CopyModel.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CopyModelResponse
Response message of ModelService.CopyModel operation.
CountTokensRequest
Request message for PredictionService.CountTokens.
CountTokensResponse
Response message for PredictionService.CountTokens.
CreateArtifactRequest
Request message for MetadataService.CreateArtifact.
CreateBatchPredictionJobRequest
Request message for JobService.CreateBatchPredictionJob.
CreateCachedContentRequest
Request message for GenAiCacheService.CreateCachedContent.
CreateContextRequest
Request message for MetadataService.CreateContext.
CreateCustomJobRequest
Request message for JobService.CreateCustomJob.
CreateDataLabelingJobRequest
Request message for JobService.CreateDataLabelingJob.
CreateDatasetOperationMetadata
Runtime operation information for DatasetService.CreateDataset.
CreateDatasetRequest
Request message for DatasetService.CreateDataset.
CreateDatasetVersionOperationMetadata
Runtime operation information for DatasetService.CreateDatasetVersion.
CreateDatasetVersionRequest
Request message for DatasetService.CreateDatasetVersion.
CreateDeploymentResourcePoolOperationMetadata
Runtime operation information for CreateDeploymentResourcePool method.
CreateDeploymentResourcePoolRequest
Request message for CreateDeploymentResourcePool method.
CreateEndpointOperationMetadata
Runtime operation information for EndpointService.CreateEndpoint.
CreateEndpointRequest
Request message for EndpointService.CreateEndpoint.
CreateEntityTypeOperationMetadata
Details of operations that perform create EntityType.
CreateEntityTypeRequest
Request message for FeaturestoreService.CreateEntityType.
CreateExecutionRequest
Request message for MetadataService.CreateExecution.
CreateFeatureGroupOperationMetadata
Details of operations that perform create FeatureGroup.
CreateFeatureGroupRequest
Request message for FeatureRegistryService.CreateFeatureGroup.
CreateFeatureOnlineStoreOperationMetadata
Details of operations that perform create FeatureOnlineStore.
CreateFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.CreateFeatureOnlineStore.
CreateFeatureOperationMetadata
Details of operations that perform create Feature.
CreateFeatureRequest
Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.
CreateFeatureViewOperationMetadata
Details of operations that perform create FeatureView.
CreateFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.CreateFeatureView.
CreateFeaturestoreOperationMetadata
Details of operations that perform create Featurestore.
CreateFeaturestoreRequest
Request message for FeaturestoreService.CreateFeaturestore.
CreateHyperparameterTuningJobRequest
Request message for JobService.CreateHyperparameterTuningJob.
CreateIndexEndpointOperationMetadata
Runtime operation information for IndexEndpointService.CreateIndexEndpoint.
CreateIndexEndpointRequest
Request message for IndexEndpointService.CreateIndexEndpoint.
CreateIndexOperationMetadata
Runtime operation information for IndexService.CreateIndex.
CreateIndexRequest
Request message for IndexService.CreateIndex.
CreateMetadataSchemaRequest
Request message for MetadataService.CreateMetadataSchema.
CreateMetadataStoreOperationMetadata
Details of operations that perform MetadataService.CreateMetadataStore.
CreateMetadataStoreRequest
Request message for MetadataService.CreateMetadataStore.
CreateModelDeploymentMonitoringJobRequest
Request message for JobService.CreateModelDeploymentMonitoringJob.
CreateModelMonitorOperationMetadata
Runtime operation information for ModelMonitoringService.CreateModelMonitor.
CreateModelMonitorRequest
Request message for ModelMonitoringService.CreateModelMonitor.
CreateModelMonitoringJobRequest
Request message for ModelMonitoringService.CreateModelMonitoringJob.
CreateNasJobRequest
Request message for JobService.CreateNasJob.
CreateNotebookExecutionJobOperationMetadata
Metadata information for NotebookService.CreateNotebookExecutionJob.
CreateNotebookExecutionJobRequest
Request message for [NotebookService.CreateNotebookExecutionJob]
CreateNotebookRuntimeTemplateOperationMetadata
Metadata information for NotebookService.CreateNotebookRuntimeTemplate.
CreateNotebookRuntimeTemplateRequest
Request message for NotebookService.CreateNotebookRuntimeTemplate.
CreatePersistentResourceOperationMetadata
Details of operations that perform create PersistentResource.
CreatePersistentResourceRequest
Request message for PersistentResourceService.CreatePersistentResource.
CreatePipelineJobRequest
Request message for PipelineService.CreatePipelineJob.
CreateRagCorpusOperationMetadata
Runtime operation information for VertexRagDataService.CreateRagCorpus.
CreateRagCorpusRequest
Request message for VertexRagDataService.CreateRagCorpus.
CreateReasoningEngineOperationMetadata
Details of ReasoningEngineService.CreateReasoningEngine operation.
CreateReasoningEngineRequest
Request message for ReasoningEngineService.CreateReasoningEngine.
CreateRegistryFeatureOperationMetadata
Details of operations that perform create FeatureGroup.
CreateScheduleRequest
Request message for ScheduleService.CreateSchedule.
CreateSpecialistPoolOperationMetadata
Runtime operation information for SpecialistPoolService.CreateSpecialistPool.
CreateSpecialistPoolRequest
Request message for SpecialistPoolService.CreateSpecialistPool.
CreateStudyRequest
Request message for VizierService.CreateStudy.
CreateTensorboardExperimentRequest
Request message for TensorboardService.CreateTensorboardExperiment.
CreateTensorboardOperationMetadata
Details of operations that perform create Tensorboard.
CreateTensorboardRequest
Request message for TensorboardService.CreateTensorboard.
CreateTensorboardRunRequest
Request message for TensorboardService.CreateTensorboardRun.
CreateTensorboardTimeSeriesRequest
Request message for TensorboardService.CreateTensorboardTimeSeries.
CreateTrainingPipelineRequest
Request message for PipelineService.CreateTrainingPipeline.
CreateTrialRequest
Request message for VizierService.CreateTrial.
CreateTuningJobRequest
Request message for GenAiTuningService.CreateTuningJob.
CsvDestination
The storage details for CSV output content.
CsvSource
The storage details for CSV input content.
CustomJob
Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).
LabelsEntry
The abstract base class for a message.
WebAccessUrisEntry
The abstract base class for a message.
CustomJobSpec
Represents the spec of a CustomJob.
DataItem
A piece of data in a Dataset. Could be an image, a video, a document or plain text.
LabelsEntry
The abstract base class for a message.
DataItemView
A container for a single DataItem and Annotations on it.
DataLabelingJob
DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
AnnotationLabelsEntry
The abstract base class for a message.
LabelsEntry
The abstract base class for a message.
Dataset
A collection of DataItems and Annotations on them.
LabelsEntry
The abstract base class for a message.
DatasetVersion
Describes the dataset version.
DedicatedResources
A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
DeleteArtifactRequest
Request message for MetadataService.DeleteArtifact.
DeleteBatchPredictionJobRequest
Request message for JobService.DeleteBatchPredictionJob.
DeleteCachedContentRequest
Request message for GenAiCacheService.DeleteCachedContent.
DeleteContextRequest
Request message for MetadataService.DeleteContext.
DeleteCustomJobRequest
Request message for JobService.DeleteCustomJob.
DeleteDataLabelingJobRequest
Request message for JobService.DeleteDataLabelingJob.
DeleteDatasetRequest
Request message for DatasetService.DeleteDataset.
DeleteDatasetVersionRequest
Request message for DatasetService.DeleteDatasetVersion.
DeleteDeploymentResourcePoolRequest
Request message for DeleteDeploymentResourcePool method.
DeleteEndpointRequest
Request message for EndpointService.DeleteEndpoint.
DeleteEntityTypeRequest
Request message for [FeaturestoreService.DeleteEntityTypes][].
DeleteExecutionRequest
Request message for MetadataService.DeleteExecution.
DeleteExtensionRequest
Request message for ExtensionRegistryService.DeleteExtension.
DeleteFeatureGroupRequest
Request message for FeatureRegistryService.DeleteFeatureGroup.
DeleteFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore.
DeleteFeatureRequest
Request message for FeaturestoreService.DeleteFeature. Request message for FeatureRegistryService.DeleteFeature.
DeleteFeatureValuesOperationMetadata
Details of operations that delete Feature values.
DeleteFeatureValuesRequest
Request message for FeaturestoreService.DeleteFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SelectEntity
Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.
SelectTimeRangeAndFeature
Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.
DeleteFeatureValuesResponse
Response message for FeaturestoreService.DeleteFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SelectEntity
Response message if the request uses the SelectEntity option.
SelectTimeRangeAndFeature
Response message if the request uses the SelectTimeRangeAndFeature option.
DeleteFeatureViewRequest
Request message for [FeatureOnlineStoreAdminService.DeleteFeatureViews][].
DeleteFeaturestoreRequest
Request message for FeaturestoreService.DeleteFeaturestore.
DeleteHyperparameterTuningJobRequest
Request message for JobService.DeleteHyperparameterTuningJob.
DeleteIndexEndpointRequest
Request message for IndexEndpointService.DeleteIndexEndpoint.
DeleteIndexRequest
Request message for IndexService.DeleteIndex.
DeleteMetadataStoreOperationMetadata
Details of operations that perform MetadataService.DeleteMetadataStore.
DeleteMetadataStoreRequest
Request message for MetadataService.DeleteMetadataStore.
DeleteModelDeploymentMonitoringJobRequest
Request message for JobService.DeleteModelDeploymentMonitoringJob.
DeleteModelMonitorRequest
Request message for ModelMonitoringService.DeleteModelMonitor.
DeleteModelMonitoringJobRequest
Request message for ModelMonitoringService.DeleteModelMonitoringJob.
DeleteModelRequest
Request message for ModelService.DeleteModel.
DeleteModelVersionRequest
Request message for ModelService.DeleteModelVersion.
DeleteNasJobRequest
Request message for JobService.DeleteNasJob.
DeleteNotebookExecutionJobRequest
Request message for [NotebookService.DeleteNotebookExecutionJob]
DeleteNotebookRuntimeRequest
Request message for NotebookService.DeleteNotebookRuntime.
DeleteNotebookRuntimeTemplateRequest
Request message for NotebookService.DeleteNotebookRuntimeTemplate.
DeleteOperationMetadata
Details of operations that perform deletes of any entities.
DeletePersistentResourceRequest
Request message for PersistentResourceService.DeletePersistentResource.
DeletePipelineJobRequest
Request message for PipelineService.DeletePipelineJob.
DeleteRagCorpusRequest
Request message for VertexRagDataService.DeleteRagCorpus.
DeleteRagFileRequest
Request message for VertexRagDataService.DeleteRagFile.
DeleteReasoningEngineRequest
Request message for ReasoningEngineService.DeleteReasoningEngine.
DeleteSavedQueryRequest
Request message for DatasetService.DeleteSavedQuery.
DeleteScheduleRequest
Request message for ScheduleService.DeleteSchedule.
DeleteSpecialistPoolRequest
Request message for SpecialistPoolService.DeleteSpecialistPool.
DeleteStudyRequest
Request message for VizierService.DeleteStudy.
DeleteTensorboardExperimentRequest
Request message for TensorboardService.DeleteTensorboardExperiment.
DeleteTensorboardRequest
Request message for TensorboardService.DeleteTensorboard.
DeleteTensorboardRunRequest
Request message for TensorboardService.DeleteTensorboardRun.
DeleteTensorboardTimeSeriesRequest
Request message for TensorboardService.DeleteTensorboardTimeSeries.
DeleteTrainingPipelineRequest
Request message for PipelineService.DeleteTrainingPipeline.
DeleteTrialRequest
Request message for VizierService.DeleteTrial.
DeployIndexOperationMetadata
Runtime operation information for IndexEndpointService.DeployIndex.
DeployIndexRequest
Request message for IndexEndpointService.DeployIndex.
DeployIndexResponse
Response message for IndexEndpointService.DeployIndex.
DeployModelOperationMetadata
Runtime operation information for EndpointService.DeployModel.
DeployModelRequest
Request message for EndpointService.DeployModel.
TrafficSplitEntry
The abstract base class for a message.
DeployModelResponse
Response message for EndpointService.DeployModel.
DeployedIndex
A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
DeployedIndexAuthConfig
Used to set up the auth on the DeployedIndex's private endpoint.
AuthProvider
Configuration for an authentication provider, including support for
JSON Web Token
(JWT) <https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32>
__.
DeployedIndexRef
Points to a DeployedIndex.
DeployedModel
A deployment of a Model. Endpoints contain one or more DeployedModels.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DeployedModelRef
Points to a DeployedModel.
DeploymentResourcePool
A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.
DestinationFeatureSetting
DirectPredictRequest
Request message for PredictionService.DirectPredict.
DirectPredictResponse
Response message for PredictionService.DirectPredict.
DirectRawPredictRequest
Request message for PredictionService.DirectRawPredict.
DirectRawPredictResponse
Response message for PredictionService.DirectRawPredict.
DirectUploadSource
The input content is encapsulated and uploaded in the request.
DiskSpec
Represents the spec of disk options.
DoubleArray
A list of double values.
EncryptionSpec
Represents a customer-managed encryption key spec that can be applied to a top-level resource.
Endpoint
Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
LabelsEntry
The abstract base class for a message.
TrafficSplitEntry
The abstract base class for a message.
EntityIdSelector
Selector for entityId. Getting ids from the given source.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EntityType
An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.
LabelsEntry
The abstract base class for a message.
EnvVar
Represents an environment variable present in a Container or Python Module.
ErrorAnalysisAnnotation
Model error analysis for each annotation.
AttributedItem
Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.
QueryType
The query type used for finding the attributed items.
EvaluateInstancesRequest
Request message for EvaluationService.EvaluateInstances.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EvaluateInstancesResponse
Response message for EvaluationService.EvaluateInstances.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EvaluatedAnnotation
True positive, false positive, or false negative.
EvaluatedAnnotation is only available under ModelEvaluationSlice
with slice of annotationSpec
dimension.
EvaluatedAnnotationType
Describes the type of the EvaluatedAnnotation. The type is determined
EvaluatedAnnotationExplanation
Explanation result of the prediction produced by the Model.
Event
An edge describing the relationship between an Artifact and an Execution in a lineage graph.
LabelsEntry
The abstract base class for a message.
Type
Describes whether an Event's Artifact is the Execution's input or output.
ExactMatchInput
Input for exact match metric.
ExactMatchInstance
Spec for exact match instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExactMatchMetricValue
Exact match metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExactMatchResults
Results for exact match metric.
ExactMatchSpec
Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.
Examples
Example-based explainability that returns the nearest neighbors from the provided dataset.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExampleGcsSource
The Cloud Storage input instances.
DataFormat
The format of the input example instances.
ExamplesOverride
Overrides for example-based explanations.
DataFormat
Data format enum.
ExamplesRestrictionsNamespace
Restrictions namespace for example-based explanations overrides.
ExecuteExtensionRequest
Request message for ExtensionExecutionService.ExecuteExtension.
ExecuteExtensionResponse
Response message for ExtensionExecutionService.ExecuteExtension.
Execution
Instance of a general execution.
LabelsEntry
The abstract base class for a message.
State
Describes the state of the Execution.
ExplainRequest
Request message for PredictionService.Explain.
ConcurrentExplanationSpecOverrideEntry
The abstract base class for a message.
ExplainResponse
Response message for PredictionService.Explain.
ConcurrentExplanation
This message is a wrapper grouping Concurrent Explanations.
ConcurrentExplanationsEntry
The abstract base class for a message.
Explanation
Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.
ExplanationMetadata
Metadata describing the Model's input and output for explanation.
InputMetadata
Metadata of the input of a feature.
Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.
Encoding
Defines how a feature is encoded. Defaults to IDENTITY.
::
input = [27, 6.0, 150]
index_feature_mapping = ["age", "height", "weight"]
BAG_OF_FEATURES_SPARSE (3):
The tensor represents a bag of features where each index
maps to a feature. Zero values in the tensor indicates
feature being non-existent.
<xref uid="google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping">InputMetadata.index_feature_mapping</xref>
must be provided for this encoding. For example:
::
input = [2, 0, 5, 0, 1]
index_feature_mapping = ["a", "b", "c", "d", "e"]
INDICATOR (4):
The tensor is a list of binaries representing whether a
feature exists or not (1 indicates existence).
<xref uid="google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.index_feature_mapping">InputMetadata.index_feature_mapping</xref>
must be provided for this encoding. For example:
::
input = [1, 0, 1, 0, 1]
index_feature_mapping = ["a", "b", "c", "d", "e"]
COMBINED_EMBEDDING (5):
The tensor is encoded into a 1-dimensional array represented
by an encoded tensor.
<xref uid="google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name">InputMetadata.encoded_tensor_name</xref>
must be provided for this encoding. For example:
::
input = ["This", "is", "a", "test", "."]
encoded = [0.1, 0.2, 0.3, 0.4, 0.5]
CONCAT_EMBEDDING (6):
Select this encoding when the input tensor is encoded into a
2-dimensional array represented by an encoded tensor.
<xref uid="google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata.encoded_tensor_name">InputMetadata.encoded_tensor_name</xref>
must be provided for this encoding. The first dimension of
the encoded tensor's shape is the same as the input tensor's
shape. For example:
::
input = ["This", "is", "a", "test", "."]
encoded = [[0.1, 0.2, 0.3, 0.4, 0.5],
[0.2, 0.1, 0.4, 0.3, 0.5],
[0.5, 0.1, 0.3, 0.5, 0.4],
[0.5, 0.3, 0.1, 0.2, 0.4],
[0.4, 0.3, 0.2, 0.5, 0.1]]
FeatureValueDomain
Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained.
Visualization
Visualization configurations for image explanation.
ColorMap
The color scheme used for highlighting areas.
OverlayType
How the original image is displayed in the visualization.
Polarity
Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.
Type
Type of the image visualization. Only applicable to [Integrated Gradients attribution][google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution].
InputsEntry
The abstract base class for a message.
OutputMetadata
Metadata of the prediction output to be explained.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OutputsEntry
The abstract base class for a message.
ExplanationMetadataOverride
The ExplanationMetadata entries that can be overridden at [online explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] time.
InputMetadataOverride
The [input metadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata] entries to be overridden.
InputsEntry
The abstract base class for a message.
ExplanationParameters
Parameters to configure explaining for Model's predictions.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExplanationSpec
Specification of Model explanation.
ExplanationSpecOverride
The ExplanationSpec entries that can be overridden at [online explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] time.
ExportDataConfig
Describes what part of the Dataset is to be exported, the destination of the export and how to export.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExportDataOperationMetadata
Runtime operation information for DatasetService.ExportData.
ExportDataRequest
Request message for DatasetService.ExportData.
ExportDataResponse
Response message for DatasetService.ExportData.
ExportFeatureValuesOperationMetadata
Details of operations that exports Features values.
ExportFeatureValuesRequest
Request message for FeaturestoreService.ExportFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FullExport
Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].
SnapshotExport
Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].
ExportFeatureValuesResponse
Response message for FeaturestoreService.ExportFeatureValues.
ExportFractionSplit
Assigns the input data to training, validation, and test sets as per
the given fractions. Any of training_fraction
,
validation_fraction
and test_fraction
may optionally be
provided, they must sum to up to 1. If the provided ones sum to less
than 1, the remainder is assigned to sets as decided by Vertex AI.
If none of the fractions are set, by default roughly 80% of data is
used for training, 10% for validation, and 10% for test.
ExportModelOperationMetadata
Details of ModelService.ExportModel operation.
OutputInfo
Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.
ExportModelRequest
Request message for ModelService.ExportModel.
OutputConfig
Output configuration for the Model export.
ExportModelResponse
Response message of ModelService.ExportModel operation.
ExportTensorboardTimeSeriesDataRequest
Request message for TensorboardService.ExportTensorboardTimeSeriesData.
ExportTensorboardTimeSeriesDataResponse
Response message for TensorboardService.ExportTensorboardTimeSeriesData.
Extension
Extensions are tools for large language models to access external data, run computations, etc.
ExtensionManifest
Manifest spec of an Extension needed for runtime execution.
ApiSpec
The API specification shown to the LLM.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExtensionOperation
Operation of an extension.
ExtensionPrivateServiceConnectConfig
PrivateExtensionConfig configuration for the extension.
Feature
Feature Metadata information. For example, color is a feature that describes an apple.
LabelsEntry
The abstract base class for a message.
MonitoringStatsAnomaly
A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.
Objective
If the objective in the request is both Import Feature Analysis and Snapshot Analysis, this objective could be one of them. Otherwise, this objective should be the same as the objective in the request.
ValueType
Only applicable for Vertex AI Legacy Feature Store. An enum representing the value type of a feature.
FeatureGroup
Vertex AI Feature Group.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BigQuery
Input source type for BigQuery Tables and Views.
LabelsEntry
The abstract base class for a message.
FeatureNoiseSigma
Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.
NoiseSigmaForFeature
Noise sigma for a single feature.
FeatureOnlineStore
Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Bigtable
AutoScaling
DedicatedServingEndpoint
The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default.
EmbeddingManagement
Deprecated: This sub message is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type. Contains settings for embedding management.
LabelsEntry
The abstract base class for a message.
Optimized
Optimized storage type
State
Possible states a featureOnlineStore can have.
FeatureSelector
Selector for Features of an EntityType.
FeatureStatsAnomaly
Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.
FeatureValue
Value for a feature.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Metadata
Metadata of feature value.
FeatureValueDestination
A destination location for Feature values and format.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureValueList
Container for list of values.
FeatureView
FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BigQuerySource
FeatureRegistrySource
A Feature Registry source for features that need to be synced to Online Store.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureGroup
Features belonging to a single feature group that will be synced to Online Store.
IndexConfig
Configuration for vector indexing.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BruteForceConfig
Configuration options for using brute force search.
DistanceMeasureType
The distance measure used in nearest neighbor search.
We strongly suggest using DOT_PRODUCT_DISTANCE +
UNIT_L2_NORM instead of COSINE distance. Our algorithms have
been more optimized for DOT_PRODUCT distance which, when
combined with UNIT_L2_NORM, is mathematically equivalent to
COSINE distance and results in the same ranking.
DOT_PRODUCT_DISTANCE (3):
Dot Product Distance. Defined as a negative
of the dot product.
TreeAHConfig
Configuration options for the tree-AH algorithm.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
LabelsEntry
The abstract base class for a message.
ServiceAgentType
Service agent type used during data sync.
SyncConfig
Configuration for Sync. Only one option is set.
VectorSearchConfig
Deprecated. Use IndexConfig instead.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DistanceMeasureType
We strongly suggest using DOT_PRODUCT_DISTANCE +
UNIT_L2_NORM instead of COSINE distance. Our algorithms have
been more optimized for DOT_PRODUCT distance which, when
combined with UNIT_L2_NORM, is mathematically equivalent to
COSINE distance and results in the same ranking.
DOT_PRODUCT_DISTANCE (3):
Dot Product Distance. Defined as a negative
of the dot product.
TreeAHConfig
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureViewDataFormat
Format of the data in the Feature View.
FeatureViewDataKey
Lookup key for a feature view.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CompositeKey
ID that is comprised from several parts (columns).
FeatureViewSync
FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.
SyncSummary
Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync.
Featurestore
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.
LabelsEntry
The abstract base class for a message.
OnlineServingConfig
OnlineServingConfig specifies the details for provisioning online serving resources.
Scaling
Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).
State
Possible states a featurestore can have.
FeaturestoreMonitoringConfig
Configuration of how features in Featurestore are monitored.
ImportFeaturesAnalysis
Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.
Baseline
Defines the baseline to do anomaly detection for feature values imported by each ImportFeatureValues operation.
State
The state defines whether to enable ImportFeature analysis.
SnapshotAnalysis
Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.
ThresholdConfig
The config for Featurestore Monitoring threshold.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FetchFeatureValuesRequest
Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Format
Format of the response data.
FetchFeatureValuesResponse
Response message for FeatureOnlineStoreService.FetchFeatureValues
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureNameValuePairList
Response structure in the format of key (feature name) and (feature) value pair.
FeatureNameValuePair
Feature name & value pair.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FileData
URI based data.
FilterSplit
Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).
Supported only for unstructured Datasets.
FindNeighborsRequest
The request message for MatchService.FindNeighbors.
Query
A query to find a number of the nearest neighbors (most similar vectors) of a vector.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RRF
Parameters for RRF algorithm that combines search results.
FindNeighborsResponse
The response message for MatchService.FindNeighbors.
NearestNeighbors
Nearest neighbors for one query.
Neighbor
A neighbor of the query vector.
FluencyInput
Input for fluency metric.
FluencyInstance
Spec for fluency instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FluencyResult
Spec for fluency result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FluencySpec
Spec for fluency score metric.
FractionSplit
Assigns the input data to training, validation, and test sets as per
the given fractions. Any of training_fraction
,
validation_fraction
and test_fraction
may optionally be
provided, they must sum to up to 1. If the provided ones sum to less
than 1, the remainder is assigned to sets as decided by Vertex AI.
If none of the fractions are set, by default roughly 80% of data is
used for training, 10% for validation, and 10% for test.
FulfillmentInput
Input for fulfillment metric.
FulfillmentInstance
Spec for fulfillment instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FulfillmentResult
Spec for fulfillment result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FulfillmentSpec
Spec for fulfillment metric.
FunctionCall
A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values.
FunctionCallingConfig
Function calling config.
Mode
Function calling mode.
FunctionDeclaration
Structured representation of a function declaration as defined by
the OpenAPI 3.0
specification <https://spec.openapis.org/oas/v3.0.3>
__. Included in
this declaration are the function name and parameters. This
FunctionDeclaration is a representation of a block of code that can
be used as a Tool
by the model and executed by the client.
FunctionResponse
The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.
GcsDestination
The Google Cloud Storage location where the output is to be written to.
GcsSource
The Google Cloud Storage location for the input content.
GenerateContentRequest
Request message for [PredictionService.GenerateContent].
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GenerateContentResponse
Response message for [PredictionService.GenerateContent].
PromptFeedback
Content filter results for a prompt sent in the request.
BlockedReason
Blocked reason enumeration.
UsageMetadata
Usage metadata about response(s).
GenerationConfig
Generation config.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GenericOperationMetadata
Generic Metadata shared by all operations.
GenieSource
Contains information about the source of the models generated from Generative AI Studio.
GetAnnotationSpecRequest
Request message for DatasetService.GetAnnotationSpec.
GetArtifactRequest
Request message for MetadataService.GetArtifact.
GetBatchPredictionJobRequest
Request message for JobService.GetBatchPredictionJob.
GetCachedContentRequest
Request message for GenAiCacheService.GetCachedContent.
GetContextRequest
Request message for MetadataService.GetContext.
GetCustomJobRequest
Request message for JobService.GetCustomJob.
GetDataLabelingJobRequest
Request message for JobService.GetDataLabelingJob.
GetDatasetRequest
Request message for DatasetService.GetDataset.
GetDatasetVersionRequest
Request message for DatasetService.GetDatasetVersion.
GetDeploymentResourcePoolRequest
Request message for GetDeploymentResourcePool method.
GetEndpointRequest
Request message for EndpointService.GetEndpoint
GetEntityTypeRequest
Request message for FeaturestoreService.GetEntityType.
GetExecutionRequest
Request message for MetadataService.GetExecution.
GetExtensionRequest
Request message for ExtensionRegistryService.GetExtension.
GetFeatureGroupRequest
Request message for FeatureRegistryService.GetFeatureGroup.
GetFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureOnlineStore.
GetFeatureRequest
Request message for FeaturestoreService.GetFeature. Request message for FeatureRegistryService.GetFeature.
GetFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureView.
GetFeatureViewSyncRequest
Request message for FeatureOnlineStoreAdminService.GetFeatureViewSync.
GetFeaturestoreRequest
Request message for FeaturestoreService.GetFeaturestore.
GetHyperparameterTuningJobRequest
Request message for JobService.GetHyperparameterTuningJob.
GetIndexEndpointRequest
Request message for IndexEndpointService.GetIndexEndpoint
GetIndexRequest
Request message for IndexService.GetIndex
GetMetadataSchemaRequest
Request message for MetadataService.GetMetadataSchema.
GetMetadataStoreRequest
Request message for MetadataService.GetMetadataStore.
GetModelDeploymentMonitoringJobRequest
Request message for JobService.GetModelDeploymentMonitoringJob.
GetModelEvaluationRequest
Request message for ModelService.GetModelEvaluation.
GetModelEvaluationSliceRequest
Request message for ModelService.GetModelEvaluationSlice.
GetModelMonitorRequest
Request message for ModelMonitoringService.GetModelMonitor.
GetModelMonitoringJobRequest
Request message for ModelMonitoringService.GetModelMonitoringJob.
GetModelRequest
Request message for ModelService.GetModel.
GetNasJobRequest
Request message for JobService.GetNasJob.
GetNasTrialDetailRequest
Request message for JobService.GetNasTrialDetail.
GetNotebookExecutionJobRequest
Request message for [NotebookService.GetNotebookExecutionJob]
GetNotebookRuntimeRequest
Request message for NotebookService.GetNotebookRuntime
GetNotebookRuntimeTemplateRequest
Request message for NotebookService.GetNotebookRuntimeTemplate
GetPersistentResourceRequest
Request message for PersistentResourceService.GetPersistentResource.
GetPipelineJobRequest
Request message for PipelineService.GetPipelineJob.
GetPublisherModelRequest
Request message for ModelGardenService.GetPublisherModel
GetRagCorpusRequest
Request message for VertexRagDataService.GetRagCorpus
GetRagFileRequest
Request message for VertexRagDataService.GetRagFile
GetReasoningEngineRequest
Request message for ReasoningEngineService.GetReasoningEngine.
GetScheduleRequest
Request message for ScheduleService.GetSchedule.
GetSpecialistPoolRequest
Request message for SpecialistPoolService.GetSpecialistPool.
GetStudyRequest
Request message for VizierService.GetStudy.
GetTensorboardExperimentRequest
Request message for TensorboardService.GetTensorboardExperiment.
GetTensorboardRequest
Request message for TensorboardService.GetTensorboard.
GetTensorboardRunRequest
Request message for TensorboardService.GetTensorboardRun.
GetTensorboardTimeSeriesRequest
Request message for TensorboardService.GetTensorboardTimeSeries.
GetTrainingPipelineRequest
Request message for PipelineService.GetTrainingPipeline.
GetTrialRequest
Request message for VizierService.GetTrial.
GetTuningJobRequest
Request message for GenAiTuningService.GetTuningJob.
GoogleDriveSource
The Google Drive location for the input content.
ResourceId
The type and ID of the Google Drive resource.
ResourceType
The type of the Google Drive resource.
GoogleSearchRetrieval
Tool to retrieve public web data for grounding, powered by Google.
GroundednessInput
Input for groundedness metric.
GroundednessInstance
Spec for groundedness instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GroundednessResult
Spec for groundedness result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GroundednessSpec
Spec for groundedness metric.
GroundingAttribution
Grounding attribution.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RetrievedContext
Attribution from context retrieved by the retrieval tools.
Web
Attribution from the web.
GroundingChunk
Grounding chunk.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RetrievedContext
Chunk from context retrieved by the retrieval tools.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Web
Chunk from the web.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GroundingMetadata
Metadata returned to client when grounding is enabled.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GroundingSupport
Grounding support.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
HarmCategory
Harm categories that will block the content.
HttpElementLocation
Enum of location an HTTP element can be.
HyperparameterTuningJob
Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
LabelsEntry
The abstract base class for a message.
IdMatcher
Matcher for Features of an EntityType by Feature ID.
ImportDataConfig
Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AnnotationLabelsEntry
The abstract base class for a message.
DataItemLabelsEntry
The abstract base class for a message.
ImportDataOperationMetadata
Runtime operation information for DatasetService.ImportData.
ImportDataRequest
Request message for DatasetService.ImportData.
ImportDataResponse
Response message for DatasetService.ImportData.
ImportExtensionOperationMetadata
Details of ExtensionRegistryService.ImportExtension operation.
ImportExtensionRequest
Request message for ExtensionRegistryService.ImportExtension.
ImportFeatureValuesOperationMetadata
Details of operations that perform import Feature values.
ImportFeatureValuesRequest
Request message for FeaturestoreService.ImportFeatureValues.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureSpec
Defines the Feature value(s) to import.
ImportFeatureValuesResponse
Response message for FeaturestoreService.ImportFeatureValues.
ImportModelEvaluationRequest
Request message for ModelService.ImportModelEvaluation
ImportRagFilesConfig
Config for importing RagFiles.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ImportRagFilesOperationMetadata
Runtime operation information for VertexRagDataService.ImportRagFiles.
ImportRagFilesRequest
Request message for VertexRagDataService.ImportRagFiles.
ImportRagFilesResponse
Response message for VertexRagDataService.ImportRagFiles.
Index
A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.
IndexUpdateMethod
The update method of an Index.
LabelsEntry
The abstract base class for a message.
IndexDatapoint
A datapoint of Index.
CrowdingTag
Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.
NumericRestriction
This field allows restricts to be based on numeric comparisons rather than categorical tokens.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Operator
Which comparison operator to use. Should be specified for queries only; specifying this for a datapoint is an error.
Datapoints for which Operator is true relative to the query's Value field will be allowlisted.
Restriction
Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).
SparseEmbedding
Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions.
IndexEndpoint
Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
LabelsEntry
The abstract base class for a message.
IndexPrivateEndpoints
IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.
IndexStats
Stats of the Index.
InputDataConfig
Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Int64Array
A list of int64 values.
IntegratedGradientsAttribution
An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
JobState
Describes the state of a job.
LargeModelReference
Contains information about the Large Model.
LineageSubgraph
A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
ListAnnotationsRequest
Request message for DatasetService.ListAnnotations.
ListAnnotationsResponse
Response message for DatasetService.ListAnnotations.
ListArtifactsRequest
Request message for MetadataService.ListArtifacts.
ListArtifactsResponse
Response message for MetadataService.ListArtifacts.
ListBatchPredictionJobsRequest
Request message for JobService.ListBatchPredictionJobs.
ListBatchPredictionJobsResponse
Response message for JobService.ListBatchPredictionJobs
ListCachedContentsRequest
Request to list CachedContents.
ListCachedContentsResponse
Response with a list of CachedContents.
ListContextsRequest
Request message for MetadataService.ListContexts
ListContextsResponse
Response message for MetadataService.ListContexts.
ListCustomJobsRequest
Request message for JobService.ListCustomJobs.
ListCustomJobsResponse
Response message for JobService.ListCustomJobs
ListDataItemsRequest
Request message for DatasetService.ListDataItems.
ListDataItemsResponse
Response message for DatasetService.ListDataItems.
ListDataLabelingJobsRequest
Request message for JobService.ListDataLabelingJobs.
ListDataLabelingJobsResponse
Response message for JobService.ListDataLabelingJobs.
ListDatasetVersionsRequest
Request message for DatasetService.ListDatasetVersions.
ListDatasetVersionsResponse
Response message for DatasetService.ListDatasetVersions.
ListDatasetsRequest
Request message for DatasetService.ListDatasets.
ListDatasetsResponse
Response message for DatasetService.ListDatasets.
ListDeploymentResourcePoolsRequest
Request message for ListDeploymentResourcePools method.
ListDeploymentResourcePoolsResponse
Response message for ListDeploymentResourcePools method.
ListEndpointsRequest
Request message for EndpointService.ListEndpoints.
ListEndpointsResponse
Response message for EndpointService.ListEndpoints.
ListEntityTypesRequest
Request message for FeaturestoreService.ListEntityTypes.
ListEntityTypesResponse
Response message for FeaturestoreService.ListEntityTypes.
ListExecutionsRequest
Request message for MetadataService.ListExecutions.
ListExecutionsResponse
Response message for MetadataService.ListExecutions.
ListExtensionsRequest
Request message for ExtensionRegistryService.ListExtensions.
ListExtensionsResponse
Response message for ExtensionRegistryService.ListExtensions
ListFeatureGroupsRequest
Request message for FeatureRegistryService.ListFeatureGroups.
ListFeatureGroupsResponse
Response message for FeatureRegistryService.ListFeatureGroups.
ListFeatureOnlineStoresRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.
ListFeatureOnlineStoresResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.
ListFeatureViewSyncsRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.
ListFeatureViewSyncsResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.
ListFeatureViewsRequest
Request message for FeatureOnlineStoreAdminService.ListFeatureViews.
ListFeatureViewsResponse
Response message for FeatureOnlineStoreAdminService.ListFeatureViews.
ListFeaturesRequest
Request message for FeaturestoreService.ListFeatures. Request message for FeatureRegistryService.ListFeatures.
ListFeaturesResponse
Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.
ListFeaturestoresRequest
Request message for FeaturestoreService.ListFeaturestores.
ListFeaturestoresResponse
Response message for FeaturestoreService.ListFeaturestores.
ListHyperparameterTuningJobsRequest
Request message for JobService.ListHyperparameterTuningJobs.
ListHyperparameterTuningJobsResponse
Response message for JobService.ListHyperparameterTuningJobs
ListIndexEndpointsRequest
Request message for IndexEndpointService.ListIndexEndpoints.
ListIndexEndpointsResponse
Response message for IndexEndpointService.ListIndexEndpoints.
ListIndexesRequest
Request message for IndexService.ListIndexes.
ListIndexesResponse
Response message for IndexService.ListIndexes.
ListMetadataSchemasRequest
Request message for MetadataService.ListMetadataSchemas.
ListMetadataSchemasResponse
Response message for MetadataService.ListMetadataSchemas.
ListMetadataStoresRequest
Request message for MetadataService.ListMetadataStores.
ListMetadataStoresResponse
Response message for MetadataService.ListMetadataStores.
ListModelDeploymentMonitoringJobsRequest
Request message for JobService.ListModelDeploymentMonitoringJobs.
ListModelDeploymentMonitoringJobsResponse
Response message for JobService.ListModelDeploymentMonitoringJobs.
ListModelEvaluationSlicesRequest
Request message for ModelService.ListModelEvaluationSlices.
ListModelEvaluationSlicesResponse
Response message for ModelService.ListModelEvaluationSlices.
ListModelEvaluationsRequest
Request message for ModelService.ListModelEvaluations.
ListModelEvaluationsResponse
Response message for ModelService.ListModelEvaluations.
ListModelMonitoringJobsRequest
Request message for ModelMonitoringService.ListModelMonitoringJobs.
ListModelMonitoringJobsResponse
Response message for ModelMonitoringService.ListModelMonitoringJobs.
ListModelMonitorsRequest
Request message for ModelMonitoringService.ListModelMonitors.
ListModelMonitorsResponse
Response message for ModelMonitoringService.ListModelMonitors
ListModelVersionsRequest
Request message for ModelService.ListModelVersions.
ListModelVersionsResponse
Response message for ModelService.ListModelVersions
ListModelsRequest
Request message for ModelService.ListModels.
ListModelsResponse
Response message for ModelService.ListModels
ListNasJobsRequest
Request message for JobService.ListNasJobs.
ListNasJobsResponse
Response message for JobService.ListNasJobs
ListNasTrialDetailsRequest
Request message for JobService.ListNasTrialDetails.
ListNasTrialDetailsResponse
Response message for JobService.ListNasTrialDetails
ListNotebookExecutionJobsRequest
Request message for [NotebookService.ListNotebookExecutionJobs]
ListNotebookExecutionJobsResponse
Response message for [NotebookService.CreateNotebookExecutionJob]
ListNotebookRuntimeTemplatesRequest
Request message for NotebookService.ListNotebookRuntimeTemplates.
ListNotebookRuntimeTemplatesResponse
Response message for NotebookService.ListNotebookRuntimeTemplates.
ListNotebookRuntimesRequest
Request message for NotebookService.ListNotebookRuntimes.
ListNotebookRuntimesResponse
Response message for NotebookService.ListNotebookRuntimes.
ListOptimalTrialsRequest
Request message for VizierService.ListOptimalTrials.
ListOptimalTrialsResponse
Response message for VizierService.ListOptimalTrials.
ListPersistentResourcesRequest
Request message for [PersistentResourceService.ListPersistentResource][].
ListPersistentResourcesResponse
Response message for PersistentResourceService.ListPersistentResources
ListPipelineJobsRequest
Request message for PipelineService.ListPipelineJobs.
ListPipelineJobsResponse
Response message for PipelineService.ListPipelineJobs
ListPublisherModelsRequest
Request message for ModelGardenService.ListPublisherModels.
ListPublisherModelsResponse
Response message for ModelGardenService.ListPublisherModels.
ListRagCorporaRequest
Request message for VertexRagDataService.ListRagCorpora.
ListRagCorporaResponse
Response message for VertexRagDataService.ListRagCorpora.
ListRagFilesRequest
Request message for VertexRagDataService.ListRagFiles.
ListRagFilesResponse
Response message for VertexRagDataService.ListRagFiles.
ListReasoningEnginesRequest
Request message for ReasoningEngineService.ListReasoningEngines.
ListReasoningEnginesResponse
Response message for ReasoningEngineService.ListReasoningEngines
ListSavedQueriesRequest
Request message for DatasetService.ListSavedQueries.
ListSavedQueriesResponse
Response message for DatasetService.ListSavedQueries.
ListSchedulesRequest
Request message for ScheduleService.ListSchedules.
ListSchedulesResponse
Response message for ScheduleService.ListSchedules
ListSpecialistPoolsRequest
Request message for SpecialistPoolService.ListSpecialistPools.
ListSpecialistPoolsResponse
Response message for SpecialistPoolService.ListSpecialistPools.
ListStudiesRequest
Request message for VizierService.ListStudies.
ListStudiesResponse
Response message for VizierService.ListStudies.
ListTensorboardExperimentsRequest
Request message for TensorboardService.ListTensorboardExperiments.
ListTensorboardExperimentsResponse
Response message for TensorboardService.ListTensorboardExperiments.
ListTensorboardRunsRequest
Request message for TensorboardService.ListTensorboardRuns.
ListTensorboardRunsResponse
Response message for TensorboardService.ListTensorboardRuns.
ListTensorboardTimeSeriesRequest
Request message for TensorboardService.ListTensorboardTimeSeries.
ListTensorboardTimeSeriesResponse
Response message for TensorboardService.ListTensorboardTimeSeries.
ListTensorboardsRequest
Request message for TensorboardService.ListTensorboards.
ListTensorboardsResponse
Response message for TensorboardService.ListTensorboards.
ListTrainingPipelinesRequest
Request message for PipelineService.ListTrainingPipelines.
ListTrainingPipelinesResponse
Response message for PipelineService.ListTrainingPipelines
ListTrialsRequest
Request message for VizierService.ListTrials.
ListTrialsResponse
Response message for VizierService.ListTrials.
ListTuningJobsRequest
Request message for GenAiTuningService.ListTuningJobs.
ListTuningJobsResponse
Response message for GenAiTuningService.ListTuningJobs
LookupStudyRequest
Request message for VizierService.LookupStudy.
MachineSpec
Specification of a single machine.
ManualBatchTuningParameters
Manual batch tuning parameters.
Measurement
A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
Metric
A message representing a metric in the measurement.
MergeVersionAliasesRequest
Request message for ModelService.MergeVersionAliases.
MetadataSchema
Instance of a general MetadataSchema.
MetadataSchemaType
Describes the type of the MetadataSchema.
MetadataStore
Instance of a metadata store. Contains a set of metadata that can be queried.
DataplexConfig
Represents Dataplex integration settings.
MetadataStoreState
Represents state information for a MetadataStore.
MigratableResource
Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutomlDataset
Represents one Dataset in automl.googleapis.com.
AutomlModel
Represents one Model in automl.googleapis.com.
DataLabelingDataset
Represents one Dataset in datalabeling.googleapis.com.
DataLabelingAnnotatedDataset
Represents one AnnotatedDataset in datalabeling.googleapis.com.
MlEngineModelVersion
Represents one model Version in ml.googleapis.com.
MigrateResourceRequest
Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MigrateAutomlDatasetConfig
Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.
MigrateAutomlModelConfig
Config for migrating Model in automl.googleapis.com to Vertex AI's Model.
MigrateDataLabelingDatasetConfig
Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.
MigrateDataLabelingAnnotatedDatasetConfig
Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.
MigrateMlEngineModelVersionConfig
Config for migrating version in ml.googleapis.com to Vertex AI's Model.
MigrateResourceResponse
Describes a successfully migrated resource.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Model
A trained machine learning Model.
BaseModelSource
User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DeploymentResourcesType
Identifies a type of Model's prediction resources.
ExportFormat
Represents export format supported by the Model. All formats export to Google Cloud Storage.
ExportableContent
The Model content that can be exported.
LabelsEntry
The abstract base class for a message.
OriginalModelInfo
Contains information about the original Model if this Model is a copy.
ModelContainerSpec
Specification of a container for serving predictions. Some fields in
this message correspond to fields in the Kubernetes Container v1
core
specification <https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core>
__.
ModelDeploymentMonitoringBigQueryTable
ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.
LogSource
Indicates where does the log come from.
LogType
Indicates what type of traffic does the log belong to.
ModelDeploymentMonitoringJob
Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.
LabelsEntry
The abstract base class for a message.
LatestMonitoringPipelineMetadata
All metadata of most recent monitoring pipelines.
MonitoringScheduleState
The state to Specify the monitoring pipeline.
ModelDeploymentMonitoringObjectiveConfig
ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.
ModelDeploymentMonitoringObjectiveType
The Model Monitoring Objective types.
ModelDeploymentMonitoringScheduleConfig
The config for scheduling monitoring job.
ModelEvaluation
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
BiasConfig
Configuration for bias detection.
ModelEvaluationExplanationSpec
ModelEvaluationSlice
A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.
Slice
Definition of a slice.
SliceSpec
Specification for how the data should be sliced.
ConfigsEntry
The abstract base class for a message.
Range
A range of values for slice(s). low
is inclusive, high
is
exclusive.
SliceConfig
Specification message containing the config for this SliceSpec. When
kind
is selected as value
and/or range
, only a single
slice will be computed. When all_values
is present, a separate
slice will be computed for each possible label/value for the
corresponding key in config
. Examples, with feature zip_code
with values 12345, 23334, 88888 and feature country with values
"US", "Canada", "Mexico" in the dataset:
Example 1:
::
{
"zip_code": { "value": { "float_value": 12345.0 } }
}
A single slice for any data with zip_code 12345 in the dataset.
Example 2:
::
{
"zip_code": { "range": { "low": 12345, "high": 20000 } }
}
A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice.
Example 3:
::
{
"zip_code": { "range": { "low": 10000, "high": 20000 } },
"country": { "value": { "string_value": "US" } }
}
A single slice containing data where the zip_codes between 10000 and 20000 has the country "US". For this example, data with the zip_code of 12345 and country "US" will be in this slice.
Example 4:
::
{ "country": {"all_values": { "value": true } } }
Three slices are computed, one for each unique country in the dataset.
Example 5:
::
{
"country": { "all_values": { "value": true } },
"zip_code": { "value": { "float_value": 12345.0 } }
}
Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country "US" will be in one slice, zip_code 12345 and country "Canada" in another slice, and zip_code 12345 and country "Mexico" in another slice, totaling 3 slices.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Value
Single value that supports strings and floats.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelExplanation
Aggregated explanation metrics for a Model over a set of instances.
ModelGardenSource
Contains information about the source of the models generated from Model Garden.
ModelMonitor
Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelMonitoringTarget
The monitoring target refers to the entity that is subject to analysis. e.g. Vertex AI Model version.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VertexModelSource
Model in Vertex AI Model Registry.
ModelMonitoringAlert
Represents a single monitoring alert. This is currently used in the SearchModelMonitoringAlerts api, thus the alert wrapped in this message belongs to the resource asked in the request.
ModelMonitoringAlertCondition
Monitoring alert triggered condition.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelMonitoringAlertConfig
The alert config for model monitoring.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
EmailAlertConfig
The config for email alert.
ModelMonitoringAnomaly
Represents a single model monitoring anomaly.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TabularAnomaly
Tabular anomaly details.
ModelMonitoringConfig
The model monitoring configuration used for Batch Prediction Job.
ModelMonitoringInput
Model monitoring data input spec.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
BatchPredictionOutput
Data from Vertex AI Batch prediction job output.
ModelMonitoringDataset
Input dataset spec.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelMonitoringBigQuerySource
Dataset spec for data sotred in BigQuery.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelMonitoringGcsSource
Dataset spec for data stored in Google Cloud Storage.
DataFormat
Supported data format.
TimeOffset
Time offset setting.
VertexEndpointLogs
Data from Vertex AI Endpoint request response logging.
ModelMonitoringJob
Represents a model monitoring job that analyze dataset using different monitoring algorithm.
ModelMonitoringJobExecutionDetail
Represent the execution details of the job.
ObjectiveStatusEntry
The abstract base class for a message.
ProcessedDataset
Processed dataset information.
ModelMonitoringNotificationSpec
Notification spec(email, notification channel) for model monitoring statistics/alerts.
EmailConfig
The config for email alerts.
NotificationChannelConfig
Google Cloud Notification Channel config.
ModelMonitoringObjectiveConfig
The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.
ExplanationConfig
The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.
ExplanationBaseline
Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PredictionFormat
The storage format of the predictions generated BatchPrediction job.
PredictionDriftDetectionConfig
The config for Prediction data drift detection.
AttributionScoreDriftThresholdsEntry
The abstract base class for a message.
DriftThresholdsEntry
The abstract base class for a message.
TrainingDataset
Training Dataset information.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TrainingPredictionSkewDetectionConfig
The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.
AttributionScoreSkewThresholdsEntry
The abstract base class for a message.
SkewThresholdsEntry
The abstract base class for a message.
ModelMonitoringObjectiveSpec
Monitoring objectives spec.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DataDriftSpec
Data drift monitoring spec. Data drift measures the distribution distance between the current dataset and a baseline dataset. A typical use case is to detect data drift between the recent production serving dataset and the training dataset, or to compare the recent production dataset with a dataset from a previous period.
FeatureAlertConditionsEntry
The abstract base class for a message.
FeatureAttributionSpec
Feature attribution monitoring spec.
FeatureAlertConditionsEntry
The abstract base class for a message.
TabularObjective
Tabular monitoring objective.
ModelMonitoringOutputSpec
Specification for the export destination of monitoring results, including metrics, logs, etc.
ModelMonitoringSchema
The Model Monitoring Schema definition.
FieldSchema
Schema field definition.
ModelMonitoringSpec
Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports.
ModelMonitoringStats
Represents the collection of statistics for a metric.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ModelMonitoringStatsAnomalies
Statistics and anomalies generated by Model Monitoring.
FeatureHistoricStatsAnomalies
Historical Stats (and Anomalies) for a specific Feature.
ModelMonitoringStatsDataPoint
Represents a single statistics data point.
TypedValue
Typed value of the statistics.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DistributionDataValue
Summary statistics for a population of values.
ModelMonitoringTabularStats
A collection of data points that describes the time-varying values of a tabular metric.
ModelSourceInfo
Detail description of the source information of the model.
ModelSourceType
Source of the model. Different from objective
field, this
ModelSourceType
enum indicates the source from which the model
was accessed or obtained, whereas the objective
indicates the
overall aim or function of this model.
MutateDeployedIndexOperationMetadata
Runtime operation information for IndexEndpointService.MutateDeployedIndex.
MutateDeployedIndexRequest
Request message for IndexEndpointService.MutateDeployedIndex.
MutateDeployedIndexResponse
Response message for IndexEndpointService.MutateDeployedIndex.
MutateDeployedModelOperationMetadata
Runtime operation information for EndpointService.MutateDeployedModel.
MutateDeployedModelRequest
Request message for EndpointService.MutateDeployedModel.
MutateDeployedModelResponse
Response message for EndpointService.MutateDeployedModel.
NasJob
Represents a Neural Architecture Search (NAS) job.
LabelsEntry
The abstract base class for a message.
NasJobOutput
Represents a uCAIP NasJob output.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MultiTrialJobOutput
The output of a multi-trial Neural Architecture Search (NAS) jobs.
NasJobSpec
Represents the spec of a NasJob.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
MultiTrialAlgorithmSpec
The spec of multi-trial Neural Architecture Search (NAS).
MetricSpec
Represents a metric to optimize.
GoalType
The available types of optimization goals.
MultiTrialAlgorithm
The available types of multi-trial algorithms.
SearchTrialSpec
Represent spec for search trials.
TrainTrialSpec
Represent spec for train trials.
NasTrial
Represents a uCAIP NasJob trial.
State
Describes a NasTrial state.
NasTrialDetail
Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.
NearestNeighborQuery
A query to find a number of similar entities.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Embedding
The embedding vector.
Parameters
Parameters that can be overrided in each query to tune query latency and recall.
StringFilter
String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.
NearestNeighborSearchOperationMetadata
Runtime operation metadata with regard to Matching Engine Index.
ContentValidationStats
RecordError
RecordErrorType
NearestNeighbors
Nearest neighbors for one query.
Neighbor
A neighbor of the query vector.
Neighbor
Neighbors for example-based explanations.
NetworkSpec
Network spec.
NfsMount
Represents a mount configuration for Network File System (NFS) to mount.
NotebookEucConfig
The euc configuration of NotebookRuntimeTemplate.
NotebookExecutionJob
NotebookExecutionJob represents an instance of a notebook execution.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DataformRepositorySource
The Dataform Repository containing the input notebook.
DirectNotebookSource
The content of the input notebook in ipynb format.
GcsNotebookSource
The Cloud Storage uri for the input notebook.
LabelsEntry
The abstract base class for a message.
NotebookExecutionJobView
Views for Get/List NotebookExecutionJob
NotebookIdleShutdownConfig
The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.
NotebookRuntime
A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.
HealthState
The substate of the NotebookRuntime to display health information.
LabelsEntry
The abstract base class for a message.
RuntimeState
The substate of the NotebookRuntime to display state of runtime. The resource of NotebookRuntime is in ACTIVE state for these sub state.
NotebookRuntimeTemplate
A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.
LabelsEntry
The abstract base class for a message.
NotebookRuntimeTemplateRef
Points to a NotebookRuntimeTemplateRef.
NotebookRuntimeType
Represents a notebook runtime type.
PairwiseChoice
Pairwise prediction autorater preference.
PairwiseQuestionAnsweringQualityInput
Input for pairwise question answering quality metric.
PairwiseQuestionAnsweringQualityInstance
Spec for pairwise question answering quality instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PairwiseQuestionAnsweringQualityResult
Spec for pairwise question answering quality result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PairwiseQuestionAnsweringQualitySpec
Spec for pairwise question answering quality score metric.
PairwiseSummarizationQualityInput
Input for pairwise summarization quality metric.
PairwiseSummarizationQualityInstance
Spec for pairwise summarization quality instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PairwiseSummarizationQualityResult
Spec for pairwise summarization quality result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PairwiseSummarizationQualitySpec
Spec for pairwise summarization quality score metric.
Part
A datatype containing media that is part of a multi-part Content
message.
A Part
consists of data which has an associated datatype. A
Part
can only contain one of the accepted types in
Part.data
.
A Part
must have a fixed IANA MIME type identifying the type and
subtype of the media if inline_data
or file_data
field is
filled with raw bytes.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
PauseModelDeploymentMonitoringJobRequest
Request message for JobService.PauseModelDeploymentMonitoringJob.
PauseScheduleRequest
Request message for ScheduleService.PauseSchedule.
PersistentDiskSpec
Represents the spec of [persistent disk][https://cloud.google.com/compute/docs/disks/persistent-disks] options.
PersistentResource
Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.
LabelsEntry
The abstract base class for a message.
State
Describes the PersistentResource state.
PipelineFailurePolicy
Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
PipelineJob
An instance of a machine learning PipelineJob.
LabelsEntry
The abstract base class for a message.
RuntimeConfig
The runtime config of a PipelineJob.
InputArtifact
The type of an input artifact.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
InputArtifactsEntry
The abstract base class for a message.
ParameterValuesEntry
The abstract base class for a message.
ParametersEntry
The abstract base class for a message.
PipelineJobDetail
The runtime detail of PipelineJob.
PipelineState
Describes the state of a pipeline.
PipelineTaskDetail
The runtime detail of a task execution.
ArtifactList
A list of artifact metadata.
InputsEntry
The abstract base class for a message.
OutputsEntry
The abstract base class for a message.
PipelineTaskStatus
A single record of the task status.
State
Specifies state of TaskExecution
PipelineTaskExecutorDetail
The runtime detail of a pipeline executor.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ContainerDetail
The detail of a container execution. It contains the job names of the lifecycle of a container execution.
CustomJobDetail
The detailed info for a custom job executor.
PipelineTemplateMetadata
Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.
Port
Represents a network port in a container.
PredefinedSplit
Assigns input data to training, validation, and test sets based on the value of a provided key.
Supported only for tabular Datasets.
PredictRequest
Request message for PredictionService.Predict.
PredictRequestResponseLoggingConfig
Configuration for logging request-response to a BigQuery table.
PredictResponse
Response message for PredictionService.Predict.
PredictSchemata
Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.
Presets
Preset configuration for example-based explanations
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Modality
Preset option controlling parameters for different modalities
Query
Preset option controlling parameters for query speed-precision trade-off
PrivateEndpoints
PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.
PrivateServiceConnectConfig
Represents configuration for private service connect.
Probe
Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExecAction
ExecAction specifies a command to execute.
PscAutomatedEndpoints
PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.
PublisherModel
A Model Garden Publisher Model.
CallToAction
Actions could take on this Publisher Model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Deploy
Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DeployMetadata
Metadata information about the deployment for managing deployment config.
LabelsEntry
The abstract base class for a message.
DeployGke
Configurations for PublisherModel GKE deployment
OpenFineTuningPipelines
Open fine tuning pipelines.
OpenNotebooks
Open notebooks.
RegionalResourceReferences
The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc..
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ReferencesEntry
The abstract base class for a message.
ViewRestApi
Rest API docs.
Documentation
A named piece of documentation.
LaunchStage
An enum representing the launch stage of a PublisherModel.
OpenSourceCategory
An enum representing the open source category of a PublisherModel.
Parent
The information about the parent of a model.
ResourceReference
Reference to a resource.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VersionState
An enum representing the state of the PublicModelVersion.
PublisherModelView
View enumeration of PublisherModel.
PurgeArtifactsMetadata
Details of operations that perform MetadataService.PurgeArtifacts.
PurgeArtifactsRequest
Request message for MetadataService.PurgeArtifacts.
PurgeArtifactsResponse
Response message for MetadataService.PurgeArtifacts.
PurgeContextsMetadata
Details of operations that perform MetadataService.PurgeContexts.
PurgeContextsRequest
Request message for MetadataService.PurgeContexts.
PurgeContextsResponse
Response message for MetadataService.PurgeContexts.
PurgeExecutionsMetadata
Details of operations that perform MetadataService.PurgeExecutions.
PurgeExecutionsRequest
Request message for MetadataService.PurgeExecutions.
PurgeExecutionsResponse
Response message for MetadataService.PurgeExecutions.
PythonPackageSpec
The spec of a Python packaged code.
QueryArtifactLineageSubgraphRequest
Request message for MetadataService.QueryArtifactLineageSubgraph.
QueryContextLineageSubgraphRequest
Request message for MetadataService.QueryContextLineageSubgraph.
QueryDeployedModelsRequest
Request message for QueryDeployedModels method.
QueryDeployedModelsResponse
Response message for QueryDeployedModels method.
QueryExecutionInputsAndOutputsRequest
Request message for MetadataService.QueryExecutionInputsAndOutputs.
QueryExtensionRequest
Request message for ExtensionExecutionService.QueryExtension.
QueryExtensionResponse
Response message for ExtensionExecutionService.QueryExtension.
QueryReasoningEngineRequest
Request message for [ReasoningEngineExecutionService.Query][].
QueryReasoningEngineResponse
Response message for [ReasoningEngineExecutionService.Query][]
QuestionAnsweringCorrectnessInput
Input for question answering correctness metric.
QuestionAnsweringCorrectnessInstance
Spec for question answering correctness instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringCorrectnessResult
Spec for question answering correctness result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringCorrectnessSpec
Spec for question answering correctness metric.
QuestionAnsweringHelpfulnessInput
Input for question answering helpfulness metric.
QuestionAnsweringHelpfulnessInstance
Spec for question answering helpfulness instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringHelpfulnessResult
Spec for question answering helpfulness result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringHelpfulnessSpec
Spec for question answering helpfulness metric.
QuestionAnsweringQualityInput
Input for question answering quality metric.
QuestionAnsweringQualityInstance
Spec for question answering quality instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringQualityResult
Spec for question answering quality result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringQualitySpec
Spec for question answering quality score metric.
QuestionAnsweringRelevanceInput
Input for question answering relevance metric.
QuestionAnsweringRelevanceInstance
Spec for question answering relevance instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringRelevanceResult
Spec for question answering relevance result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
QuestionAnsweringRelevanceSpec
Spec for question answering relevance metric.
RagContexts
Relevant contexts for one query.
Context
A context of the query.
RagCorpus
A RagCorpus is a RagFile container and a project can have multiple RagCorpora.
RagEmbeddingModelConfig
Config for the embedding model to use for RAG.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VertexPredictionEndpoint
Config representing a model hosted on Vertex Prediction Endpoint.
RagFile
A RagFile contains user data for chunking, embedding and indexing.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RagFileType
The type of the RagFile.
RagFileChunkingConfig
Specifies the size and overlap of chunks for RagFiles.
RagQuery
A query to retrieve relevant contexts.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RawPredictRequest
Request message for PredictionService.RawPredict.
RayMetricSpec
Configuration for the Ray metrics.
RaySpec
Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.
ResourcePoolImagesEntry
The abstract base class for a message.
ReadFeatureValuesRequest
Request message for FeaturestoreOnlineServingService.ReadFeatureValues.
ReadFeatureValuesResponse
Response message for FeaturestoreOnlineServingService.ReadFeatureValues.
EntityView
Entity view with Feature values.
Data
Container to hold value(s), successive in time, for one Feature from the request.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
FeatureDescriptor
Metadata for requested Features.
Header
Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features.
ReadIndexDatapointsRequest
The request message for MatchService.ReadIndexDatapoints.
ReadIndexDatapointsResponse
The response message for MatchService.ReadIndexDatapoints.
ReadTensorboardBlobDataRequest
Request message for TensorboardService.ReadTensorboardBlobData.
ReadTensorboardBlobDataResponse
Response message for TensorboardService.ReadTensorboardBlobData.
ReadTensorboardSizeRequest
Request message for TensorboardService.ReadTensorboardSize.
ReadTensorboardSizeResponse
Response message for TensorboardService.ReadTensorboardSize.
ReadTensorboardTimeSeriesDataRequest
Request message for TensorboardService.ReadTensorboardTimeSeriesData.
ReadTensorboardTimeSeriesDataResponse
Response message for TensorboardService.ReadTensorboardTimeSeriesData.
ReadTensorboardUsageRequest
Request message for TensorboardService.ReadTensorboardUsage.
ReadTensorboardUsageResponse
Response message for TensorboardService.ReadTensorboardUsage.
MonthlyUsageDataEntry
The abstract base class for a message.
PerMonthUsageData
Per month usage data
PerUserUsageData
Per user usage data.
ReasoningEngine
ReasoningEngine provides a customizable runtime for models to determine which actions to take and in which order.
ReasoningEngineSpec
ReasoningEngine configurations
PackageSpec
User provided package spec like pickled object and package requirements.
RebootPersistentResourceOperationMetadata
Details of operations that perform reboot PersistentResource.
RebootPersistentResourceRequest
Request message for PersistentResourceService.RebootPersistentResource.
RemoveContextChildrenRequest
Request message for [MetadataService.DeleteContextChildrenRequest][].
RemoveContextChildrenResponse
Response message for MetadataService.RemoveContextChildren.
RemoveDatapointsRequest
Request message for IndexService.RemoveDatapoints
RemoveDatapointsResponse
Response message for IndexService.RemoveDatapoints
ResourcePool
Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
AutoscalingSpec
The min/max number of replicas allowed if enabling autoscaling
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ResourceRuntime
Persistent Cluster runtime information as output
AccessUrisEntry
The abstract base class for a message.
ResourceRuntimeSpec
Configuration for the runtime on a PersistentResource instance, including but not limited to:
- Service accounts used to run the workloads.
- Whether to make it a dedicated Ray Cluster.
ResourcesConsumed
Statistics information about resource consumption.
RestoreDatasetVersionOperationMetadata
Runtime operation information for DatasetService.RestoreDatasetVersion.
RestoreDatasetVersionRequest
Request message for DatasetService.RestoreDatasetVersion.
ResumeModelDeploymentMonitoringJobRequest
Request message for JobService.ResumeModelDeploymentMonitoringJob.
ResumeScheduleRequest
Request message for ScheduleService.ResumeSchedule.
Retrieval
Defines a retrieval tool that model can call to access external knowledge.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RetrieveContextsRequest
Request message for VertexRagService.RetrieveContexts.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VertexRagStore
The data source for Vertex RagStore.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RagResource
The definition of the Rag resource.
RetrieveContextsResponse
Response message for VertexRagService.RetrieveContexts.
RougeInput
Input for rouge metric.
RougeInstance
Spec for rouge instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RougeMetricValue
Rouge metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RougeResults
Results for rouge metric.
RougeSpec
Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1.
RuntimeConfig
Runtime configuration to run the extension.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CodeInterpreterRuntimeConfig
VertexAISearchRuntimeConfig
SafetyInput
Input for safety metric.
SafetyInstance
Spec for safety instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SafetyRating
Safety rating corresponding to the generated content.
HarmProbability
Harm probability levels in the content.
HarmSeverity
Harm severity levels.
SafetyResult
Spec for safety result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SafetySetting
Safety settings.
HarmBlockMethod
Probability vs severity.
HarmBlockThreshold
Probability based thresholds levels for blocking.
SafetySpec
Spec for safety metric.
SampleConfig
Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SampleStrategy
Sample strategy decides which subset of DataItems should be selected for human labeling in every batch.
SampledShapleyAttribution
An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
SamplingStrategy
Sampling Strategy for logging, can be for both training and prediction dataset.
RandomSampleConfig
Requests are randomly selected.
SavedQuery
A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
Scalar
One point viewable on a scalar metric plot.
Schedule
An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RunResponse
Status of a scheduled run.
State
Possible state of the schedule.
Scheduling
All parameters related to queuing and scheduling of custom jobs.
Schema
Schema is used to define the format of input/output data. Represents
a select subset of an OpenAPI 3.0 schema
object <https://spec.openapis.org/oas/v3.0.3#schema>
__. More fields
may be added in the future as needed.
PropertiesEntry
The abstract base class for a message.
SearchDataItemsRequest
Request message for DatasetService.SearchDataItems.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
OrderByAnnotation
Expression that allows ranking results based on annotation's property.
SearchDataItemsResponse
Response message for DatasetService.SearchDataItems.
SearchEntryPoint
Google search entry point.
SearchFeaturesRequest
Request message for FeaturestoreService.SearchFeatures.
SearchFeaturesResponse
Response message for FeaturestoreService.SearchFeatures.
SearchMigratableResourcesRequest
Request message for MigrationService.SearchMigratableResources.
SearchMigratableResourcesResponse
Response message for MigrationService.SearchMigratableResources.
SearchModelDeploymentMonitoringStatsAnomaliesRequest
Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.
StatsAnomaliesObjective
Stats requested for specific objective.
SearchModelDeploymentMonitoringStatsAnomaliesResponse
Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.
SearchModelMonitoringAlertsRequest
Request message for ModelMonitoringService.SearchModelMonitoringAlerts.
SearchModelMonitoringAlertsResponse
Response message for ModelMonitoringService.SearchModelMonitoringAlerts.
SearchModelMonitoringStatsFilter
Filter for searching ModelMonitoringStats.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TabularStatsFilter
Tabular statistics filter.
SearchModelMonitoringStatsRequest
Request message for ModelMonitoringService.SearchModelMonitoringStats.
SearchModelMonitoringStatsResponse
Response message for ModelMonitoringService.SearchModelMonitoringStats.
SearchNearestEntitiesRequest
The request message for FeatureOnlineStoreService.SearchNearestEntities.
SearchNearestEntitiesResponse
Response message for FeatureOnlineStoreService.SearchNearestEntities
Segment
Segment of the content.
ServiceAccountSpec
Configuration for the use of custom service account to run the workloads.
ShieldedVmConfig
A set of Shielded Instance options. See Images using supported
Shielded VM
features <https://cloud.google.com/compute/docs/instances/modifying-shielded-vm>
__.
SmoothGradConfig
Config for SmoothGrad approximation of gradients.
When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details:
https://arxiv.org/pdf/1706.03825.pdf
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SpecialistPool
SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.
StartNotebookRuntimeOperationMetadata
Metadata information for NotebookService.StartNotebookRuntime.
StartNotebookRuntimeRequest
Request message for NotebookService.StartNotebookRuntime.
StartNotebookRuntimeResponse
Response message for NotebookService.StartNotebookRuntime.
StopTrialRequest
Request message for VizierService.StopTrial.
StratifiedSplit
Assigns input data to the training, validation, and test sets so
that the distribution of values found in the categorical column (as
specified by the key
field) is mirrored within each split. The
fraction values determine the relative sizes of the splits.
For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C".
Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned.
Supported only for tabular Datasets.
StreamDirectPredictRequest
Request message for PredictionService.StreamDirectPredict.
The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
StreamDirectPredictResponse
Response message for PredictionService.StreamDirectPredict.
StreamDirectRawPredictRequest
Request message for PredictionService.StreamDirectRawPredict.
The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
StreamDirectRawPredictResponse
Response message for PredictionService.StreamDirectRawPredict.
StreamRawPredictRequest
Request message for PredictionService.StreamRawPredict.
StreamingFetchFeatureValuesRequest
Request message for FeatureOnlineStoreService.StreamingFetchFeatureValues. For the entities requested, all features under the requested feature view will be returned.
StreamingFetchFeatureValuesResponse
Response message for FeatureOnlineStoreService.StreamingFetchFeatureValues.
StreamingPredictRequest
Request message for PredictionService.StreamingPredict.
The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].
StreamingPredictResponse
Response message for PredictionService.StreamingPredict.
StreamingRawPredictRequest
Request message for PredictionService.StreamingRawPredict.
The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.
StreamingRawPredictResponse
Response message for PredictionService.StreamingRawPredict.
StreamingReadFeatureValuesRequest
Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].
StringArray
A list of string values.
StructFieldValue
One field of a Struct (or object) type feature value.
StructValue
Struct (or object) type feature value.
Study
A message representing a Study.
State
Describes the Study state.
StudySpec
Represents specification of a Study.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Algorithm
The available search algorithms for the Study.
ConvexAutomatedStoppingSpec
Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ConvexStopConfig
Configuration for ConvexStopPolicy.
DecayCurveAutomatedStoppingSpec
The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.
MeasurementSelectionType
This indicates which measurement to use if/when the service automatically selects the final measurement from previously reported intermediate measurements. Choose this based on two considerations: A) Do you expect your measurements to monotonically improve? If so, choose LAST_MEASUREMENT. On the other hand, if you're in a situation where your system can "over-train" and you expect the performance to get better for a while but then start declining, choose BEST_MEASUREMENT. B) Are your measurements significantly noisy and/or irreproducible? If so, BEST_MEASUREMENT will tend to be over-optimistic, and it may be better to choose LAST_MEASUREMENT. If both or neither of (A) and (B) apply, it doesn't matter which selection type is chosen.
MedianAutomatedStoppingSpec
The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.
MetricSpec
Represents a metric to optimize.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
GoalType
The available types of optimization goals.
SafetyMetricConfig
Used in safe optimization to specify threshold levels and risk tolerance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ObservationNoise
Describes the noise level of the repeated observations.
"Noisy" means that the repeated observations with the same Trial parameters may lead to different metric evaluations.
ParameterSpec
Represents a single parameter to optimize.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CategoricalValueSpec
Value specification for a parameter in CATEGORICAL
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ConditionalParameterSpec
Represents a parameter spec with condition from its parent parameter.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
CategoricalValueCondition
Represents the spec to match categorical values from parent parameter.
DiscreteValueCondition
Represents the spec to match discrete values from parent parameter.
IntValueCondition
Represents the spec to match integer values from parent parameter.
DiscreteValueSpec
Value specification for a parameter in DISCRETE
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
DoubleValueSpec
Value specification for a parameter in DOUBLE
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
IntegerValueSpec
Value specification for a parameter in INTEGER
type.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ScaleType
The type of scaling that should be applied to this parameter.
StudyStoppingConfig
The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.
TransferLearningConfig
This contains flag for manually disabling transfer learning for a study. The names of prior studies being used for transfer learning (if any) are also listed here.
StudyTimeConstraint
Time-based Constraint for Study
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SuggestTrialsMetadata
Details of operations that perform Trials suggestion.
SuggestTrialsRequest
Request message for VizierService.SuggestTrials.
SuggestTrialsResponse
Response message for VizierService.SuggestTrials.
SummarizationHelpfulnessInput
Input for summarization helpfulness metric.
SummarizationHelpfulnessInstance
Spec for summarization helpfulness instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationHelpfulnessResult
Spec for summarization helpfulness result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationHelpfulnessSpec
Spec for summarization helpfulness score metric.
SummarizationQualityInput
Input for summarization quality metric.
SummarizationQualityInstance
Spec for summarization quality instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationQualityResult
Spec for summarization quality result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationQualitySpec
Spec for summarization quality score metric.
SummarizationVerbosityInput
Input for summarization verbosity metric.
SummarizationVerbosityInstance
Spec for summarization verbosity instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationVerbosityResult
Spec for summarization verbosity result.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
SummarizationVerbositySpec
Spec for summarization verbosity score metric.
SupervisedHyperParameters
Hyperparameters for SFT.
AdapterSize
Supported adapter sizes for tuning.
SupervisedTuningDataStats
Tuning data statistics for Supervised Tuning.
SupervisedTuningDatasetDistribution
Dataset distribution for Supervised Tuning.
DatasetBucket
Dataset bucket used to create a histogram for the distribution given a population of values.
SupervisedTuningSpec
Tuning Spec for Supervised Tuning.
SyncFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.SyncFeatureView.
SyncFeatureViewResponse
Respose message for FeatureOnlineStoreAdminService.SyncFeatureView.
TFRecordDestination
The storage details for TFRecord output content.
Tensor
A tensor value type.
DataType
Data type of the tensor.
StructValEntry
The abstract base class for a message.
Tensorboard
Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.
LabelsEntry
The abstract base class for a message.
TensorboardBlob
One blob (e.g, image, graph) viewable on a blob metric plot.
TensorboardBlobSequence
One point viewable on a blob metric plot, but mostly just a wrapper
message to work around repeated fields can't be used directly within
oneof
fields.
TensorboardExperiment
A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.
LabelsEntry
The abstract base class for a message.
TensorboardRun
TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
LabelsEntry
The abstract base class for a message.
TensorboardTensor
One point viewable on a tensor metric plot.
TensorboardTimeSeries
TensorboardTimeSeries maps to times series produced in training runs
Metadata
Describes metadata for a TensorboardTimeSeries.
ValueType
An enum representing the value type of a TensorboardTimeSeries.
ThresholdConfig
The config for feature monitoring threshold.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TimeSeriesData
All the data stored in a TensorboardTimeSeries.
TimeSeriesDataPoint
A TensorboardTimeSeries data point.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TimestampSplit
Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set.
Supported only for tabular Datasets.
TokensInfo
Tokens info with a list of tokens and the corresponding list of token ids.
Tool
Tool details that the model may use to generate response.
A Tool
is a piece of code that enables the system to interact
with external systems to perform an action, or set of actions,
outside of knowledge and scope of the model. A Tool object should
contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval
or GoogleSearchRetrieval).
ToolCallValidInput
Input for tool call valid metric.
ToolCallValidInstance
Spec for tool call valid instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolCallValidMetricValue
Tool call valid metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolCallValidResults
Results for tool call valid metric.
ToolCallValidSpec
Spec for tool call valid metric.
ToolConfig
Tool config. This config is shared for all tools provided in the request.
ToolNameMatchInput
Input for tool name match metric.
ToolNameMatchInstance
Spec for tool name match instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolNameMatchMetricValue
Tool name match metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolNameMatchResults
Results for tool name match metric.
ToolNameMatchSpec
Spec for tool name match metric.
ToolParameterKVMatchInput
Input for tool parameter key value match metric.
ToolParameterKVMatchInstance
Spec for tool parameter key value match instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolParameterKVMatchMetricValue
Tool parameter key value match metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolParameterKVMatchResults
Results for tool parameter key value match metric.
ToolParameterKVMatchSpec
Spec for tool parameter key value match metric.
ToolParameterKeyMatchInput
Input for tool parameter key match metric.
ToolParameterKeyMatchInstance
Spec for tool parameter key match instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolParameterKeyMatchMetricValue
Tool parameter key match metric value for an instance.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ToolParameterKeyMatchResults
Results for tool parameter key match metric.
ToolParameterKeyMatchSpec
Spec for tool parameter key match metric.
ToolUseExample
A single example of the tool usage.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
ExtensionOperation
Identifies one operation of the extension.
TrainingConfig
CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
TrainingPipeline
The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.
LabelsEntry
The abstract base class for a message.
Trial
A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.
Parameter
A message representing a parameter to be tuned.
State
Describes a Trial state.
WebAccessUrisEntry
The abstract base class for a message.
TrialContext
Next ID: 3
TunedModel
The Model Registry Model and Online Prediction Endpoint assiociated with this TuningJob.
TuningDataStats
The tuning data statistic values for TuningJob.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
TuningJob
Represents a TuningJob that runs with Google owned models.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
LabelsEntry
The abstract base class for a message.
Type
Type contains the list of OpenAPI data types as defined by https://swagger.io/docs/specification/data-models/data-types/
UndeployIndexOperationMetadata
Runtime operation information for IndexEndpointService.UndeployIndex.
UndeployIndexRequest
Request message for IndexEndpointService.UndeployIndex.
UndeployIndexResponse
Response message for IndexEndpointService.UndeployIndex.
UndeployModelOperationMetadata
Runtime operation information for EndpointService.UndeployModel.
UndeployModelRequest
Request message for EndpointService.UndeployModel.
TrafficSplitEntry
The abstract base class for a message.
UndeployModelResponse
Response message for EndpointService.UndeployModel.
UnmanagedContainerModel
Contains model information necessary to perform batch prediction without requiring a full model import.
UpdateArtifactRequest
Request message for MetadataService.UpdateArtifact.
UpdateCachedContentRequest
Request message for GenAiCacheService.UpdateCachedContent. Only expire_time or ttl can be updated.
UpdateContextRequest
Request message for MetadataService.UpdateContext.
UpdateDatasetRequest
Request message for DatasetService.UpdateDataset.
UpdateDatasetVersionRequest
Request message for DatasetService.UpdateDatasetVersion.
UpdateDeploymentResourcePoolOperationMetadata
Runtime operation information for UpdateDeploymentResourcePool method.
UpdateDeploymentResourcePoolRequest
Request message for UpdateDeploymentResourcePool method.
UpdateEndpointRequest
Request message for EndpointService.UpdateEndpoint.
UpdateEntityTypeRequest
Request message for FeaturestoreService.UpdateEntityType.
UpdateExecutionRequest
Request message for MetadataService.UpdateExecution.
UpdateExplanationDatasetOperationMetadata
Runtime operation information for ModelService.UpdateExplanationDataset.
UpdateExplanationDatasetRequest
Request message for ModelService.UpdateExplanationDataset.
UpdateExplanationDatasetResponse
Response message of ModelService.UpdateExplanationDataset operation.
UpdateExtensionRequest
Request message for ExtensionRegistryService.UpdateExtension.
UpdateFeatureGroupOperationMetadata
Details of operations that perform update FeatureGroup.
UpdateFeatureGroupRequest
Request message for FeatureRegistryService.UpdateFeatureGroup.
UpdateFeatureOnlineStoreOperationMetadata
Details of operations that perform update FeatureOnlineStore.
UpdateFeatureOnlineStoreRequest
Request message for FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore.
UpdateFeatureOperationMetadata
Details of operations that perform update Feature.
UpdateFeatureRequest
Request message for FeaturestoreService.UpdateFeature. Request message for FeatureRegistryService.UpdateFeature.
UpdateFeatureViewOperationMetadata
Details of operations that perform update FeatureView.
UpdateFeatureViewRequest
Request message for FeatureOnlineStoreAdminService.UpdateFeatureView.
UpdateFeaturestoreOperationMetadata
Details of operations that perform update Featurestore.
UpdateFeaturestoreRequest
Request message for FeaturestoreService.UpdateFeaturestore.
UpdateIndexEndpointRequest
Request message for IndexEndpointService.UpdateIndexEndpoint.
UpdateIndexOperationMetadata
Runtime operation information for IndexService.UpdateIndex.
UpdateIndexRequest
Request message for IndexService.UpdateIndex.
UpdateModelDeploymentMonitoringJobOperationMetadata
Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.
UpdateModelDeploymentMonitoringJobRequest
Request message for JobService.UpdateModelDeploymentMonitoringJob.
UpdateModelMonitorOperationMetadata
Runtime operation information for ModelMonitoringService.UpdateModelMonitor.
UpdateModelMonitorRequest
Request message for ModelMonitoringService.UpdateModelMonitor.
UpdateModelRequest
Request message for ModelService.UpdateModel.
UpdateNotebookRuntimeTemplateRequest
Request message for NotebookService.UpdateNotebookRuntimeTemplate.
UpdatePersistentResourceOperationMetadata
Details of operations that perform update PersistentResource.
UpdatePersistentResourceRequest
Request message for UpdatePersistentResource method.
UpdateReasoningEngineOperationMetadata
Details of ReasoningEngineService.UpdateReasoningEngine operation.
UpdateReasoningEngineRequest
Request message for ReasoningEngineService.UpdateReasoningEngine.
UpdateScheduleRequest
Request message for ScheduleService.UpdateSchedule.
UpdateSpecialistPoolOperationMetadata
Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool.
UpdateSpecialistPoolRequest
Request message for SpecialistPoolService.UpdateSpecialistPool.
UpdateTensorboardExperimentRequest
Request message for TensorboardService.UpdateTensorboardExperiment.
UpdateTensorboardOperationMetadata
Details of operations that perform update Tensorboard.
UpdateTensorboardRequest
Request message for TensorboardService.UpdateTensorboard.
UpdateTensorboardRunRequest
Request message for TensorboardService.UpdateTensorboardRun.
UpdateTensorboardTimeSeriesRequest
Request message for TensorboardService.UpdateTensorboardTimeSeries.
UpgradeNotebookRuntimeOperationMetadata
Metadata information for NotebookService.UpgradeNotebookRuntime.
UpgradeNotebookRuntimeRequest
Request message for NotebookService.UpgradeNotebookRuntime.
UpgradeNotebookRuntimeResponse
Response message for NotebookService.UpgradeNotebookRuntime.
UploadModelOperationMetadata
Details of ModelService.UploadModel operation.
UploadModelRequest
Request message for ModelService.UploadModel.
UploadModelResponse
Response message of ModelService.UploadModel operation.
UploadRagFileConfig
Config for uploading RagFile.
UploadRagFileRequest
Request message for VertexRagDataService.UploadRagFile.
UploadRagFileResponse
Response message for VertexRagDataService.UploadRagFile.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
UpsertDatapointsRequest
Request message for IndexService.UpsertDatapoints
UpsertDatapointsResponse
Response message for IndexService.UpsertDatapoints
UserActionReference
References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Value
Value is the value of the field.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
VertexAISearch
Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation
VertexRagStore
Retrieve from Vertex RAG Store for grounding.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
RagResource
The definition of the Rag resource.
VideoMetadata
Metadata describes the input video content.
WorkerPoolSpec
Represents the spec of a worker pool in a job.
This message has oneof
_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
WriteFeatureValuesPayload
Contains Feature values to be written for a specific entity.
FeatureValuesEntry
The abstract base class for a message.
WriteFeatureValuesRequest
Request message for FeaturestoreOnlineServingService.WriteFeatureValues.
WriteFeatureValuesResponse
Response message for FeaturestoreOnlineServingService.WriteFeatureValues.
WriteTensorboardExperimentDataRequest
Request message for TensorboardService.WriteTensorboardExperimentData.
WriteTensorboardExperimentDataResponse
Response message for TensorboardService.WriteTensorboardExperimentData.
WriteTensorboardRunDataRequest
Request message for TensorboardService.WriteTensorboardRunData.
WriteTensorboardRunDataResponse
Response message for TensorboardService.WriteTensorboardRunData.
XraiAttribution
An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details:
https://arxiv.org/abs/1906.02825
Supported only by image Models.
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