Package com.google.cloud.aiplatform.v1

Class Model

java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.aiplatform.v1.Model
All Implemented Interfaces:
ModelOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
@Generated public final class Model extends com.google.protobuf.GeneratedMessage implements ModelOrBuilder
 A trained machine learning Model.
Protobuf type google.cloud.aiplatform.v1.Model
See Also:

  • Field Details

    • NAME_FIELD_NUMBER

      public static final int NAME_FIELD_NUMBER
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    • VERSION_ID_FIELD_NUMBER

      public static final int VERSION_ID_FIELD_NUMBER
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    • VERSION_ALIASES_FIELD_NUMBER

      public static final int VERSION_ALIASES_FIELD_NUMBER
      See Also:

    • VERSION_CREATE_TIME_FIELD_NUMBER

      public static final int VERSION_CREATE_TIME_FIELD_NUMBER
      See Also:

    • VERSION_UPDATE_TIME_FIELD_NUMBER

      public static final int VERSION_UPDATE_TIME_FIELD_NUMBER
      See Also:

    • DISPLAY_NAME_FIELD_NUMBER

      public static final int DISPLAY_NAME_FIELD_NUMBER
      See Also:

    • DESCRIPTION_FIELD_NUMBER

      public static final int DESCRIPTION_FIELD_NUMBER
      See Also:

    • VERSION_DESCRIPTION_FIELD_NUMBER

      public static final int VERSION_DESCRIPTION_FIELD_NUMBER
      See Also:

    • DEFAULT_CHECKPOINT_ID_FIELD_NUMBER

      public static final int DEFAULT_CHECKPOINT_ID_FIELD_NUMBER
      See Also:

    • PREDICT_SCHEMATA_FIELD_NUMBER

      public static final int PREDICT_SCHEMATA_FIELD_NUMBER
      See Also:

    • METADATA_SCHEMA_URI_FIELD_NUMBER

      public static final int METADATA_SCHEMA_URI_FIELD_NUMBER
      See Also:

    • METADATA_FIELD_NUMBER

      public static final int METADATA_FIELD_NUMBER
      See Also:

    • SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER

      public static final int SUPPORTED_EXPORT_FORMATS_FIELD_NUMBER
      See Also:

    • TRAINING_PIPELINE_FIELD_NUMBER

      public static final int TRAINING_PIPELINE_FIELD_NUMBER
      See Also:

    • PIPELINE_JOB_FIELD_NUMBER

      public static final int PIPELINE_JOB_FIELD_NUMBER
      See Also:

    • CONTAINER_SPEC_FIELD_NUMBER

      public static final int CONTAINER_SPEC_FIELD_NUMBER
      See Also:

    • ARTIFACT_URI_FIELD_NUMBER

      public static final int ARTIFACT_URI_FIELD_NUMBER
      See Also:

    • SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER

      public static final int SUPPORTED_DEPLOYMENT_RESOURCES_TYPES_FIELD_NUMBER
      See Also:

    • SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER

      public static final int SUPPORTED_INPUT_STORAGE_FORMATS_FIELD_NUMBER
      See Also:

    • SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER

      public static final int SUPPORTED_OUTPUT_STORAGE_FORMATS_FIELD_NUMBER
      See Also:

    • CREATE_TIME_FIELD_NUMBER

      public static final int CREATE_TIME_FIELD_NUMBER
      See Also:

    • UPDATE_TIME_FIELD_NUMBER

      public static final int UPDATE_TIME_FIELD_NUMBER
      See Also:

    • DEPLOYED_MODELS_FIELD_NUMBER

      public static final int DEPLOYED_MODELS_FIELD_NUMBER
      See Also:

    • EXPLANATION_SPEC_FIELD_NUMBER

      public static final int EXPLANATION_SPEC_FIELD_NUMBER
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    • ETAG_FIELD_NUMBER

      public static final int ETAG_FIELD_NUMBER
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    • LABELS_FIELD_NUMBER

      public static final int LABELS_FIELD_NUMBER
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    • DATA_STATS_FIELD_NUMBER

      public static final int DATA_STATS_FIELD_NUMBER
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    • ENCRYPTION_SPEC_FIELD_NUMBER

      public static final int ENCRYPTION_SPEC_FIELD_NUMBER
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    • MODEL_SOURCE_INFO_FIELD_NUMBER

      public static final int MODEL_SOURCE_INFO_FIELD_NUMBER
      See Also:

    • ORIGINAL_MODEL_INFO_FIELD_NUMBER

      public static final int ORIGINAL_MODEL_INFO_FIELD_NUMBER
      See Also:

    • METADATA_ARTIFACT_FIELD_NUMBER

      public static final int METADATA_ARTIFACT_FIELD_NUMBER
      See Also:

    • BASE_MODEL_SOURCE_FIELD_NUMBER

      public static final int BASE_MODEL_SOURCE_FIELD_NUMBER
      See Also:

    • SATISFIES_PZS_FIELD_NUMBER

      public static final int SATISFIES_PZS_FIELD_NUMBER
      See Also:

    • SATISFIES_PZI_FIELD_NUMBER

      public static final int SATISFIES_PZI_FIELD_NUMBER
      See Also:

    • CHECKPOINTS_FIELD_NUMBER

      public static final int CHECKPOINTS_FIELD_NUMBER
      See Also:

  • Method Details

    • getDescriptor

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

    • internalGetMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
      Overrides:
      internalGetMapFieldReflection in class com.google.protobuf.GeneratedMessage

    • internalGetFieldAccessorTable

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

    • getName

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

    • getNameBytes

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

    • getVersionId

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

    • getVersionIdBytes

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

    • getVersionAliasesList

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

    • getVersionAliasesCount

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

    • getVersionAliases

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

    • getVersionAliasesBytes

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

    • hasVersionCreateTime

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

    • getVersionCreateTime

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

    • getVersionCreateTimeOrBuilder

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

    • hasVersionUpdateTime

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

    • getVersionUpdateTime

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

    • getVersionUpdateTimeOrBuilder

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

    • getDisplayName

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

    • getDisplayNameBytes

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

    • getDescription

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

    • getDescriptionBytes

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

    • getVersionDescription

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

    • getVersionDescriptionBytes

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

    • getDefaultCheckpointId

      public String getDefaultCheckpointId()
       The default checkpoint id of a model version.
      string default_checkpoint_id = 53;
      Specified by:
      getDefaultCheckpointId in interface ModelOrBuilder
      Returns:
      The defaultCheckpointId.

    • getDefaultCheckpointIdBytes

      public com.google.protobuf.ByteString getDefaultCheckpointIdBytes()
       The default checkpoint id of a model version.
      string default_checkpoint_id = 53;
      Specified by:
      getDefaultCheckpointIdBytes in interface ModelOrBuilder
      Returns:
      The bytes for defaultCheckpointId.

    • hasPredictSchemata

      public boolean hasPredictSchemata()
       The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
      Specified by:
      hasPredictSchemata in interface ModelOrBuilder
      Returns:
      Whether the predictSchemata field is set.

    • getPredictSchemata

      public PredictSchemata getPredictSchemata()
       The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
      Specified by:
      getPredictSchemata in interface ModelOrBuilder
      Returns:
      The predictSchemata.

    • getPredictSchemataOrBuilder

      public PredictSchemataOrBuilder getPredictSchemataOrBuilder()
       The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;
      Specified by:
      getPredictSchemataOrBuilder in interface ModelOrBuilder

    • getMetadataSchemaUri

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

    • getMetadataSchemaUriBytes

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

    • hasMetadata

      public boolean hasMetadata()
       Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
      .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
      Specified by:
      hasMetadata in interface ModelOrBuilder
      Returns:
      Whether the metadata field is set.

    • getMetadata

      public com.google.protobuf.Value getMetadata()
       Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
      .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
      Specified by:
      getMetadata in interface ModelOrBuilder
      Returns:
      The metadata.

    • getMetadataOrBuilder

      public com.google.protobuf.ValueOrBuilder getMetadataOrBuilder()
       Immutable. An additional information about the Model; the schema of the
 metadata can be found in
 [metadata_schema][google.cloud.aiplatform.v1.Model.metadata_schema_uri].
 Unset if the Model does not have any additional information.
      .google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];
      Specified by:
      getMetadataOrBuilder in interface ModelOrBuilder

    • getSupportedExportFormatsList

      public List<Model.ExportFormat> getSupportedExportFormatsList()
       Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
      repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedExportFormatsList in interface ModelOrBuilder

    • getSupportedExportFormatsOrBuilderList

      public List<? extends Model.ExportFormatOrBuilder> getSupportedExportFormatsOrBuilderList()
       Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
      repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedExportFormatsOrBuilderList in interface ModelOrBuilder

    • getSupportedExportFormatsCount

      public int getSupportedExportFormatsCount()
       Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
      repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedExportFormatsCount in interface ModelOrBuilder

    • getSupportedExportFormats

      public Model.ExportFormat getSupportedExportFormats(int index)
       Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
      repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedExportFormats in interface ModelOrBuilder

    • getSupportedExportFormatsOrBuilder

      public Model.ExportFormatOrBuilder getSupportedExportFormatsOrBuilder(int index)
       Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
      repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedExportFormatsOrBuilder in interface ModelOrBuilder

    • getTrainingPipeline

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

    • getTrainingPipelineBytes

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

    • 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) = { ... }
      Specified by:
      getPipelineJob in interface ModelOrBuilder
      Returns:
      The pipelineJob.

    • getPipelineJobBytes

      public com.google.protobuf.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) = { ... }
      Specified by:
      getPipelineJobBytes in interface ModelOrBuilder
      Returns:
      The bytes for pipelineJob.

    • hasContainerSpec

      public boolean hasContainerSpec()
       Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.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];
      Specified by:
      hasContainerSpec in interface ModelOrBuilder
      Returns:
      Whether the containerSpec field is set.

    • getContainerSpec

      public ModelContainerSpec getContainerSpec()
       Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.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];
      Specified by:
      getContainerSpec in interface ModelOrBuilder
      Returns:
      The containerSpec.

    • getContainerSpecOrBuilder

      public ModelContainerSpecOrBuilder getContainerSpecOrBuilder()
       Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.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];
      Specified by:
      getContainerSpecOrBuilder in interface ModelOrBuilder

    • getArtifactUri

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

    • getArtifactUriBytes

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

    • getSupportedDeploymentResourcesTypesList

      public List<Model.DeploymentResourcesType> getSupportedDeploymentResourcesTypesList()
       Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
 has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedDeploymentResourcesTypesList in interface ModelOrBuilder
      Returns:
      A list containing the supportedDeploymentResourcesTypes.

    • getSupportedDeploymentResourcesTypesCount

      public int getSupportedDeploymentResourcesTypesCount()
       Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
 has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedDeploymentResourcesTypesCount in interface ModelOrBuilder
      Returns:
      The count of supportedDeploymentResourcesTypes.

    • getSupportedDeploymentResourcesTypes

      public Model.DeploymentResourcesType getSupportedDeploymentResourcesTypes(int index)
       Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
 has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedDeploymentResourcesTypes in interface ModelOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The supportedDeploymentResourcesTypes at the given index.

    • getSupportedDeploymentResourcesTypesValueList

      public List<Integer> getSupportedDeploymentResourcesTypesValueList()
       Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
 has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedDeploymentResourcesTypesValueList in interface ModelOrBuilder
      Returns:
      A list containing the enum numeric values on the wire for supportedDeploymentResourcesTypes.

    • getSupportedDeploymentResourcesTypesValue

      public int getSupportedDeploymentResourcesTypesValue(int index)
       Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models]
 object. Because not all Models support all resource configuration types,
 the configuration types this Model supports are listed here. If no
 configuration types are listed, the Model cannot be deployed to an
 [Endpoint][google.cloud.aiplatform.v1.Endpoint] and does not support
 online predictions
 ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
 Such a Model can serve predictions by using a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
 has at least one entry each in
 [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
 and
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      repeated .google.cloud.aiplatform.v1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedDeploymentResourcesTypesValue in interface ModelOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The enum numeric value on the wire of supportedDeploymentResourcesTypes at the given index.

    • getSupportedInputStorageFormatsList

      public com.google.protobuf.ProtocolStringList getSupportedInputStorageFormatsList()
       Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedInputStorageFormatsList in interface ModelOrBuilder
      Returns:
      A list containing the supportedInputStorageFormats.

    • getSupportedInputStorageFormatsCount

      public int getSupportedInputStorageFormatsCount()
       Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedInputStorageFormatsCount in interface ModelOrBuilder
      Returns:
      The count of supportedInputStorageFormats.

    • getSupportedInputStorageFormats

      public String getSupportedInputStorageFormats(int index)
       Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedInputStorageFormats in interface ModelOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The supportedInputStorageFormats at the given index.

    • getSupportedInputStorageFormatsBytes

      public com.google.protobuf.ByteString getSupportedInputStorageFormatsBytes(int index)
       Output only. The formats this Model supports in
 [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.BatchPredictionJob.input_config].
 If
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 exists, the instances should be given as per that schema.

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each instance is a single line. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `csv`
 The CSV format, where each instance is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record`
 The TFRecord format, where each instance is a single record in tfrecord
 syntax. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `tf-record-gzip`
 Similar to `tf-record`, but the file is gzipped. Uses
 [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].

 * `bigquery`
 Each instance is a single row in BigQuery. Uses
 [BigQuerySource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.bigquery_source].

 * `file-list`
 Each line of the file is the location of an instance to process, uses
 `gcs_source` field of the
 [InputConfig][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig]
 object.


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedInputStorageFormatsBytes in interface ModelOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the supportedInputStorageFormats at the given index.

    • getSupportedOutputStorageFormatsList

      public com.google.protobuf.ProtocolStringList getSupportedOutputStorageFormatsList()
       Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedOutputStorageFormatsList in interface ModelOrBuilder
      Returns:
      A list containing the supportedOutputStorageFormats.

    • getSupportedOutputStorageFormatsCount

      public int getSupportedOutputStorageFormatsCount()
       Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedOutputStorageFormatsCount in interface ModelOrBuilder
      Returns:
      The count of supportedOutputStorageFormats.

    • getSupportedOutputStorageFormats

      public String getSupportedOutputStorageFormats(int index)
       Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedOutputStorageFormats in interface ModelOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The supportedOutputStorageFormats at the given index.

    • getSupportedOutputStorageFormatsBytes

      public com.google.protobuf.ByteString getSupportedOutputStorageFormatsBytes(int index)
       Output only. The formats this Model supports in
 [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.BatchPredictionJob.output_config].
 If both
 [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri]
 exist, the predictions are returned together with their instances. In other
 words, the prediction has the original instance data first, followed by the
 actual prediction content (as per the schema).

 The possible formats are:

 * `jsonl`
 The JSON Lines format, where each prediction is a single line. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `csv`
 The CSV format, where each prediction is a single comma-separated line.
 The first line in the file is the header, containing comma-separated field
 names. Uses
 [GcsDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].

 * `bigquery`
 Each prediction is a single row in a BigQuery table, uses
 [BigQueryDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.bigquery_destination]
 .


 If this Model doesn't support any of these formats it means it cannot be
 used with a
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
 However, if it has
 [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
 it could serve online predictions by using
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 or
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
      repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSupportedOutputStorageFormatsBytes in interface ModelOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the supportedOutputStorageFormats at the given index.

    • hasCreateTime

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

    • getCreateTime

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

    • getCreateTimeOrBuilder

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

    • hasUpdateTime

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

    • getUpdateTime

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

    • getUpdateTimeOrBuilder

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

    • getDeployedModelsList

      public List<DeployedModelRef> getDeployedModelsList()
       Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
      repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getDeployedModelsList in interface ModelOrBuilder

    • getDeployedModelsOrBuilderList

      public List<? extends DeployedModelRefOrBuilder> getDeployedModelsOrBuilderList()
       Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
      repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getDeployedModelsOrBuilderList in interface ModelOrBuilder

    • getDeployedModelsCount

      public int getDeployedModelsCount()
       Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
      repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getDeployedModelsCount in interface ModelOrBuilder

    • getDeployedModels

      public DeployedModelRef getDeployedModels(int index)
       Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
      repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getDeployedModels in interface ModelOrBuilder

    • getDeployedModelsOrBuilder

      public DeployedModelRefOrBuilder getDeployedModelsOrBuilder(int index)
       Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
      repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getDeployedModelsOrBuilder in interface ModelOrBuilder

    • hasExplanationSpec

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

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] after
 being [deployed][google.cloud.aiplatform.v1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
      .google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
      Specified by:
      hasExplanationSpec in interface ModelOrBuilder
      Returns:
      Whether the explanationSpec field is set.

    • getExplanationSpec

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

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] after
 being [deployed][google.cloud.aiplatform.v1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
      .google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
      Specified by:
      getExplanationSpec in interface ModelOrBuilder
      Returns:
      The explanationSpec.

    • getExplanationSpecOrBuilder

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

 The Model can be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] after
 being [deployed][google.cloud.aiplatform.v1.EndpointService.DeployModel] if
 it is populated. The Model can be used for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 if it is populated.

 All fields of the explanation_spec can be overridden by
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model],
 or
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].

 If the default explanation specification is not set for this Model, this
 Model can still be used for
 [requesting
 explanation][google.cloud.aiplatform.v1.PredictionService.Explain] by
 setting
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 of
 [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model]
 and for [batch
 explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
 by setting
 [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
 of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
      .google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 23;
      Specified by:
      getExplanationSpecOrBuilder in interface ModelOrBuilder

    • getEtag

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

    • getEtagBytes

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

    • getLabelsCount

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

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

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

    • containsLabels

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

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

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

    • getLabels

      @Deprecated public Map<String,String> getLabels()
      Deprecated.
      Use getLabelsMap() instead.
      Specified by:
      getLabels in interface ModelOrBuilder

    • getLabelsMap

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

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

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

    • getLabelsOrDefault

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

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

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

    • getLabelsOrThrow

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

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

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

    • 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.TrainingPipeline.input_data_config].
      .google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
      Specified by:
      hasDataStats in interface ModelOrBuilder
      Returns:
      Whether the dataStats field is set.

    • 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.TrainingPipeline.input_data_config].
      .google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
      Specified by:
      getDataStats in interface ModelOrBuilder
      Returns:
      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.TrainingPipeline.input_data_config].
      .google.cloud.aiplatform.v1.Model.DataStats data_stats = 21;
      Specified by:
      getDataStatsOrBuilder in interface ModelOrBuilder

    • hasEncryptionSpec

      public boolean hasEncryptionSpec()
       Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;
      Specified by:
      hasEncryptionSpec in interface ModelOrBuilder
      Returns:
      Whether the encryptionSpec field is set.

    • getEncryptionSpec

      public EncryptionSpec getEncryptionSpec()
       Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;
      Specified by:
      getEncryptionSpec in interface ModelOrBuilder
      Returns:
      The encryptionSpec.

    • getEncryptionSpecOrBuilder

      public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
       Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;
      Specified by:
      getEncryptionSpecOrBuilder in interface ModelOrBuilder

    • hasModelSourceInfo

      public boolean hasModelSourceInfo()
       Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
      .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasModelSourceInfo in interface ModelOrBuilder
      Returns:
      Whether the modelSourceInfo field is set.

    • getModelSourceInfo

      public ModelSourceInfo getModelSourceInfo()
       Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
      .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getModelSourceInfo in interface ModelOrBuilder
      Returns:
      The modelSourceInfo.

    • getModelSourceInfoOrBuilder

      public ModelSourceInfoOrBuilder getModelSourceInfoOrBuilder()
       Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or saved and tuned from Genie or
 Model Garden.
      .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getModelSourceInfoOrBuilder in interface ModelOrBuilder

    • hasOriginalModelInfo

      public boolean hasOriginalModelInfo()
       Output only. If this Model is a copy of another Model, this contains info
 about the original.
      .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasOriginalModelInfo in interface ModelOrBuilder
      Returns:
      Whether the originalModelInfo field is set.

    • getOriginalModelInfo

      public Model.OriginalModelInfo getOriginalModelInfo()
       Output only. If this Model is a copy of another Model, this contains info
 about the original.
      .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getOriginalModelInfo in interface ModelOrBuilder
      Returns:
      The originalModelInfo.

    • getOriginalModelInfoOrBuilder

      public Model.OriginalModelInfoOrBuilder getOriginalModelInfoOrBuilder()
       Output only. If this Model is a copy of another Model, this contains info
 about the original.
      .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getOriginalModelInfoOrBuilder in interface ModelOrBuilder

    • getMetadataArtifact

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

    • getMetadataArtifactBytes

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

    • 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];
      Specified by:
      hasBaseModelSource in interface ModelOrBuilder
      Returns:
      Whether the baseModelSource field is set.

    • 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];
      Specified by:
      getBaseModelSource in interface ModelOrBuilder
      Returns:
      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];
      Specified by:
      getBaseModelSourceOrBuilder in interface ModelOrBuilder

    • getSatisfiesPzs

      public boolean getSatisfiesPzs()
       Output only. Reserved for future use.
      bool satisfies_pzs = 51 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzs in interface ModelOrBuilder
      Returns:
      The satisfiesPzs.

    • getSatisfiesPzi

      public boolean getSatisfiesPzi()
       Output only. Reserved for future use.
      bool satisfies_pzi = 52 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzi in interface ModelOrBuilder
      Returns:
      The satisfiesPzi.

    • getCheckpointsList

      public List<Checkpoint> getCheckpointsList()
       Optional. Output only. The checkpoints of the model.
      repeated .google.cloud.aiplatform.v1.Checkpoint checkpoints = 57 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getCheckpointsList in interface ModelOrBuilder

    • getCheckpointsOrBuilderList

      public List<? extends CheckpointOrBuilder> getCheckpointsOrBuilderList()
       Optional. Output only. The checkpoints of the model.
      repeated .google.cloud.aiplatform.v1.Checkpoint checkpoints = 57 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getCheckpointsOrBuilderList in interface ModelOrBuilder

    • getCheckpointsCount

      public int getCheckpointsCount()
       Optional. Output only. The checkpoints of the model.
      repeated .google.cloud.aiplatform.v1.Checkpoint checkpoints = 57 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getCheckpointsCount in interface ModelOrBuilder

    • getCheckpoints

      public Checkpoint getCheckpoints(int index)
       Optional. Output only. The checkpoints of the model.
      repeated .google.cloud.aiplatform.v1.Checkpoint checkpoints = 57 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getCheckpoints in interface ModelOrBuilder

    • getCheckpointsOrBuilder

      public CheckpointOrBuilder getCheckpointsOrBuilder(int index)
       Optional. Output only. The checkpoints of the model.
      repeated .google.cloud.aiplatform.v1.Checkpoint checkpoints = 57 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getCheckpointsOrBuilder in interface ModelOrBuilder

    • isInitialized

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

    • writeTo

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

    • getSerializedSize

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

    • equals

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

    • hashCode

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

    • parseFrom

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

    • parseFrom

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

    • parseFrom

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

    • parseFrom

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

    • parseFrom

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

    • parseFrom

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

    • parseFrom

      public static Model parseFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

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

    • parseDelimitedFrom

      public static Model parseDelimitedFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static Model parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseFrom

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

    • parseFrom

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

    • newBuilderForType

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

    • newBuilder

      public static Model.Builder newBuilder()

    • newBuilder

      public static Model.Builder newBuilder(Model prototype)

    • toBuilder

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

    • newBuilderForType

      protected Model.Builder newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent)
      Overrides:
      newBuilderForType in class com.google.protobuf.AbstractMessage

    • getDefaultInstance

      public static Model getDefaultInstance()

    • parser

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

    • getParserForType

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

    • getDefaultInstanceForType

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