Package com.google.cloud.aiplatform.v1beta1

Class Model

  • All Implemented Interfaces:
    ModelOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
    public final class Model
extends com.google.protobuf.GeneratedMessageV3
implements ModelOrBuilder
     A trained machine learning Model.
    Protobuf type google.cloud.aiplatform.v1beta1.Model
    See Also:
    Serialized Form

    • Field Detail

      • VERSION_ID_FIELD_NUMBER

        public static final int VERSION_ID_FIELD_NUMBER
        See Also:
        Constant Field Values

      • VERSION_ALIASES_FIELD_NUMBER

        public static final int VERSION_ALIASES_FIELD_NUMBER
        See Also:
        Constant Field Values

      • VERSION_CREATE_TIME_FIELD_NUMBER

        public static final int VERSION_CREATE_TIME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • VERSION_UPDATE_TIME_FIELD_NUMBER

        public static final int VERSION_UPDATE_TIME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • DISPLAY_NAME_FIELD_NUMBER

        public static final int DISPLAY_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • DESCRIPTION_FIELD_NUMBER

        public static final int DESCRIPTION_FIELD_NUMBER
        See Also:
        Constant Field Values

      • VERSION_DESCRIPTION_FIELD_NUMBER

        public static final int VERSION_DESCRIPTION_FIELD_NUMBER
        See Also:
        Constant Field Values

      • PREDICT_SCHEMATA_FIELD_NUMBER

        public static final int PREDICT_SCHEMATA_FIELD_NUMBER
        See Also:
        Constant Field Values

      • METADATA_SCHEMA_URI_FIELD_NUMBER

        public static final int METADATA_SCHEMA_URI_FIELD_NUMBER
        See Also:
        Constant Field Values

      • SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER

        public static final int SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • TRAINING_PIPELINE_FIELD_NUMBER

        public static final int TRAINING_PIPELINE_FIELD_NUMBER
        See Also:
        Constant Field Values

      • CONTAINER_SPEC_FIELD_NUMBER

        public static final int CONTAINER_SPEC_FIELD_NUMBER
        See Also:
        Constant Field Values

      • ARTIFACT_URI_FIELD_NUMBER

        public static final int ARTIFACT_URI_FIELD_NUMBER
        See Also:
        Constant Field Values

      • SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER

        public static final int SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER
        See Also:
        Constant Field Values

      • SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER

        public static final int SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER

        public static final int SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • CREATE_TIME_FIELD_NUMBER

        public static final int CREATE_TIME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • UPDATE_TIME_FIELD_NUMBER

        public static final int UPDATE_TIME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • DEPLOYED_MODELS_FIELD_NUMBER

        public static final int DEPLOYED_MODELS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • EXPLANATION_SPEC_FIELD_NUMBER

        public static final int EXPLANATION_SPEC_FIELD_NUMBER
        See Also:
        Constant Field Values

      • ENCRYPTION_SPEC_FIELD_NUMBER

        public static final int ENCRYPTION_SPEC_FIELD_NUMBER
        See Also:
        Constant Field Values

      • MODEL_SOURCE_INFO_FIELD_NUMBER

        public static final int MODEL_SOURCE_INFO_FIELD_NUMBER
        See Also:
        Constant Field Values

      • ORIGINAL_MODEL_INFO_FIELD_NUMBER

        public static final int ORIGINAL_MODEL_INFO_FIELD_NUMBER
        See Also:
        Constant Field Values

      • METADATA_ARTIFACT_FIELD_NUMBER

        public static final int METADATA_ARTIFACT_FIELD_NUMBER
        See Also:
        Constant Field Values

    • Method Detail

      • newInstance

        protected Object newInstance​(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)
        Overrides:
        newInstance in class com.google.protobuf.GeneratedMessageV3

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetMapField

        protected com.google.protobuf.MapField internalGetMapField​(int number)
        Overrides:
        internalGetMapField in class com.google.protobuf.GeneratedMessageV3

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3

      • getName

        public String getName()
         The resource name of the Model.
        string name = 1;
        Specified by:
        getName in interface ModelOrBuilder
        Returns:
        The name.

      • getNameBytes

        public com.google.protobuf.ByteString getNameBytes()
         The resource name of the Model.
        string name = 1;
        Specified by:
        getNameBytes in interface ModelOrBuilder
        Returns:
        The bytes for name.

      • getVersionId

        public String getVersionId()
         Output only. Immutable. The version ID of the model.
 A new version is committed when a new model version is uploaded or
 trained under an existing model id. It is an auto-incrementing decimal
 number in string representation.
        string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionId in interface ModelOrBuilder
        Returns:
        The versionId.

      • getVersionIdBytes

        public com.google.protobuf.ByteString getVersionIdBytes()
         Output only. Immutable. The version ID of the model.
 A new version is committed when a new model version is uploaded or
 trained under an existing model id. It is an auto-incrementing decimal
 number in string representation.
        string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionIdBytes in interface ModelOrBuilder
        Returns:
        The bytes for versionId.

      • getVersionAliasesList

        public com.google.protobuf.ProtocolStringList getVersionAliasesList()
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Specified by:
        getVersionAliasesList in interface ModelOrBuilder
        Returns:
        A list containing the versionAliases.

      • getVersionAliasesCount

        public int getVersionAliasesCount()
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Specified by:
        getVersionAliasesCount in interface ModelOrBuilder
        Returns:
        The count of versionAliases.

      • getVersionAliases

        public String getVersionAliases​(int index)
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Specified by:
        getVersionAliases in interface ModelOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The versionAliases at the given index.

      • getVersionAliasesBytes

        public com.google.protobuf.ByteString getVersionAliasesBytes​(int index)
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Specified by:
        getVersionAliasesBytes in interface ModelOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the versionAliases at the given index.

      • hasVersionCreateTime

        public boolean hasVersionCreateTime()
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasVersionCreateTime in interface ModelOrBuilder
        Returns:
        Whether the versionCreateTime field is set.

      • getVersionCreateTime

        public com.google.protobuf.Timestamp getVersionCreateTime()
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionCreateTime in interface ModelOrBuilder
        Returns:
        The versionCreateTime.

      • getVersionCreateTimeOrBuilder

        public com.google.protobuf.TimestampOrBuilder getVersionCreateTimeOrBuilder()
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionCreateTimeOrBuilder in interface ModelOrBuilder

      • hasVersionUpdateTime

        public boolean hasVersionUpdateTime()
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasVersionUpdateTime in interface ModelOrBuilder
        Returns:
        Whether the versionUpdateTime field is set.

      • getVersionUpdateTime

        public com.google.protobuf.Timestamp getVersionUpdateTime()
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionUpdateTime in interface ModelOrBuilder
        Returns:
        The versionUpdateTime.

      • getVersionUpdateTimeOrBuilder

        public com.google.protobuf.TimestampOrBuilder getVersionUpdateTimeOrBuilder()
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getVersionUpdateTimeOrBuilder in interface ModelOrBuilder

      • getDisplayName

        public String getDisplayName()
         Required. The display name of the Model.
 The name can be up to 128 characters long and can consist of any UTF-8
 characters.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Specified by:
        getDisplayName in interface ModelOrBuilder
        Returns:
        The displayName.

      • getDisplayNameBytes

        public com.google.protobuf.ByteString getDisplayNameBytes()
         Required. The display name of the Model.
 The name can be up to 128 characters long and can consist of any UTF-8
 characters.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Specified by:
        getDisplayNameBytes in interface ModelOrBuilder
        Returns:
        The bytes for displayName.

      • getDescription

        public String getDescription()
         The description of the Model.
        string description = 3;
        Specified by:
        getDescription in interface ModelOrBuilder
        Returns:
        The description.

      • getDescriptionBytes

        public com.google.protobuf.ByteString getDescriptionBytes()
         The description of the Model.
        string description = 3;
        Specified by:
        getDescriptionBytes in interface ModelOrBuilder
        Returns:
        The bytes for description.

      • getVersionDescription

        public String getVersionDescription()
         The description of this version.
        string version_description = 30;
        Specified by:
        getVersionDescription in interface ModelOrBuilder
        Returns:
        The versionDescription.

      • getVersionDescriptionBytes

        public com.google.protobuf.ByteString getVersionDescriptionBytes()
         The description of this version.
        string version_description = 30;
        Specified by:
        getVersionDescriptionBytes in interface ModelOrBuilder
        Returns:
        The bytes for versionDescription.

      • hasPredictSchemata

        public boolean hasPredictSchemata()
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        .google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;
        Specified by:
        hasPredictSchemata in interface ModelOrBuilder
        Returns:
        Whether the predictSchemata field is set.

      • getPredictSchemata

        public PredictSchemata getPredictSchemata()
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        .google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;
        Specified by:
        getPredictSchemata in interface ModelOrBuilder
        Returns:
        The predictSchemata.

      • getPredictSchemataOrBuilder

        public PredictSchemataOrBuilder getPredictSchemataOrBuilder()
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        .google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;
        Specified by:
        getPredictSchemataOrBuilder in interface ModelOrBuilder

      • getMetadataSchemaUri

        public String getMetadataSchemaUri()
         Immutable. Points to a YAML file stored on Google Cloud Storage describing
 additional information about the Model, that is specific to it. Unset if
 the Model does not have any additional information. The schema is defined
 as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML Models always have this field populated by Vertex AI, if no
 additional metadata is needed, this field is set to an empty string.
 Note: The URI given on output will be immutable and probably different,
 including the URI scheme, than the one given on input. The output URI will
 point to a location where the user only has a read access.
        string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMetadataSchemaUri in interface ModelOrBuilder
        Returns:
        The metadataSchemaUri.

      • getMetadataSchemaUriBytes

        public com.google.protobuf.ByteString getMetadataSchemaUriBytes()
         Immutable. Points to a YAML file stored on Google Cloud Storage describing
 additional information about the Model, that is specific to it. Unset if
 the Model does not have any additional information. The schema is defined
 as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML Models always have this field populated by Vertex AI, if no
 additional metadata is needed, this field is set to an empty string.
 Note: The URI given on output will be immutable and probably different,
 including the URI scheme, than the one given on input. The output URI will
 point to a location where the user only has a read access.
        string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMetadataSchemaUriBytes in interface ModelOrBuilder
        Returns:
        The bytes for metadataSchemaUri.

      • hasMetadata

        public boolean hasMetadata()
         Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
        .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        hasMetadata in interface ModelOrBuilder
        Returns:
        Whether the metadata field is set.

      • getMetadata

        public com.google.protobuf.Value getMetadata()
         Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
        .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMetadata in interface ModelOrBuilder
        Returns:
        The metadata.

      • getMetadataOrBuilder

        public com.google.protobuf.ValueOrBuilder getMetadataOrBuilder()
         Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
        .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getMetadataOrBuilder in interface ModelOrBuilder

      • getSupportedExportFormatsList

        public List<Model.ExportFormat> getSupportedExportFormatsList()
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedExportFormatsList in interface ModelOrBuilder

      • getSupportedExportFormatsOrBuilderList

        public List<? extends Model.ExportFormatOrBuilder> getSupportedExportFormatsOrBuilderList()
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedExportFormatsOrBuilderList in interface ModelOrBuilder

      • getSupportedExportFormatsCount

        public int getSupportedExportFormatsCount()
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedExportFormatsCount in interface ModelOrBuilder

      • getSupportedExportFormats

        public Model.ExportFormat getSupportedExportFormats​(int index)
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedExportFormats in interface ModelOrBuilder

      • getSupportedExportFormatsOrBuilder

        public Model.ExportFormatOrBuilder getSupportedExportFormatsOrBuilder​(int index)
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedExportFormatsOrBuilder in interface ModelOrBuilder

      • getTrainingPipeline

        public String getTrainingPipeline()
         Output only. The resource name of the TrainingPipeline that uploaded this
 Model, if any.
        string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
        Specified by:
        getTrainingPipeline in interface ModelOrBuilder
        Returns:
        The trainingPipeline.

      • getTrainingPipelineBytes

        public com.google.protobuf.ByteString getTrainingPipelineBytes()
         Output only. The resource name of the TrainingPipeline that uploaded this
 Model, if any.
        string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
        Specified by:
        getTrainingPipelineBytes in interface ModelOrBuilder
        Returns:
        The bytes for trainingPipeline.

      • hasContainerSpec

        public boolean hasContainerSpec()
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
        Specified by:
        hasContainerSpec in interface ModelOrBuilder
        Returns:
        Whether the containerSpec field is set.

      • getContainerSpec

        public ModelContainerSpec getContainerSpec()
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
        Specified by:
        getContainerSpec in interface ModelOrBuilder
        Returns:
        The containerSpec.

      • getContainerSpecOrBuilder

        public ModelContainerSpecOrBuilder getContainerSpecOrBuilder()
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
        Specified by:
        getContainerSpecOrBuilder in interface ModelOrBuilder

      • getArtifactUri

        public String getArtifactUri()
         Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getArtifactUri in interface ModelOrBuilder
        Returns:
        The artifactUri.

      • getArtifactUriBytes

        public com.google.protobuf.ByteString getArtifactUriBytes()
         Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getArtifactUriBytes in interface ModelOrBuilder
        Returns:
        The bytes for artifactUri.

      • getSupportedDeploymentResourcesTypesList

        public List<Model.DeploymentResourcesType> getSupportedDeploymentResourcesTypesList()
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob],
 if it has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
        repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedDeploymentResourcesTypesList in interface ModelOrBuilder
        Returns:
        A list containing the supportedDeploymentResourcesTypes.

      • getSupportedDeploymentResourcesTypesCount

        public int getSupportedDeploymentResourcesTypesCount()
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob],
 if it has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
        repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedDeploymentResourcesTypesCount in interface ModelOrBuilder
        Returns:
        The count of supportedDeploymentResourcesTypes.

      • getSupportedDeploymentResourcesTypes

        public Model.DeploymentResourcesType getSupportedDeploymentResourcesTypes​(int index)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob],
 if it has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
        repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedDeploymentResourcesTypes in interface ModelOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The supportedDeploymentResourcesTypes at the given index.

      • getSupportedDeploymentResourcesTypesValueList

        public List<Integer> getSupportedDeploymentResourcesTypesValueList()
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob],
 if it has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
        repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedDeploymentResourcesTypesValueList in interface ModelOrBuilder
        Returns:
        A list containing the enum numeric values on the wire for supportedDeploymentResourcesTypes.

      • getSupportedDeploymentResourcesTypesValue

        public int getSupportedDeploymentResourcesTypesValue​(int index)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob],
 if it has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
        repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedDeploymentResourcesTypesValue in interface ModelOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The enum numeric value on the wire of supportedDeploymentResourcesTypes at the given index.

      • getSupportedInputStorageFormatsList

        public com.google.protobuf.ProtocolStringList getSupportedInputStorageFormatsList()
         Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedInputStorageFormatsList in interface ModelOrBuilder
        Returns:
        A list containing the supportedInputStorageFormats.

      • getSupportedInputStorageFormatsCount

        public int getSupportedInputStorageFormatsCount()
         Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedInputStorageFormatsCount in interface ModelOrBuilder
        Returns:
        The count of supportedInputStorageFormats.

      • getSupportedInputStorageFormats

        public String getSupportedInputStorageFormats​(int index)
         Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedInputStorageFormats in interface ModelOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The supportedInputStorageFormats at the given index.

      • getSupportedInputStorageFormatsBytes

        public com.google.protobuf.ByteString getSupportedInputStorageFormatsBytes​(int index)
         Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedInputStorageFormatsBytes in interface ModelOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the supportedInputStorageFormats at the given index.

      • getSupportedOutputStorageFormatsList

        public com.google.protobuf.ProtocolStringList getSupportedOutputStorageFormatsList()
         Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedOutputStorageFormatsList in interface ModelOrBuilder
        Returns:
        A list containing the supportedOutputStorageFormats.

      • getSupportedOutputStorageFormatsCount

        public int getSupportedOutputStorageFormatsCount()
         Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedOutputStorageFormatsCount in interface ModelOrBuilder
        Returns:
        The count of supportedOutputStorageFormats.

      • getSupportedOutputStorageFormats

        public String getSupportedOutputStorageFormats​(int index)
         Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedOutputStorageFormats in interface ModelOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The supportedOutputStorageFormats at the given index.

      • getSupportedOutputStorageFormatsBytes

        public com.google.protobuf.ByteString getSupportedOutputStorageFormatsBytes​(int index)
         Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
        repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getSupportedOutputStorageFormatsBytes in interface ModelOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the supportedOutputStorageFormats at the given index.

      • hasCreateTime

        public boolean hasCreateTime()
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasCreateTime in interface ModelOrBuilder
        Returns:
        Whether the createTime field is set.

      • getCreateTime

        public com.google.protobuf.Timestamp getCreateTime()
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getCreateTime in interface ModelOrBuilder
        Returns:
        The createTime.

      • getCreateTimeOrBuilder

        public com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getCreateTimeOrBuilder in interface ModelOrBuilder

      • hasUpdateTime

        public boolean hasUpdateTime()
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasUpdateTime in interface ModelOrBuilder
        Returns:
        Whether the updateTime field is set.

      • getUpdateTime

        public com.google.protobuf.Timestamp getUpdateTime()
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getUpdateTime in interface ModelOrBuilder
        Returns:
        The updateTime.

      • getUpdateTimeOrBuilder

        public com.google.protobuf.TimestampOrBuilder getUpdateTimeOrBuilder()
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getUpdateTimeOrBuilder in interface ModelOrBuilder

      • getDeployedModelsList

        public List<DeployedModelRef> getDeployedModelsList()
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getDeployedModelsList in interface ModelOrBuilder

      • getDeployedModelsOrBuilderList

        public List<? extends DeployedModelRefOrBuilder> getDeployedModelsOrBuilderList()
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getDeployedModelsOrBuilderList in interface ModelOrBuilder

      • getDeployedModelsCount

        public int getDeployedModelsCount()
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getDeployedModelsCount in interface ModelOrBuilder

      • getDeployedModels

        public DeployedModelRef getDeployedModels​(int index)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getDeployedModels in interface ModelOrBuilder

      • getDeployedModelsOrBuilder

        public DeployedModelRefOrBuilder getDeployedModelsOrBuilder​(int index)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getDeployedModelsOrBuilder in interface ModelOrBuilder

      • hasExplanationSpec

        public boolean hasExplanationSpec()
         The default explanation specification for this Model.

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain]
 after being
 [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;
        Specified by:
        hasExplanationSpec in interface ModelOrBuilder
        Returns:
        Whether the explanationSpec field is set.

      • getExplanationSpec

        public ExplanationSpec getExplanationSpec()
         The default explanation specification for this Model.

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain]
 after being
 [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;
        Specified by:
        getExplanationSpec in interface ModelOrBuilder
        Returns:
        The explanationSpec.

      • getExplanationSpecOrBuilder

        public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
         The default explanation specification for this Model.

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain]
 after being
 [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec]
 of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;
        Specified by:
        getExplanationSpecOrBuilder in interface ModelOrBuilder

      • getEtag

        public String getEtag()
         Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
        string etag = 16;
        Specified by:
        getEtag in interface ModelOrBuilder
        Returns:
        The etag.

      • getEtagBytes

        public com.google.protobuf.ByteString getEtagBytes()
         Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
        string etag = 16;
        Specified by:
        getEtagBytes in interface ModelOrBuilder
        Returns:
        The bytes for etag.

      • getLabelsCount

        public int getLabelsCount()
        Description copied from interface: ModelOrBuilder
         The labels with user-defined metadata to organize your Models.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;
        Specified by:
        getLabelsCount in interface ModelOrBuilder

      • containsLabels

        public boolean containsLabels​(String key)
         The labels with user-defined metadata to organize your Models.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;
        Specified by:
        containsLabels in interface ModelOrBuilder

      • getLabelsMap

        public Map<String,​String> getLabelsMap()
         The labels with user-defined metadata to organize your Models.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;
        Specified by:
        getLabelsMap in interface ModelOrBuilder

      • getLabelsOrDefault

        public String getLabelsOrDefault​(String key,
                                 String defaultValue)
         The labels with user-defined metadata to organize your Models.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;
        Specified by:
        getLabelsOrDefault in interface ModelOrBuilder

      • getLabelsOrThrow

        public String getLabelsOrThrow​(String key)
         The labels with user-defined metadata to organize your Models.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;
        Specified by:
        getLabelsOrThrow in interface ModelOrBuilder

      • hasEncryptionSpec

        public boolean hasEncryptionSpec()
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;
        Specified by:
        hasEncryptionSpec in interface ModelOrBuilder
        Returns:
        Whether the encryptionSpec field is set.

      • getEncryptionSpec

        public EncryptionSpec getEncryptionSpec()
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;
        Specified by:
        getEncryptionSpec in interface ModelOrBuilder
        Returns:
        The encryptionSpec.

      • getEncryptionSpecOrBuilder

        public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;
        Specified by:
        getEncryptionSpecOrBuilder in interface ModelOrBuilder

      • hasModelSourceInfo

        public boolean hasModelSourceInfo()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasModelSourceInfo in interface ModelOrBuilder
        Returns:
        Whether the modelSourceInfo field is set.

      • getModelSourceInfo

        public ModelSourceInfo getModelSourceInfo()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getModelSourceInfo in interface ModelOrBuilder
        Returns:
        The modelSourceInfo.

      • getModelSourceInfoOrBuilder

        public ModelSourceInfoOrBuilder getModelSourceInfoOrBuilder()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getModelSourceInfoOrBuilder in interface ModelOrBuilder

      • hasOriginalModelInfo

        public boolean hasOriginalModelInfo()
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1beta1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        hasOriginalModelInfo in interface ModelOrBuilder
        Returns:
        Whether the originalModelInfo field is set.

      • getOriginalModelInfo

        public Model.OriginalModelInfo getOriginalModelInfo()
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1beta1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getOriginalModelInfo in interface ModelOrBuilder
        Returns:
        The originalModelInfo.

      • getOriginalModelInfoOrBuilder

        public Model.OriginalModelInfoOrBuilder getOriginalModelInfoOrBuilder()
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1beta1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getOriginalModelInfoOrBuilder in interface ModelOrBuilder

      • getMetadataArtifact

        public String getMetadataArtifact()
         Output only. The resource name of the Artifact that was created in
 MetadataStore when creating the Model. The Artifact resource name pattern
 is
 `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
        string metadata_artifact = 44 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getMetadataArtifact in interface ModelOrBuilder
        Returns:
        The metadataArtifact.

      • getMetadataArtifactBytes

        public com.google.protobuf.ByteString getMetadataArtifactBytes()
         Output only. The resource name of the Artifact that was created in
 MetadataStore when creating the Model. The Artifact resource name pattern
 is
 `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
        string metadata_artifact = 44 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getMetadataArtifactBytes in interface ModelOrBuilder
        Returns:
        The bytes for metadataArtifact.

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3

      • writeTo

        public void writeTo​(com.google.protobuf.CodedOutputStream output)
             throws IOException
        Specified by:
        writeTo in interface com.google.protobuf.MessageLite
        Overrides:
        writeTo in class com.google.protobuf.GeneratedMessageV3
        Throws:
        IOException

      • getSerializedSize

        public int getSerializedSize()
        Specified by:
        getSerializedSize in interface com.google.protobuf.MessageLite
        Overrides:
        getSerializedSize in class com.google.protobuf.GeneratedMessageV3

      • equals

        public boolean equals​(Object obj)
        Specified by:
        equals in interface com.google.protobuf.Message
        Overrides:
        equals in class com.google.protobuf.AbstractMessage

      • hashCode

        public int hashCode()
        Specified by:
        hashCode in interface com.google.protobuf.Message
        Overrides:
        hashCode in class com.google.protobuf.AbstractMessage

      • parseFrom

        public static Model parseFrom​(ByteBuffer data)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(ByteBuffer data,
                              com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(com.google.protobuf.ByteString data)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(com.google.protobuf.ByteString data,
                              com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(byte[] data)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(byte[] data,
                              com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                       throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static Model parseFrom​(com.google.protobuf.CodedInputStream input,
                              com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                       throws IOException
        Throws:
        IOException

      • newBuilderForType

        public Model.Builder newBuilderForType()
        Specified by:
        newBuilderForType in interface com.google.protobuf.Message
        Specified by:
        newBuilderForType in interface com.google.protobuf.MessageLite

      • toBuilder

        public Model.Builder toBuilder()
        Specified by:
        toBuilder in interface com.google.protobuf.Message
        Specified by:
        toBuilder in interface com.google.protobuf.MessageLite

      • newBuilderForType

        protected Model.Builder newBuilderForType​(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)
        Specified by:
        newBuilderForType in class com.google.protobuf.GeneratedMessageV3

      • getDefaultInstance

        public static Model getDefaultInstance()

      • parser

        public static com.google.protobuf.Parser<Model> parser()

      • getParserForType

        public com.google.protobuf.Parser<Model> getParserForType()
        Specified by:
        getParserForType in interface com.google.protobuf.Message
        Specified by:
        getParserForType in interface com.google.protobuf.MessageLite
        Overrides:
        getParserForType in class com.google.protobuf.GeneratedMessageV3

      • getDefaultInstanceForType

        public Model getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder