com.google.cloud.aiplatform.v1beta1

Interface ModelOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

Model, Model.Builder

public interface ModelOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
boolean	containsLabels(String key) The labels with user-defined metadata to organize your Models.
String	getArtifactUri() Immutable.
com.google.protobuf.ByteString	getArtifactUriBytes() Immutable.
Model.BaseModelSource	getBaseModelSource() Optional.
Model.BaseModelSourceOrBuilder	getBaseModelSourceOrBuilder() Optional.
ModelContainerSpec	getContainerSpec() Input only.
ModelContainerSpecOrBuilder	getContainerSpecOrBuilder() Input only.
com.google.protobuf.Timestamp	getCreateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getCreateTimeOrBuilder() Output only.
DeployedModelRef	getDeployedModels(int index) Output only.
int	getDeployedModelsCount() Output only.
List<DeployedModelRef>	getDeployedModelsList() Output only.
DeployedModelRefOrBuilder	getDeployedModelsOrBuilder(int index) Output only.
List<? extends DeployedModelRefOrBuilder>	getDeployedModelsOrBuilderList() Output only.
String	getDescription() The description of the Model.
com.google.protobuf.ByteString	getDescriptionBytes() The description of the Model.
String	getDisplayName() Required.
com.google.protobuf.ByteString	getDisplayNameBytes() Required.
EncryptionSpec	getEncryptionSpec() Customer-managed encryption key spec for a Model.
EncryptionSpecOrBuilder	getEncryptionSpecOrBuilder() Customer-managed encryption key spec for a Model.
String	getEtag() Used to perform consistent read-modify-write updates.
com.google.protobuf.ByteString	getEtagBytes() Used to perform consistent read-modify-write updates.
ExplanationSpec	getExplanationSpec() The default explanation specification for this Model.
ExplanationSpecOrBuilder	getExplanationSpecOrBuilder() The default explanation specification for this Model.
Map<String,String>	getLabels() Deprecated.
int	getLabelsCount() The labels with user-defined metadata to organize your Models.
Map<String,String>	getLabelsMap() The labels with user-defined metadata to organize your Models.
String	getLabelsOrDefault(String key, String defaultValue) The labels with user-defined metadata to organize your Models.
String	getLabelsOrThrow(String key) The labels with user-defined metadata to organize your Models.
com.google.protobuf.Value	getMetadata() Immutable.
String	getMetadataArtifact() Output only.
com.google.protobuf.ByteString	getMetadataArtifactBytes() Output only.
com.google.protobuf.ValueOrBuilder	getMetadataOrBuilder() Immutable.
String	getMetadataSchemaUri() Immutable.
com.google.protobuf.ByteString	getMetadataSchemaUriBytes() Immutable.
ModelSourceInfo	getModelSourceInfo() Output only.
ModelSourceInfoOrBuilder	getModelSourceInfoOrBuilder() Output only.
String	getName() The resource name of the Model.
com.google.protobuf.ByteString	getNameBytes() The resource name of the Model.
Model.OriginalModelInfo	getOriginalModelInfo() Output only.
Model.OriginalModelInfoOrBuilder	getOriginalModelInfoOrBuilder() Output only.
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].
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].
boolean	getSatisfiesPzi() Output only.
boolean	getSatisfiesPzs() Output only.
Model.DeploymentResourcesType	getSupportedDeploymentResourcesTypes(int index) Output only.
int	getSupportedDeploymentResourcesTypesCount() Output only.
List<Model.DeploymentResourcesType>	getSupportedDeploymentResourcesTypesList() Output only.
int	getSupportedDeploymentResourcesTypesValue(int index) Output only.
List<Integer>	getSupportedDeploymentResourcesTypesValueList() Output only.
Model.ExportFormat	getSupportedExportFormats(int index) Output only.
int	getSupportedExportFormatsCount() Output only.
List<Model.ExportFormat>	getSupportedExportFormatsList() Output only.
Model.ExportFormatOrBuilder	getSupportedExportFormatsOrBuilder(int index) Output only.
List<? extends Model.ExportFormatOrBuilder>	getSupportedExportFormatsOrBuilderList() Output only.
String	getSupportedInputStorageFormats(int index) Output only.
com.google.protobuf.ByteString	getSupportedInputStorageFormatsBytes(int index) Output only.
int	getSupportedInputStorageFormatsCount() Output only.
List<String>	getSupportedInputStorageFormatsList() Output only.
String	getSupportedOutputStorageFormats(int index) Output only.
com.google.protobuf.ByteString	getSupportedOutputStorageFormatsBytes(int index) Output only.
int	getSupportedOutputStorageFormatsCount() Output only.
List<String>	getSupportedOutputStorageFormatsList() Output only.
String	getTrainingPipeline() Output only.
com.google.protobuf.ByteString	getTrainingPipelineBytes() Output only.
com.google.protobuf.Timestamp	getUpdateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getUpdateTimeOrBuilder() Output only.
String	getVersionAliases(int index) User provided version aliases so that a model version can be referenced via alias (i.e.
com.google.protobuf.ByteString	getVersionAliasesBytes(int index) User provided version aliases so that a model version can be referenced via alias (i.e.
int	getVersionAliasesCount() User provided version aliases so that a model version can be referenced via alias (i.e.
List<String>	getVersionAliasesList() User provided version aliases so that a model version can be referenced via alias (i.e.
com.google.protobuf.Timestamp	getVersionCreateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getVersionCreateTimeOrBuilder() Output only.
String	getVersionDescription() The description of this version.
com.google.protobuf.ByteString	getVersionDescriptionBytes() The description of this version.
String	getVersionId() Output only.
com.google.protobuf.ByteString	getVersionIdBytes() Output only.
com.google.protobuf.Timestamp	getVersionUpdateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getVersionUpdateTimeOrBuilder() Output only.
boolean	hasBaseModelSource() Optional.
boolean	hasContainerSpec() Input only.
boolean	hasCreateTime() Output only.
boolean	hasEncryptionSpec() Customer-managed encryption key spec for a Model.
boolean	hasExplanationSpec() The default explanation specification for this Model.
boolean	hasMetadata() Immutable.
boolean	hasModelSourceInfo() Output only.
boolean	hasOriginalModelInfo() Output only.
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].
boolean	hasUpdateTime() Output only.
boolean	hasVersionCreateTime() Output only.
boolean	hasVersionUpdateTime() Output only.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getName

String getName()

 The resource name of the Model.
 

string name = 1;

Returns:

The name.

getNameBytes

com.google.protobuf.ByteString getNameBytes()

 The resource name of the Model.
 

string name = 1;

Returns:

The bytes for name.

getVersionId

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];

Returns:

The versionId.

getVersionIdBytes

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];

Returns:

The bytes for versionId.

getVersionAliasesList

List<String> 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;

Returns:

A list containing the versionAliases.

getVersionAliasesCount

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;

Returns:

The count of versionAliases.

getVersionAliases

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;

Parameters:

index - The index of the element to return.

Returns:

The versionAliases at the given index.

getVersionAliasesBytes

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;

Parameters:

index - The index of the value to return.

Returns:

The bytes of the versionAliases at the given index.

hasVersionCreateTime

boolean hasVersionCreateTime()

 Output only. Timestamp when this version was created.
 

.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the versionCreateTime field is set.

getVersionCreateTime

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];

Returns:

The versionCreateTime.

getVersionCreateTimeOrBuilder

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];

hasVersionUpdateTime

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];

Returns:

Whether the versionUpdateTime field is set.

getVersionUpdateTime

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];

Returns:

The versionUpdateTime.

getVersionUpdateTimeOrBuilder

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];

getDisplayName

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];

Returns:

The displayName.

getDisplayNameBytes

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];

Returns:

The bytes for displayName.

getDescription

String getDescription()

 The description of the Model.
 

string description = 3;

Returns:

The description.

getDescriptionBytes

com.google.protobuf.ByteString getDescriptionBytes()

 The description of the Model.
 

string description = 3;

Returns:

The bytes for description.

getVersionDescription

String getVersionDescription()

 The description of this version.
 

string version_description = 30;

Returns:

The versionDescription.

getVersionDescriptionBytes

com.google.protobuf.ByteString getVersionDescriptionBytes()

 The description of this version.
 

string version_description = 30;

Returns:

The bytes for versionDescription.

hasPredictSchemata

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;

Returns:

Whether the predictSchemata field is set.

getPredictSchemata

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;

Returns:

The predictSchemata.

getPredictSchemataOrBuilder

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;

getMetadataSchemaUri

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];

Returns:

The metadataSchemaUri.

getMetadataSchemaUriBytes

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];

Returns:

The bytes for metadataSchemaUri.

hasMetadata

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];

Returns:

Whether the metadata field is set.

getMetadata

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];

Returns:

The metadata.

getMetadataOrBuilder

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];

getSupportedExportFormatsList

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];

getSupportedExportFormats

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];

getSupportedExportFormatsCount

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];

getSupportedExportFormatsOrBuilderList

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];

getSupportedExportFormatsOrBuilder

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];

getTrainingPipeline

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) = { ... }

Returns:

The trainingPipeline.

getTrainingPipelineBytes

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) = { ... }

Returns:

The bytes for trainingPipeline.

hasContainerSpec

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 required for AutoML Models.
 

.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

Returns:

Whether the containerSpec field is set.

getContainerSpec

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 required for AutoML Models.
 

.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

Returns:

The containerSpec.

getContainerSpecOrBuilder

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 required for AutoML Models.
 

.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

getArtifactUri

String getArtifactUri()

 Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not required for AutoML Models.
 

string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];

Returns:

The artifactUri.

getArtifactUriBytes

com.google.protobuf.ByteString getArtifactUriBytes()

 Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not required for AutoML Models.
 

string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];

Returns:

The bytes for artifactUri.

getSupportedDeploymentResourcesTypesList

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];

Returns:

A list containing the supportedDeploymentResourcesTypes.

getSupportedDeploymentResourcesTypesCount

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];

Returns:

The count of supportedDeploymentResourcesTypes.

getSupportedDeploymentResourcesTypes

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];

Parameters:

index - The index of the element to return.

Returns:

The supportedDeploymentResourcesTypes at the given index.

getSupportedDeploymentResourcesTypesValueList

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];

Returns:

A list containing the enum numeric values on the wire for supportedDeploymentResourcesTypes.

getSupportedDeploymentResourcesTypesValue

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];

Parameters:

index - The index of the value to return.

Returns:

The enum numeric value on the wire of supportedDeploymentResourcesTypes at the given index.

getSupportedInputStorageFormatsList

List<String> 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];

Returns:

A list containing the supportedInputStorageFormats.

getSupportedInputStorageFormatsCount

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];

Returns:

The count of supportedInputStorageFormats.

getSupportedInputStorageFormats

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];

Parameters:

index - The index of the element to return.

Returns:

The supportedInputStorageFormats at the given index.

getSupportedInputStorageFormatsBytes

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];

Parameters:

index - The index of the value to return.

Returns:

The bytes of the supportedInputStorageFormats at the given index.

getSupportedOutputStorageFormatsList

List<String> 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];

Returns:

A list containing the supportedOutputStorageFormats.

getSupportedOutputStorageFormatsCount

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];

Returns:

The count of supportedOutputStorageFormats.

getSupportedOutputStorageFormats

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];

Parameters:

index - The index of the element to return.

Returns:

The supportedOutputStorageFormats at the given index.

getSupportedOutputStorageFormatsBytes

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];

Parameters:

index - The index of the value to return.

Returns:

The bytes of the supportedOutputStorageFormats at the given index.

hasCreateTime

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];

Returns:

Whether the createTime field is set.

getCreateTime

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];

Returns:

The createTime.

getCreateTimeOrBuilder

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];

hasUpdateTime

boolean hasUpdateTime()

 Output only. Timestamp when this Model was most recently updated.
 

.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the updateTime field is set.

getUpdateTime

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];

Returns:

The updateTime.

getUpdateTimeOrBuilder

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];

getDeployedModelsList

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];

getDeployedModels

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];

getDeployedModelsCount

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];

getDeployedModelsOrBuilderList

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];

getDeployedModelsOrBuilder

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];

hasExplanationSpec

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;

Returns:

Whether the explanationSpec field is set.

getExplanationSpec

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;

Returns:

The explanationSpec.

getExplanationSpecOrBuilder

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;

getEtag

String getEtag()

 Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
 

string etag = 16;

Returns:

The etag.

getEtagBytes

com.google.protobuf.ByteString getEtagBytes()

 Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
 

string etag = 16;

Returns:

The bytes for etag.

getLabelsCount

int getLabelsCount()

 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;

containsLabels

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;

getLabels

@Deprecated
Map<String,String> getLabels()

Deprecated.

Use getLabelsMap() instead.

getLabelsMap

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;

getLabelsOrDefault

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;

getLabelsOrThrow

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;

hasEncryptionSpec

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;

Returns:

Whether the encryptionSpec field is set.

getEncryptionSpec

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;

Returns:

The encryptionSpec.

getEncryptionSpecOrBuilder

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;

hasModelSourceInfo

boolean hasModelSourceInfo()

 Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
 

.google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the modelSourceInfo field is set.

getModelSourceInfo

ModelSourceInfo getModelSourceInfo()

 Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
 

.google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The modelSourceInfo.

getModelSourceInfoOrBuilder

ModelSourceInfoOrBuilder getModelSourceInfoOrBuilder()

 Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
 

.google.cloud.aiplatform.v1beta1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

hasOriginalModelInfo

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];

Returns:

Whether the originalModelInfo field is set.

getOriginalModelInfo

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];

Returns:

The originalModelInfo.

getOriginalModelInfoOrBuilder

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];

getMetadataArtifact

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];

Returns:

The metadataArtifact.

getMetadataArtifactBytes

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];

Returns:

The bytes for metadataArtifact.

hasBaseModelSource

boolean hasBaseModelSource()

 Optional. User input field to specify the base model source. Currently it
 only supports specifing the Model Garden models and Genie models.
 

.google.cloud.aiplatform.v1beta1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

Returns:

Whether the baseModelSource field is set.

getBaseModelSource

Model.BaseModelSource getBaseModelSource()

 Optional. User input field to specify the base model source. Currently it
 only supports specifing the Model Garden models and Genie models.
 

.google.cloud.aiplatform.v1beta1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The baseModelSource.

getBaseModelSourceOrBuilder

Model.BaseModelSourceOrBuilder getBaseModelSourceOrBuilder()

 Optional. User input field to specify the base model source. Currently it
 only supports specifing the Model Garden models and Genie models.
 

.google.cloud.aiplatform.v1beta1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

getSatisfiesPzs

boolean getSatisfiesPzs()

 Output only. Reserved for future use.
 

bool satisfies_pzs = 51 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The satisfiesPzs.

getSatisfiesPzi

boolean getSatisfiesPzi()

 Output only. Reserved for future use.
 

bool satisfies_pzi = 52 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The satisfiesPzi.