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public static final class Model.Builder extends GeneratedMessageV3.Builder<Model.Builder> implements ModelOrBuilder
A trained machine learning Model.
Protobuf type google.cloud.aiplatform.v1.Model
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > Model.BuilderImplements
ModelOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns | |
---|---|
Type | Description |
Descriptor |
Methods
addAllDeployedModels(Iterable<? extends DeployedModelRef> values)
public Model.Builder addAllDeployedModels(Iterable<? extends DeployedModelRef> values)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<? extends com.google.cloud.aiplatform.v1.DeployedModelRef> |
Returns | |
---|---|
Type | Description |
Model.Builder |
addAllSupportedDeploymentResourcesTypes(Iterable<? extends Model.DeploymentResourcesType> values)
public Model.Builder addAllSupportedDeploymentResourcesTypes(Iterable<? extends Model.DeploymentResourcesType> values)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<? extends com.google.cloud.aiplatform.v1.Model.DeploymentResourcesType> The supportedDeploymentResourcesTypes to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addAllSupportedDeploymentResourcesTypesValue(Iterable<Integer> values)
public Model.Builder addAllSupportedDeploymentResourcesTypesValue(Iterable<Integer> values)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<Integer> The enum numeric values on the wire for supportedDeploymentResourcesTypes to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addAllSupportedExportFormats(Iterable<? extends Model.ExportFormat> values)
public Model.Builder addAllSupportedExportFormats(Iterable<? extends Model.ExportFormat> values)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<? extends com.google.cloud.aiplatform.v1.Model.ExportFormat> |
Returns | |
---|---|
Type | Description |
Model.Builder |
addAllSupportedInputStorageFormats(Iterable<String> values)
public Model.Builder addAllSupportedInputStorageFormats(Iterable<String> values)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<String> The supportedInputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addAllSupportedOutputStorageFormats(Iterable<String> values)
public Model.Builder addAllSupportedOutputStorageFormats(Iterable<String> values)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
values | Iterable<String> The supportedOutputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addAllVersionAliases(Iterable<String> values)
public Model.Builder addAllVersionAliases(Iterable<String> values)
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{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;
Parameter | |
---|---|
Name | Description |
values | Iterable<String> The versionAliases to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addDeployedModels(DeployedModelRef value)
public Model.Builder addDeployedModels(DeployedModelRef value)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | DeployedModelRef |
Returns | |
---|---|
Type | Description |
Model.Builder |
addDeployedModels(DeployedModelRef.Builder builderForValue)
public Model.Builder addDeployedModels(DeployedModelRef.Builder builderForValue)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | DeployedModelRef.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
addDeployedModels(int index, DeployedModelRef value)
public Model.Builder addDeployedModels(int index, DeployedModelRef value)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
value | DeployedModelRef |
Returns | |
---|---|
Type | Description |
Model.Builder |
addDeployedModels(int index, DeployedModelRef.Builder builderForValue)
public Model.Builder addDeployedModels(int index, DeployedModelRef.Builder builderForValue)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
builderForValue | DeployedModelRef.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
addDeployedModelsBuilder()
public DeployedModelRef.Builder addDeployedModelsBuilder()
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
DeployedModelRef.Builder |
addDeployedModelsBuilder(int index)
public DeployedModelRef.Builder addDeployedModelsBuilder(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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
DeployedModelRef.Builder |
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public Model.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
Model.Builder |
addSupportedDeploymentResourcesTypes(Model.DeploymentResourcesType value)
public Model.Builder addSupportedDeploymentResourcesTypes(Model.DeploymentResourcesType value)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Model.DeploymentResourcesType The supportedDeploymentResourcesTypes to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addSupportedDeploymentResourcesTypesValue(int value)
public Model.Builder addSupportedDeploymentResourcesTypesValue(int value)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | int The enum numeric value on the wire for supportedDeploymentResourcesTypes to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addSupportedExportFormats(Model.ExportFormat value)
public Model.Builder addSupportedExportFormats(Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Model.ExportFormat |
Returns | |
---|---|
Type | Description |
Model.Builder |
addSupportedExportFormats(Model.ExportFormat.Builder builderForValue)
public Model.Builder addSupportedExportFormats(Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Model.ExportFormat.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
addSupportedExportFormats(int index, Model.ExportFormat value)
public Model.Builder addSupportedExportFormats(int index, Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
value | Model.ExportFormat |
Returns | |
---|---|
Type | Description |
Model.Builder |
addSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
public Model.Builder addSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
builderForValue | Model.ExportFormat.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
addSupportedExportFormatsBuilder()
public Model.ExportFormat.Builder addSupportedExportFormatsBuilder()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.ExportFormat.Builder |
addSupportedExportFormatsBuilder(int index)
public Model.ExportFormat.Builder addSupportedExportFormatsBuilder(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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.ExportFormat.Builder |
addSupportedInputStorageFormats(String value)
public Model.Builder addSupportedInputStorageFormats(String value)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | String The supportedInputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addSupportedInputStorageFormatsBytes(ByteString value)
public Model.Builder addSupportedInputStorageFormatsBytes(ByteString value)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes of the supportedInputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addSupportedOutputStorageFormats(String value)
public Model.Builder addSupportedOutputStorageFormats(String value)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | String The supportedOutputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addSupportedOutputStorageFormatsBytes(ByteString value)
public Model.Builder addSupportedOutputStorageFormatsBytes(ByteString value)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes of the supportedOutputStorageFormats to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addVersionAliases(String value)
public Model.Builder addVersionAliases(String value)
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{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;
Parameter | |
---|---|
Name | Description |
value | String The versionAliases to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
addVersionAliasesBytes(ByteString value)
public Model.Builder addVersionAliasesBytes(ByteString value)
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{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;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes of the versionAliases to add. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
build()
public Model build()
Returns | |
---|---|
Type | Description |
Model |
buildPartial()
public Model buildPartial()
Returns | |
---|---|
Type | Description |
Model |
clear()
public Model.Builder clear()
Returns | |
---|---|
Type | Description |
Model.Builder |
clearArtifactUri()
public Model.Builder clearArtifactUri()
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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearContainerSpec()
public Model.Builder clearContainerSpec()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearCreateTime()
public Model.Builder clearCreateTime()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearDataStats()
public Model.Builder clearDataStats()
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Returns | |
---|---|
Type | Description |
Model.Builder |
clearDeployedModels()
public Model.Builder clearDeployedModels()
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearDescription()
public Model.Builder clearDescription()
The description of the Model.
string description = 3;
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearDisplayName()
public Model.Builder clearDisplayName()
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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearEncryptionSpec()
public Model.Builder clearEncryptionSpec()
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.v1.EncryptionSpec encryption_spec = 24;
Returns | |
---|---|
Type | Description |
Model.Builder |
clearEtag()
public Model.Builder clearEtag()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearExplanationSpec()
public Model.Builder clearExplanationSpec()
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Returns | |
---|---|
Type | Description |
Model.Builder |
clearField(Descriptors.FieldDescriptor field)
public Model.Builder clearField(Descriptors.FieldDescriptor field)
Parameter | |
---|---|
Name | Description |
field | FieldDescriptor |
Returns | |
---|---|
Type | Description |
Model.Builder |
clearLabels()
public Model.Builder clearLabels()
Returns | |
---|---|
Type | Description |
Model.Builder |
clearMetadata()
public Model.Builder clearMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearMetadataArtifact()
public Model.Builder clearMetadataArtifact()
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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearMetadataSchemaUri()
public Model.Builder clearMetadataSchemaUri()
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. 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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearModelSourceInfo()
public Model.Builder clearModelSourceInfo()
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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearName()
public Model.Builder clearName()
The resource name of the Model.
string name = 1;
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public Model.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter | |
---|---|
Name | Description |
oneof | OneofDescriptor |
Returns | |
---|---|
Type | Description |
Model.Builder |
clearOriginalModelInfo()
public Model.Builder clearOriginalModelInfo()
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearPipelineJob()
public Model.Builder clearPipelineJob()
Optional. This field is populated if the model is produced by a pipeline job.
string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearPredictSchemata()
public Model.Builder clearPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Returns | |
---|---|
Type | Description |
Model.Builder |
clearSupportedDeploymentResourcesTypes()
public Model.Builder clearSupportedDeploymentResourcesTypes()
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearSupportedExportFormats()
public Model.Builder clearSupportedExportFormats()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearSupportedInputStorageFormats()
public Model.Builder clearSupportedInputStorageFormats()
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearSupportedOutputStorageFormats()
public Model.Builder clearSupportedOutputStorageFormats()
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearTrainingPipeline()
public Model.Builder clearTrainingPipeline()
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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearUpdateTime()
public Model.Builder clearUpdateTime()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearVersionAliases()
public Model.Builder clearVersionAliases()
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{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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearVersionCreateTime()
public Model.Builder clearVersionCreateTime()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clearVersionDescription()
public Model.Builder clearVersionDescription()
The description of this version.
string version_description = 30;
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearVersionId()
public Model.Builder clearVersionId()
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 | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
clearVersionUpdateTime()
public Model.Builder clearVersionUpdateTime()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.Builder |
clone()
public Model.Builder clone()
Returns | |
---|---|
Type | Description |
Model.Builder |
containsLabels(String key)
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;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
boolean |
getArtifactUri()
public 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 | |
---|---|
Type | Description |
String | The artifactUri. |
getArtifactUriBytes()
public 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 | |
---|---|
Type | Description |
ByteString | The bytes for artifactUri. |
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, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelContainerSpec | The containerSpec. |
getContainerSpecBuilder()
public ModelContainerSpec.Builder getContainerSpecBuilder()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelContainerSpec.Builder |
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, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelContainerSpecOrBuilder |
getCreateTime()
public 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 | |
---|---|
Type | Description |
Timestamp | The createTime. |
getCreateTimeBuilder()
public Timestamp.Builder getCreateTimeBuilder()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Builder |
getCreateTimeOrBuilder()
public 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];
Returns | |
---|---|
Type | Description |
TimestampOrBuilder |
getDataStats()
public Model.DataStats getDataStats()
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Returns | |
---|---|
Type | Description |
Model.DataStats | The dataStats. |
getDataStatsBuilder()
public Model.DataStats.Builder getDataStatsBuilder()
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Returns | |
---|---|
Type | Description |
Model.DataStats.Builder |
getDataStatsOrBuilder()
public Model.DataStatsOrBuilder getDataStatsOrBuilder()
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Returns | |
---|---|
Type | Description |
Model.DataStatsOrBuilder |
getDefaultInstanceForType()
public Model getDefaultInstanceForType()
Returns | |
---|---|
Type | Description |
Model |
getDeployedModels(int index)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
DeployedModelRef |
getDeployedModelsBuilder(int index)
public DeployedModelRef.Builder getDeployedModelsBuilder(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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
DeployedModelRef.Builder |
getDeployedModelsBuilderList()
public List<DeployedModelRef.Builder> getDeployedModelsBuilderList()
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<Builder> |
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
int |
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<DeployedModelRef> |
getDeployedModelsOrBuilder(int index)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
DeployedModelRefOrBuilder |
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<? extends com.google.cloud.aiplatform.v1.DeployedModelRefOrBuilder> |
getDescription()
public String getDescription()
The description of the Model.
string description = 3;
Returns | |
---|---|
Type | Description |
String | The description. |
getDescriptionBytes()
public ByteString getDescriptionBytes()
The description of the Model.
string description = 3;
Returns | |
---|---|
Type | Description |
ByteString | The bytes for description. |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns | |
---|---|
Type | Description |
Descriptor |
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];
Returns | |
---|---|
Type | Description |
String | The displayName. |
getDisplayNameBytes()
public 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 | |
---|---|
Type | Description |
ByteString | The bytes for displayName. |
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.v1.EncryptionSpec encryption_spec = 24;
Returns | |
---|---|
Type | Description |
EncryptionSpec | The encryptionSpec. |
getEncryptionSpecBuilder()
public EncryptionSpec.Builder getEncryptionSpecBuilder()
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.v1.EncryptionSpec encryption_spec = 24;
Returns | |
---|---|
Type | Description |
EncryptionSpec.Builder |
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.v1.EncryptionSpec encryption_spec = 24;
Returns | |
---|---|
Type | Description |
EncryptionSpecOrBuilder |
getEtag()
public String getEtag()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;
Returns | |
---|---|
Type | Description |
String | The etag. |
getEtagBytes()
public ByteString getEtagBytes()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;
Returns | |
---|---|
Type | Description |
ByteString | The bytes for etag. |
getExplanationSpec()
public ExplanationSpec getExplanationSpec()
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Returns | |
---|---|
Type | Description |
ExplanationSpec | The explanationSpec. |
getExplanationSpecBuilder()
public ExplanationSpec.Builder getExplanationSpecBuilder()
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Returns | |
---|---|
Type | Description |
ExplanationSpec.Builder |
getExplanationSpecOrBuilder()
public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Returns | |
---|---|
Type | Description |
ExplanationSpecOrBuilder |
getLabels() (deprecated)
public Map<String,String> getLabels()
Use #getLabelsMap() instead.
Returns | |
---|---|
Type | Description |
Map<String,String> |
getLabelsCount()
public 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;
Returns | |
---|---|
Type | Description |
int |
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;
Returns | |
---|---|
Type | Description |
Map<String,String> |
getLabelsOrDefault(String key, String defaultValue)
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;
Parameters | |
---|---|
Name | Description |
key | String |
defaultValue | String |
Returns | |
---|---|
Type | Description |
String |
getLabelsOrThrow(String key)
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;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
String |
getMetadata()
public Value getMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Returns | |
---|---|
Type | Description |
Value | The metadata. |
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];
Returns | |
---|---|
Type | Description |
String | The metadataArtifact. |
getMetadataArtifactBytes()
public 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 | |
---|---|
Type | Description |
ByteString | The bytes for metadataArtifact. |
getMetadataBuilder()
public Value.Builder getMetadataBuilder()
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Returns | |
---|---|
Type | Description |
Builder |
getMetadataOrBuilder()
public ValueOrBuilder getMetadataOrBuilder()
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Returns | |
---|---|
Type | Description |
ValueOrBuilder |
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. 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 | |
---|---|
Type | Description |
String | The metadataSchemaUri. |
getMetadataSchemaUriBytes()
public 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. 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 | |
---|---|
Type | Description |
ByteString | The bytes for metadataSchemaUri. |
getModelSourceInfo()
public 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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelSourceInfo | The modelSourceInfo. |
getModelSourceInfoBuilder()
public ModelSourceInfo.Builder getModelSourceInfoBuilder()
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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelSourceInfo.Builder |
getModelSourceInfoOrBuilder()
public 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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
ModelSourceInfoOrBuilder |
getMutableLabels() (deprecated)
public Map<String,String> getMutableLabels()
Use alternate mutation accessors instead.
Returns | |
---|---|
Type | Description |
Map<String,String> |
getName()
public String getName()
The resource name of the Model.
string name = 1;
Returns | |
---|---|
Type | Description |
String | The name. |
getNameBytes()
public ByteString getNameBytes()
The resource name of the Model.
string name = 1;
Returns | |
---|---|
Type | Description |
ByteString | The bytes for name. |
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.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.OriginalModelInfo | The originalModelInfo. |
getOriginalModelInfoBuilder()
public Model.OriginalModelInfo.Builder getOriginalModelInfoBuilder()
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.OriginalModelInfo.Builder |
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.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Model.OriginalModelInfoOrBuilder |
getPipelineJob()
public String getPipelineJob()
Optional. This field is populated if the model is produced by a pipeline job.
string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Returns | |
---|---|
Type | Description |
String | The pipelineJob. |
getPipelineJobBytes()
public ByteString getPipelineJobBytes()
Optional. This field is populated if the model is produced by a pipeline job.
string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Returns | |
---|---|
Type | Description |
ByteString | The bytes for pipelineJob. |
getPredictSchemata()
public PredictSchemata getPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Returns | |
---|---|
Type | Description |
PredictSchemata | The predictSchemata. |
getPredictSchemataBuilder()
public PredictSchemata.Builder getPredictSchemataBuilder()
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Returns | |
---|---|
Type | Description |
PredictSchemata.Builder |
getPredictSchemataOrBuilder()
public PredictSchemataOrBuilder getPredictSchemataOrBuilder()
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Returns | |
---|---|
Type | Description |
PredictSchemataOrBuilder |
getSupportedDeploymentResourcesTypes(int index)
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
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the element to return. |
Returns | |
---|---|
Type | Description |
Model.DeploymentResourcesType | The supportedDeploymentResourcesTypes at the given index. |
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
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
int | The count of supportedDeploymentResourcesTypes. |
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
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<DeploymentResourcesType> | A list containing the supportedDeploymentResourcesTypes. |
getSupportedDeploymentResourcesTypesValue(int index)
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
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the value to return. |
Returns | |
---|---|
Type | Description |
int | The enum numeric value on the wire of 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
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<Integer> | A list containing the enum numeric values on the wire for supportedDeploymentResourcesTypes. |
getSupportedExportFormats(int index)
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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.ExportFormat |
getSupportedExportFormatsBuilder(int index)
public Model.ExportFormat.Builder getSupportedExportFormatsBuilder(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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.ExportFormat.Builder |
getSupportedExportFormatsBuilderList()
public List<Model.ExportFormat.Builder> getSupportedExportFormatsBuilderList()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<Builder> |
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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
int |
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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<ExportFormat> |
getSupportedExportFormatsOrBuilder(int index)
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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.ExportFormatOrBuilder |
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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
List<? extends com.google.cloud.aiplatform.v1.Model.ExportFormatOrBuilder> |
getSupportedInputStorageFormats(int index)
public String getSupportedInputStorageFormats(int index)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the element to return. |
Returns | |
---|---|
Type | Description |
String | The supportedInputStorageFormats at the given index. |
getSupportedInputStorageFormatsBytes(int index)
public ByteString getSupportedInputStorageFormatsBytes(int index)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the value to return. |
Returns | |
---|---|
Type | Description |
ByteString | The bytes of the supportedInputStorageFormats at the given index. |
getSupportedInputStorageFormatsCount()
public int getSupportedInputStorageFormatsCount()
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
int | The count of supportedInputStorageFormats. |
getSupportedInputStorageFormatsList()
public ProtocolStringList getSupportedInputStorageFormatsList()
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
ProtocolStringList | A list containing the supportedInputStorageFormats. |
getSupportedOutputStorageFormats(int index)
public String getSupportedOutputStorageFormats(int index)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the element to return. |
Returns | |
---|---|
Type | Description |
String | The supportedOutputStorageFormats at the given index. |
getSupportedOutputStorageFormatsBytes(int index)
public ByteString getSupportedOutputStorageFormatsBytes(int index)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int The index of the value to return. |
Returns | |
---|---|
Type | Description |
ByteString | The bytes of the supportedOutputStorageFormats at the given index. |
getSupportedOutputStorageFormatsCount()
public int getSupportedOutputStorageFormatsCount()
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
int | The count of supportedOutputStorageFormats. |
getSupportedOutputStorageFormatsList()
public ProtocolStringList getSupportedOutputStorageFormatsList()
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
ProtocolStringList | A list containing the supportedOutputStorageFormats. |
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) = { ... }
Returns | |
---|---|
Type | Description |
String | The trainingPipeline. |
getTrainingPipelineBytes()
public 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 | |
---|---|
Type | Description |
ByteString | The bytes for trainingPipeline. |
getUpdateTime()
public 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 | |
---|---|
Type | Description |
Timestamp | The updateTime. |
getUpdateTimeBuilder()
public Timestamp.Builder getUpdateTimeBuilder()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Builder |
getUpdateTimeOrBuilder()
public TimestampOrBuilder getUpdateTimeOrBuilder()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
TimestampOrBuilder |
getVersionAliases(int index)
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{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;
Parameter | |
---|---|
Name | Description |
index | int The index of the element to return. |
Returns | |
---|---|
Type | Description |
String | The versionAliases at the given index. |
getVersionAliasesBytes(int index)
public 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{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;
Parameter | |
---|---|
Name | Description |
index | int The index of the value to return. |
Returns | |
---|---|
Type | Description |
ByteString | The bytes of the versionAliases at the given index. |
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{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 | |
---|---|
Type | Description |
int | The count of versionAliases. |
getVersionAliasesList()
public 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{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 | |
---|---|
Type | Description |
ProtocolStringList | A list containing the versionAliases. |
getVersionCreateTime()
public Timestamp getVersionCreateTime()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Timestamp | The versionCreateTime. |
getVersionCreateTimeBuilder()
public Timestamp.Builder getVersionCreateTimeBuilder()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Builder |
getVersionCreateTimeOrBuilder()
public TimestampOrBuilder getVersionCreateTimeOrBuilder()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
TimestampOrBuilder |
getVersionDescription()
public String getVersionDescription()
The description of this version.
string version_description = 30;
Returns | |
---|---|
Type | Description |
String | The versionDescription. |
getVersionDescriptionBytes()
public ByteString getVersionDescriptionBytes()
The description of this version.
string version_description = 30;
Returns | |
---|---|
Type | Description |
ByteString | The bytes for versionDescription. |
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];
Returns | |
---|---|
Type | Description |
String | The versionId. |
getVersionIdBytes()
public 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 | |
---|---|
Type | Description |
ByteString | The bytes for versionId. |
getVersionUpdateTime()
public 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 | |
---|---|
Type | Description |
Timestamp | The versionUpdateTime. |
getVersionUpdateTimeBuilder()
public Timestamp.Builder getVersionUpdateTimeBuilder()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
Builder |
getVersionUpdateTimeOrBuilder()
public 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];
Returns | |
---|---|
Type | Description |
TimestampOrBuilder |
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, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Returns | |
---|---|
Type | Description |
boolean | Whether the containerSpec field is set. |
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];
Returns | |
---|---|
Type | Description |
boolean | Whether the createTime field is set. |
hasDataStats()
public boolean hasDataStats()
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Returns | |
---|---|
Type | Description |
boolean | Whether the dataStats field is set. |
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.v1.EncryptionSpec encryption_spec = 24;
Returns | |
---|---|
Type | Description |
boolean | Whether the encryptionSpec field is set. |
hasExplanationSpec()
public boolean hasExplanationSpec()
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Returns | |
---|---|
Type | Description |
boolean | Whether the explanationSpec field is set. |
hasMetadata()
public boolean hasMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Returns | |
---|---|
Type | Description |
boolean | Whether the metadata field is set. |
hasModelSourceInfo()
public 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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
boolean | Whether the modelSourceInfo field is set. |
hasOriginalModelInfo()
public boolean hasOriginalModelInfo()
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Returns | |
---|---|
Type | Description |
boolean | Whether the originalModelInfo field is set. |
hasPredictSchemata()
public boolean hasPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Returns | |
---|---|
Type | Description |
boolean | Whether the predictSchemata field is set. |
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];
Returns | |
---|---|
Type | Description |
boolean | Whether the updateTime field is set. |
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];
Returns | |
---|---|
Type | Description |
boolean | Whether the versionCreateTime field is set. |
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];
Returns | |
---|---|
Type | Description |
boolean | Whether the versionUpdateTime field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns | |
---|---|
Type | Description |
FieldAccessorTable |
internalGetMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
com.google.protobuf.MapFieldReflectionAccessor |
internalGetMutableMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
com.google.protobuf.MapFieldReflectionAccessor |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
mergeContainerSpec(ModelContainerSpec value)
public Model.Builder mergeContainerSpec(ModelContainerSpec value)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ModelContainerSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeCreateTime(Timestamp value)
public Model.Builder mergeCreateTime(Timestamp value)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeDataStats(Model.DataStats value)
public Model.Builder mergeDataStats(Model.DataStats value)
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Parameter | |
---|---|
Name | Description |
value | Model.DataStats |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeEncryptionSpec(EncryptionSpec value)
public Model.Builder mergeEncryptionSpec(EncryptionSpec value)
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.v1.EncryptionSpec encryption_spec = 24;
Parameter | |
---|---|
Name | Description |
value | EncryptionSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeExplanationSpec(ExplanationSpec value)
public Model.Builder mergeExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Parameter | |
---|---|
Name | Description |
value | ExplanationSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeFrom(Model other)
public Model.Builder mergeFrom(Model other)
Parameter | |
---|---|
Name | Description |
other | Model |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public Model.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
Model.Builder |
Exceptions | |
---|---|
Type | Description |
IOException |
mergeFrom(Message other)
public Model.Builder mergeFrom(Message other)
Parameter | |
---|---|
Name | Description |
other | Message |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeMetadata(Value value)
public Model.Builder mergeMetadata(Value value)
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Parameter | |
---|---|
Name | Description |
value | Value |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeModelSourceInfo(ModelSourceInfo value)
public Model.Builder mergeModelSourceInfo(ModelSourceInfo value)
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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ModelSourceInfo |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeOriginalModelInfo(Model.OriginalModelInfo value)
public Model.Builder mergeOriginalModelInfo(Model.OriginalModelInfo value)
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Model.OriginalModelInfo |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergePredictSchemata(PredictSchemata value)
public Model.Builder mergePredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Parameter | |
---|---|
Name | Description |
value | PredictSchemata |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final Model.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeUpdateTime(Timestamp value)
public Model.Builder mergeUpdateTime(Timestamp value)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeVersionCreateTime(Timestamp value)
public Model.Builder mergeVersionCreateTime(Timestamp value)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
mergeVersionUpdateTime(Timestamp value)
public Model.Builder mergeVersionUpdateTime(Timestamp value)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
putAllLabels(Map<String,String> values)
public Model.Builder putAllLabels(Map<String,String> values)
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;
Parameter | |
---|---|
Name | Description |
values | Map<String,String> |
Returns | |
---|---|
Type | Description |
Model.Builder |
putLabels(String key, String value)
public Model.Builder putLabels(String key, String value)
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;
Parameters | |
---|---|
Name | Description |
key | String |
value | String |
Returns | |
---|---|
Type | Description |
Model.Builder |
removeDeployedModels(int index)
public Model.Builder removeDeployedModels(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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.Builder |
removeLabels(String key)
public Model.Builder removeLabels(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;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
Model.Builder |
removeSupportedExportFormats(int index)
public Model.Builder removeSupportedExportFormats(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.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
index | int |
Returns | |
---|---|
Type | Description |
Model.Builder |
setArtifactUri(String value)
public Model.Builder setArtifactUri(String value)
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];
Parameter | |
---|---|
Name | Description |
value | String The artifactUri to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setArtifactUriBytes(ByteString value)
public Model.Builder setArtifactUriBytes(ByteString value)
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];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for artifactUri to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setContainerSpec(ModelContainerSpec value)
public Model.Builder setContainerSpec(ModelContainerSpec value)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ModelContainerSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
setContainerSpec(ModelContainerSpec.Builder builderForValue)
public Model.Builder setContainerSpec(ModelContainerSpec.Builder builderForValue)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models.
.google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | ModelContainerSpec.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setCreateTime(Timestamp value)
public Model.Builder setCreateTime(Timestamp value)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
setCreateTime(Timestamp.Builder builderForValue)
public Model.Builder setCreateTime(Timestamp.Builder builderForValue)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setDataStats(Model.DataStats value)
public Model.Builder setDataStats(Model.DataStats value)
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Parameter | |
---|---|
Name | Description |
value | Model.DataStats |
Returns | |
---|---|
Type | Description |
Model.Builder |
setDataStats(Model.DataStats.Builder builderForValue)
public Model.Builder setDataStats(Model.DataStats.Builder builderForValue)
Stats of data used for training or evaluating the Model.
Only populated when the Model is trained by a TrainingPipeline with data_input_config.
.google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
Parameter | |
---|---|
Name | Description |
builderForValue | Model.DataStats.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setDeployedModels(int index, DeployedModelRef value)
public Model.Builder setDeployedModels(int index, DeployedModelRef value)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
value | DeployedModelRef |
Returns | |
---|---|
Type | Description |
Model.Builder |
setDeployedModels(int index, DeployedModelRef.Builder builderForValue)
public Model.Builder setDeployedModels(int index, DeployedModelRef.Builder builderForValue)
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.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
builderForValue | DeployedModelRef.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setDescription(String value)
public Model.Builder setDescription(String value)
The description of the Model.
string description = 3;
Parameter | |
---|---|
Name | Description |
value | String The description to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setDescriptionBytes(ByteString value)
public Model.Builder setDescriptionBytes(ByteString value)
The description of the Model.
string description = 3;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for description to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setDisplayName(String value)
public Model.Builder setDisplayName(String value)
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];
Parameter | |
---|---|
Name | Description |
value | String The displayName to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setDisplayNameBytes(ByteString value)
public Model.Builder setDisplayNameBytes(ByteString value)
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];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for displayName to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setEncryptionSpec(EncryptionSpec value)
public Model.Builder setEncryptionSpec(EncryptionSpec value)
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.v1.EncryptionSpec encryption_spec = 24;
Parameter | |
---|---|
Name | Description |
value | EncryptionSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
setEncryptionSpec(EncryptionSpec.Builder builderForValue)
public Model.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
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.v1.EncryptionSpec encryption_spec = 24;
Parameter | |
---|---|
Name | Description |
builderForValue | EncryptionSpec.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setEtag(String value)
public Model.Builder setEtag(String value)
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;
Parameter | |
---|---|
Name | Description |
value | String The etag to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setEtagBytes(ByteString value)
public Model.Builder setEtagBytes(ByteString value)
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for etag to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setExplanationSpec(ExplanationSpec value)
public Model.Builder setExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Parameter | |
---|---|
Name | Description |
value | ExplanationSpec |
Returns | |
---|---|
Type | Description |
Model.Builder |
setExplanationSpec(ExplanationSpec.Builder builderForValue)
public Model.Builder setExplanationSpec(ExplanationSpec.Builder builderForValue)
The default explanation specification for this Model.
The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated.
All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob.
If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
Parameter | |
---|---|
Name | Description |
builderForValue | ExplanationSpec.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public Model.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
Model.Builder |
setMetadata(Value value)
public Model.Builder setMetadata(Value value)
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Parameter | |
---|---|
Name | Description |
value | Value |
Returns | |
---|---|
Type | Description |
Model.Builder |
setMetadata(Value.Builder builderForValue)
public Model.Builder setMetadata(Value.Builder builderForValue)
Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
Parameter | |
---|---|
Name | Description |
builderForValue | Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setMetadataArtifact(String value)
public Model.Builder setMetadataArtifact(String value)
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];
Parameter | |
---|---|
Name | Description |
value | String The metadataArtifact to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setMetadataArtifactBytes(ByteString value)
public Model.Builder setMetadataArtifactBytes(ByteString value)
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];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for metadataArtifact to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setMetadataSchemaUri(String value)
public Model.Builder setMetadataSchemaUri(String value)
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. 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];
Parameter | |
---|---|
Name | Description |
value | String The metadataSchemaUri to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setMetadataSchemaUriBytes(ByteString value)
public Model.Builder setMetadataSchemaUriBytes(ByteString value)
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. 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];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for metadataSchemaUri to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setModelSourceInfo(ModelSourceInfo value)
public Model.Builder setModelSourceInfo(ModelSourceInfo value)
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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | ModelSourceInfo |
Returns | |
---|---|
Type | Description |
Model.Builder |
setModelSourceInfo(ModelSourceInfo.Builder builderForValue)
public Model.Builder setModelSourceInfo(ModelSourceInfo.Builder builderForValue)
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.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | ModelSourceInfo.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setName(String value)
public Model.Builder setName(String value)
The resource name of the Model.
string name = 1;
Parameter | |
---|---|
Name | Description |
value | String The name to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setNameBytes(ByteString value)
public Model.Builder setNameBytes(ByteString value)
The resource name of the Model.
string name = 1;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for name to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setOriginalModelInfo(Model.OriginalModelInfo value)
public Model.Builder setOriginalModelInfo(Model.OriginalModelInfo value)
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Model.OriginalModelInfo |
Returns | |
---|---|
Type | Description |
Model.Builder |
setOriginalModelInfo(Model.OriginalModelInfo.Builder builderForValue)
public Model.Builder setOriginalModelInfo(Model.OriginalModelInfo.Builder builderForValue)
Output only. If this Model is a copy of another Model, this contains info about the original.
.google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Model.OriginalModelInfo.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setPipelineJob(String value)
public Model.Builder setPipelineJob(String value)
Optional. This field is populated if the model is produced by a pipeline job.
string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Parameter | |
---|---|
Name | Description |
value | String The pipelineJob to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setPipelineJobBytes(ByteString value)
public Model.Builder setPipelineJobBytes(ByteString value)
Optional. This field is populated if the model is produced by a pipeline job.
string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for pipelineJob to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setPredictSchemata(PredictSchemata value)
public Model.Builder setPredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Parameter | |
---|---|
Name | Description |
value | PredictSchemata |
Returns | |
---|---|
Type | Description |
Model.Builder |
setPredictSchemata(PredictSchemata.Builder builderForValue)
public Model.Builder setPredictSchemata(PredictSchemata.Builder builderForValue)
The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
.google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
Parameter | |
---|---|
Name | Description |
builderForValue | PredictSchemata.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public Model.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Returns | |
---|---|
Type | Description |
Model.Builder |
setSupportedDeploymentResourcesTypes(int index, Model.DeploymentResourcesType value)
public Model.Builder setSupportedDeploymentResourcesTypes(int index, Model.DeploymentResourcesType value)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int The index to set the value at. |
value | Model.DeploymentResourcesType The supportedDeploymentResourcesTypes to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setSupportedDeploymentResourcesTypesValue(int index, int value)
public Model.Builder setSupportedDeploymentResourcesTypesValue(int index, int value)
Output only. When this Model is deployed, its prediction resources are
described by the prediction_resources
field of the
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 and does not support
online predictions
(PredictionService.Predict
or
PredictionService.Explain).
Such a Model can serve predictions by using a
BatchPredictionJob, if it
has at least one entry each in
supported_input_storage_formats
and
supported_output_storage_formats.
repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int The index to set the value at. |
value | int The enum numeric value on the wire for supportedDeploymentResourcesTypes to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setSupportedExportFormats(int index, Model.ExportFormat value)
public Model.Builder setSupportedExportFormats(int index, Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
value | Model.ExportFormat |
Returns | |
---|---|
Type | Description |
Model.Builder |
setSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
public Model.Builder setSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int |
builderForValue | Model.ExportFormat.Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setSupportedInputStorageFormats(int index, String value)
public Model.Builder setSupportedInputStorageFormats(int index, String value)
Output only. The formats this Model supports in BatchPredictionJob.input_config. If 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.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.tf-record
The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource.tf-record-gzip
Similar totf-record
, but the file is gzipped. Uses GcsSource.bigquery
Each instance is a single row in BigQuery. Uses BigQuerySource.file-list
Each line of the file is the location of an instance to process, usesgcs_source
field of the InputConfig object.
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int The index to set the value at. |
value | String The supportedInputStorageFormats to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setSupportedOutputStorageFormats(int index, String value)
public Model.Builder setSupportedOutputStorageFormats(int index, String value)
Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and 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.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.bigquery
Each prediction is a single row in a BigQuery table, uses BigQueryDestination .
If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameters | |
---|---|
Name | Description |
index | int The index to set the value at. |
value | String The supportedOutputStorageFormats to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setTrainingPipeline(String value)
public Model.Builder setTrainingPipeline(String value)
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) = { ... }
Parameter | |
---|---|
Name | Description |
value | String The trainingPipeline to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setTrainingPipelineBytes(ByteString value)
public Model.Builder setTrainingPipelineBytes(ByteString value)
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) = { ... }
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for trainingPipeline to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final Model.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
Model.Builder |
setUpdateTime(Timestamp value)
public Model.Builder setUpdateTime(Timestamp value)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
setUpdateTime(Timestamp.Builder builderForValue)
public Model.Builder setUpdateTime(Timestamp.Builder builderForValue)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setVersionAliases(int index, String value)
public Model.Builder setVersionAliases(int index, String value)
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{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 | |
---|---|
Name | Description |
index | int The index to set the value at. |
value | String The versionAliases to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setVersionCreateTime(Timestamp value)
public Model.Builder setVersionCreateTime(Timestamp value)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
setVersionCreateTime(Timestamp.Builder builderForValue)
public Model.Builder setVersionCreateTime(Timestamp.Builder builderForValue)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |
setVersionDescription(String value)
public Model.Builder setVersionDescription(String value)
The description of this version.
string version_description = 30;
Parameter | |
---|---|
Name | Description |
value | String The versionDescription to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setVersionDescriptionBytes(ByteString value)
public Model.Builder setVersionDescriptionBytes(ByteString value)
The description of this version.
string version_description = 30;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for versionDescription to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setVersionId(String value)
public Model.Builder setVersionId(String value)
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];
Parameter | |
---|---|
Name | Description |
value | String The versionId to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setVersionIdBytes(ByteString value)
public Model.Builder setVersionIdBytes(ByteString value)
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];
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for versionId to set. |
Returns | |
---|---|
Type | Description |
Model.Builder | This builder for chaining. |
setVersionUpdateTime(Timestamp value)
public Model.Builder setVersionUpdateTime(Timestamp value)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
value | Timestamp |
Returns | |
---|---|
Type | Description |
Model.Builder |
setVersionUpdateTime(Timestamp.Builder builderForValue)
public Model.Builder setVersionUpdateTime(Timestamp.Builder builderForValue)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
Parameter | |
---|---|
Name | Description |
builderForValue | Builder |
Returns | |
---|---|
Type | Description |
Model.Builder |