Class Model (3.42.0) 

public final class Model extends GeneratedMessageV3 implements ModelOrBuilder

A trained machine learning Model.

Protobuf type google.cloud.aiplatform.v1.Model

Inheritance

Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > Model

Implements

ModelOrBuilder

Static Fields

ARTIFACT_URI_FIELD_NUMBER

public static final int ARTIFACT_URI_FIELD_NUMBER
Field Value
Type Description
int

BASE_MODEL_SOURCE_FIELD_NUMBER

public static final int BASE_MODEL_SOURCE_FIELD_NUMBER
Field Value
Type Description
int

CONTAINER_SPEC_FIELD_NUMBER

public static final int CONTAINER_SPEC_FIELD_NUMBER
Field Value
Type Description
int

CREATE_TIME_FIELD_NUMBER

public static final int CREATE_TIME_FIELD_NUMBER
Field Value
Type Description
int

DATA_STATS_FIELD_NUMBER

public static final int DATA_STATS_FIELD_NUMBER
Field Value
Type Description
int

DEPLOYED_MODELS_FIELD_NUMBER

public static final int DEPLOYED_MODELS_FIELD_NUMBER
Field Value
Type Description
int

DESCRIPTION_FIELD_NUMBER

public static final int DESCRIPTION_FIELD_NUMBER
Field Value
Type Description
int

DISPLAY_NAME_FIELD_NUMBER

public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
Type Description
int

ENCRYPTION_SPEC_FIELD_NUMBER

public static final int ENCRYPTION_SPEC_FIELD_NUMBER
Field Value
Type Description
int

ETAG_FIELD_NUMBER

public static final int ETAG_FIELD_NUMBER
Field Value
Type Description
int

EXPLANATION_SPEC_FIELD_NUMBER

public static final int EXPLANATION_SPEC_FIELD_NUMBER
Field Value
Type Description
int

LABELS_FIELD_NUMBER

public static final int LABELS_FIELD_NUMBER
Field Value
Type Description
int

METADATA_ARTIFACT_FIELD_NUMBER

public static final int METADATA_ARTIFACT_FIELD_NUMBER
Field Value
Type Description
int

METADATA_FIELD_NUMBER

public static final int METADATA_FIELD_NUMBER
Field Value
Type Description
int

METADATA_SCHEMA_URI_FIELD_NUMBER

public static final int METADATA_SCHEMA_URI_FIELD_NUMBER
Field Value
Type Description
int

MODEL_SOURCE_INFO_FIELD_NUMBER

public static final int MODEL_SOURCE_INFO_FIELD_NUMBER
Field Value
Type Description
int

NAME_FIELD_NUMBER

public static final int NAME_FIELD_NUMBER
Field Value
Type Description
int

ORIGINAL_MODEL_INFO_FIELD_NUMBER

public static final int ORIGINAL_MODEL_INFO_FIELD_NUMBER
Field Value
Type Description
int

PIPELINE_JOB_FIELD_NUMBER

public static final int PIPELINE_JOB_FIELD_NUMBER
Field Value
Type Description
int

PREDICT_SCHEMATA_FIELD_NUMBER

public static final int PREDICT_SCHEMATA_FIELD_NUMBER
Field Value
Type Description
int

SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER

public static final int SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER
Field Value
Type Description
int

SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER

public static final int SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER
Field Value
Type Description
int

SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER

public static final int SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER
Field Value
Type Description
int

SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER

public static final int SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER
Field Value
Type Description
int

TRAINING_PIPELINE_FIELD_NUMBER

public static final int TRAINING_PIPELINE_FIELD_NUMBER
Field Value
Type Description
int

UPDATE_TIME_FIELD_NUMBER

public static final int UPDATE_TIME_FIELD_NUMBER
Field Value
Type Description
int

VERSION_ALIASES_FIELD_NUMBER

public static final int VERSION_ALIASES_FIELD_NUMBER
Field Value
Type Description
int

VERSION_CREATE_TIME_FIELD_NUMBER

public static final int VERSION_CREATE_TIME_FIELD_NUMBER
Field Value
Type Description
int

VERSION_DESCRIPTION_FIELD_NUMBER

public static final int VERSION_DESCRIPTION_FIELD_NUMBER
Field Value
Type Description
int

VERSION_ID_FIELD_NUMBER

public static final int VERSION_ID_FIELD_NUMBER
Field Value
Type Description
int

VERSION_UPDATE_TIME_FIELD_NUMBER

public static final int VERSION_UPDATE_TIME_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

public static Model getDefaultInstance()
Returns
Type Description
Model

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

newBuilder()

public static Model.Builder newBuilder()
Returns
Type Description
Model.Builder

newBuilder(Model prototype)

public static Model.Builder newBuilder(Model prototype)
Parameter
Name Description
prototype Model
Returns
Type Description
Model.Builder

parseDelimitedFrom(InputStream input)

public static Model parseDelimitedFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static Model parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseFrom(byte[] data)

public static Model parseFrom(byte[] data)
Parameter
Name Description
data byte[]
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static Model parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data byte[]
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static Model parseFrom(ByteString data)
Parameter
Name Description
data ByteString
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static Model parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteString
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static Model parseFrom(CodedInputStream input)
Parameter
Name Description
input CodedInputStream
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static Model parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseFrom(InputStream input)

public static Model parseFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static Model parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
IOException

parseFrom(ByteBuffer data)

public static Model parseFrom(ByteBuffer data)
Parameter
Name Description
data ByteBuffer
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static Model parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteBuffer
extensionRegistry ExtensionRegistryLite
Returns
Type Description
Model
Exceptions
Type Description
InvalidProtocolBufferException

parser()

public static Parser<Model> parser()
Returns
Type Description
Parser<Model>

Methods

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

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
boolean
Overrides

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.

getBaseModelSource()

public Model.BaseModelSource getBaseModelSource()

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

.google.cloud.aiplatform.v1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
Model.BaseModelSource

The baseModelSource.

getBaseModelSourceOrBuilder()

public Model.BaseModelSourceOrBuilder getBaseModelSourceOrBuilder()

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

.google.cloud.aiplatform.v1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
Model.BaseModelSourceOrBuilder

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.

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.

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.

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

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.

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.

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.

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.

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.

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

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.

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

getParserForType()

public Parser<Model> getParserForType()
Returns
Type Description
Parser<Model>
Overrides

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.

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

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
int
Overrides

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

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 to tf-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, uses gcs_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 to tf-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, uses gcs_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 to tf-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, uses gcs_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 to tf-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, uses gcs_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.

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.

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.

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

hasBaseModelSource()

public boolean hasBaseModelSource()

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

.google.cloud.aiplatform.v1.Model.BaseModelSource base_model_source = 50 [(.google.api.field_behavior) = OPTIONAL];

Returns
Type Description
boolean

Whether the baseModelSource field is set.

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.

hashCode()

public int hashCode()
Returns
Type Description
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

newBuilderForType()

public Model.Builder newBuilderForType()
Returns
Type Description
Model.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected Model.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Name Description
parent BuilderParent
Returns
Type Description
Model.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Name Description
unused UnusedPrivateParameter
Returns
Type Description
Object
Overrides

toBuilder()

public Model.Builder toBuilder()
Returns
Type Description
Model.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
Name Description
output CodedOutputStream
Overrides
Exceptions
Type Description
IOException