Package com.google.cloud.aiplatform.v1

Class Model.Builder

  • All Implemented Interfaces:
    ModelOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
    Enclosing class:
    Model
    public static final class Model.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>
implements ModelOrBuilder
     A trained machine learning Model.
    Protobuf type google.cloud.aiplatform.v1.Model

    • Method Detail

      • getDescriptor

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

      • internalGetMapField

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

      • internalGetMutableMapField

        protected com.google.protobuf.MapField internalGetMutableMapField​(int number)
        Overrides:
        internalGetMutableMapField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • clear

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

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • getDefaultInstanceForType

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

      • build

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

      • buildPartial

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

      • clone

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

      • setField

        public Model.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                              Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • clearField

        public Model.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • clearOneof

        public Model.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • setRepeatedField

        public Model.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                      int index,
                                      Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • addRepeatedField

        public Model.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                      Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • mergeFrom

        public Model.Builder mergeFrom​(com.google.protobuf.Message other)
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<Model.Builder>

      • isInitialized

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

      • mergeFrom

        public Model.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                               com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                        throws IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<Model.Builder>
        Throws:
        IOException

      • 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.

      • setName

        public Model.Builder setName​(String value)
         The resource name of the Model.
        string name = 1;
        Parameters:
        value - The name to set.
        Returns:
        This builder for chaining.

      • clearName

        public Model.Builder clearName()
         The resource name of the Model.
        string name = 1;
        Returns:
        This builder for chaining.

      • setNameBytes

        public Model.Builder setNameBytes​(com.google.protobuf.ByteString value)
         The resource name of the Model.
        string name = 1;
        Parameters:
        value - The bytes for name to set.
        Returns:
        This builder for chaining.

      • 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.

      • setVersionId

        public Model.Builder setVersionId​(String value)
         Output only. Immutable. The version ID of the model.
 A new version is committed when a new model version is uploaded or
 trained under an existing model id. It is an auto-incrementing decimal
 number in string representation.
        string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
        Parameters:
        value - The versionId to set.
        Returns:
        This builder for chaining.

      • clearVersionId

        public Model.Builder clearVersionId()
         Output only. Immutable. The version ID of the model.
 A new version is committed when a new model version is uploaded or
 trained under an existing model id. It is an auto-incrementing decimal
 number in string representation.
        string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        This builder for chaining.

      • setVersionIdBytes

        public Model.Builder setVersionIdBytes​(com.google.protobuf.ByteString value)
         Output only. Immutable. The version ID of the model.
 A new version is committed when a new model version is uploaded or
 trained under an existing model id. It is an auto-incrementing decimal
 number in string representation.
        string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
        Parameters:
        value - The bytes for versionId to set.
        Returns:
        This builder for chaining.

      • 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.

      • setVersionAliases

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

      • addVersionAliases

        public Model.Builder addVersionAliases​(String value)
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Parameters:
        value - The versionAliases to add.
        Returns:
        This builder for chaining.

      • addAllVersionAliases

        public Model.Builder addAllVersionAliases​(Iterable<String> values)
         User provided version aliases so that a model version can be referenced via
 alias (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_alias}`
 instead of auto-generated version id (i.e.
 `projects/{project}/locations/{location}/models/{model_id}@{version_id})`.
 The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
 version_id. A default version alias will be created for the first version
 of the model, and there must be exactly one default version alias for a
 model.
        repeated string version_aliases = 29;
        Parameters:
        values - The versionAliases to add.
        Returns:
        This builder for chaining.

      • clearVersionAliases

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

      • addVersionAliasesBytes

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

      • 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.

      • setVersionCreateTime

        public Model.Builder setVersionCreateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setVersionCreateTime

        public Model.Builder setVersionCreateTime​(com.google.protobuf.Timestamp.Builder builderForValue)
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeVersionCreateTime

        public Model.Builder mergeVersionCreateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearVersionCreateTime

        public Model.Builder clearVersionCreateTime()
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getVersionCreateTimeBuilder

        public com.google.protobuf.Timestamp.Builder getVersionCreateTimeBuilder()
         Output only. Timestamp when this version was created.
        .google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • 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.

      • setVersionUpdateTime

        public Model.Builder setVersionUpdateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setVersionUpdateTime

        public Model.Builder setVersionUpdateTime​(com.google.protobuf.Timestamp.Builder builderForValue)
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeVersionUpdateTime

        public Model.Builder mergeVersionUpdateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearVersionUpdateTime

        public Model.Builder clearVersionUpdateTime()
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getVersionUpdateTimeBuilder

        public com.google.protobuf.Timestamp.Builder getVersionUpdateTimeBuilder()
         Output only. Timestamp when this version was most recently updated.
        .google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • 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.

      • setDisplayName

        public Model.Builder setDisplayName​(String value)
         Required. The display name of the Model.
 The name can be up to 128 characters long and can consist of any UTF-8
 characters.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Parameters:
        value - The displayName to set.
        Returns:
        This builder for chaining.

      • clearDisplayName

        public Model.Builder clearDisplayName()
         Required. The display name of the Model.
 The name can be up to 128 characters long and can consist of any UTF-8
 characters.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        This builder for chaining.

      • setDisplayNameBytes

        public Model.Builder setDisplayNameBytes​(com.google.protobuf.ByteString value)
         Required. The display name of the Model.
 The name can be up to 128 characters long and can consist of any UTF-8
 characters.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Parameters:
        value - The bytes for displayName to set.
        Returns:
        This builder for chaining.

      • 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.

      • setDescription

        public Model.Builder setDescription​(String value)
         The description of the Model.
        string description = 3;
        Parameters:
        value - The description to set.
        Returns:
        This builder for chaining.

      • clearDescription

        public Model.Builder clearDescription()
         The description of the Model.
        string description = 3;
        Returns:
        This builder for chaining.

      • setDescriptionBytes

        public Model.Builder setDescriptionBytes​(com.google.protobuf.ByteString value)
         The description of the Model.
        string description = 3;
        Parameters:
        value - The bytes for description to set.
        Returns:
        This builder for chaining.

      • 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.

      • setVersionDescription

        public Model.Builder setVersionDescription​(String value)
         The description of this version.
        string version_description = 30;
        Parameters:
        value - The versionDescription to set.
        Returns:
        This builder for chaining.

      • clearVersionDescription

        public Model.Builder clearVersionDescription()
         The description of this version.
        string version_description = 30;
        Returns:
        This builder for chaining.

      • setVersionDescriptionBytes

        public Model.Builder setVersionDescriptionBytes​(com.google.protobuf.ByteString value)
         The description of this version.
        string version_description = 30;
        Parameters:
        value - The bytes for versionDescription to set.
        Returns:
        This builder for chaining.

      • 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.

      • setPredictSchemata

        public Model.Builder setPredictSchemata​(PredictSchemata value)
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
        .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;

      • setPredictSchemata

        public Model.Builder setPredictSchemata​(PredictSchemata.Builder builderForValue)
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
        .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;

      • mergePredictSchemata

        public Model.Builder mergePredictSchemata​(PredictSchemata value)
         The schemata that describe formats of the Model's predictions and
 explanations as given and returned via
 [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
 and
 [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
        .google.cloud.aiplatform.v1.PredictSchemata predict_schemata = 4;

      • clearPredictSchemata

        public Model.Builder clearPredictSchemata()
         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;

      • getPredictSchemataBuilder

        public PredictSchemata.Builder getPredictSchemataBuilder()
         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;

      • 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.

      • setMetadataSchemaUri

        public Model.Builder setMetadataSchemaUri​(String value)
         Immutable. Points to a YAML file stored on Google Cloud Storage describing
 additional information about the Model, that is specific to it. Unset if
 the Model does not have any additional information. The schema is defined
 as an OpenAPI 3.0.2 [Schema
 Object](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];
        Parameters:
        value - The metadataSchemaUri to set.
        Returns:
        This builder for chaining.

      • clearMetadataSchemaUri

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

      • setMetadataSchemaUriBytes

        public Model.Builder setMetadataSchemaUriBytes​(com.google.protobuf.ByteString value)
         Immutable. Points to a YAML file stored on Google Cloud Storage describing
 additional information about the Model, that is specific to it. Unset if
 the Model does not have any additional information. The schema is defined
 as an OpenAPI 3.0.2 [Schema
 Object](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];
        Parameters:
        value - The bytes for metadataSchemaUri to set.
        Returns:
        This builder for chaining.

      • 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.

      • setMetadata

        public Model.Builder setMetadata​(com.google.protobuf.Value value)
         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];

      • setMetadata

        public Model.Builder setMetadata​(com.google.protobuf.Value.Builder builderForValue)
         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];

      • mergeMetadata

        public Model.Builder mergeMetadata​(com.google.protobuf.Value value)
         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];

      • clearMetadata

        public Model.Builder clearMetadata()
         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];

      • getMetadataBuilder

        public com.google.protobuf.Value.Builder getMetadataBuilder()
         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];

      • 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

      • 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

      • setSupportedExportFormats

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

      • setSupportedExportFormats

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

      • addSupportedExportFormats

        public Model.Builder addSupportedExportFormats​(Model.ExportFormat value)
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addSupportedExportFormats

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

      • addSupportedExportFormats

        public Model.Builder addSupportedExportFormats​(Model.ExportFormat.Builder builderForValue)
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addSupportedExportFormats

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

      • addAllSupportedExportFormats

        public Model.Builder addAllSupportedExportFormats​(Iterable<? extends Model.ExportFormat> values)
         Output only. The formats in which this Model may be exported. If empty,
 this Model is not available for export.
        repeated .google.cloud.aiplatform.v1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearSupportedExportFormats

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

      • removeSupportedExportFormats

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

      • getSupportedExportFormatsBuilder

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

      • 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

      • 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

      • addSupportedExportFormatsBuilder

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

      • addSupportedExportFormatsBuilder

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

      • getSupportedExportFormatsBuilderList

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

      • 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.

      • setTrainingPipeline

        public Model.Builder setTrainingPipeline​(String value)
         Output only. The resource name of the TrainingPipeline that uploaded this
 Model, if any.
        string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
        Parameters:
        value - The trainingPipeline to set.
        Returns:
        This builder for chaining.

      • clearTrainingPipeline

        public Model.Builder clearTrainingPipeline()
         Output only. The resource name of the TrainingPipeline that uploaded this
 Model, if any.
        string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
        Returns:
        This builder for chaining.

      • setTrainingPipelineBytes

        public Model.Builder setTrainingPipelineBytes​(com.google.protobuf.ByteString value)
         Output only. The resource name of the TrainingPipeline that uploaded this
 Model, if any.
        string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
        Parameters:
        value - The bytes for trainingPipeline to set.
        Returns:
        This builder for chaining.

      • 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.

      • setPipelineJob

        public Model.Builder setPipelineJob​(String value)
         Optional. This field is populated if the model is produced by a pipeline
 job.
        string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
        Parameters:
        value - The pipelineJob to set.
        Returns:
        This builder for chaining.

      • clearPipelineJob

        public Model.Builder clearPipelineJob()
         Optional. This field is populated if the model is produced by a pipeline
 job.
        string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
        Returns:
        This builder for chaining.

      • setPipelineJobBytes

        public Model.Builder setPipelineJobBytes​(com.google.protobuf.ByteString value)
         Optional. This field is populated if the model is produced by a pipeline
 job.
        string pipeline_job = 47 [(.google.api.field_behavior) = OPTIONAL, (.google.api.resource_reference) = { ... }
        Parameters:
        value - The bytes for pipelineJob to set.
        Returns:
        This builder for chaining.

      • 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 present for AutoML Models or Large 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 present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
        Specified by:
        getContainerSpec in interface ModelOrBuilder
        Returns:
        The containerSpec.

      • setContainerSpec

        public Model.Builder setContainerSpec​(ModelContainerSpec value)
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

      • setContainerSpec

        public Model.Builder setContainerSpec​(ModelContainerSpec.Builder builderForValue)
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

      • mergeContainerSpec

        public Model.Builder mergeContainerSpec​(ModelContainerSpec value)
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

      • clearContainerSpec

        public Model.Builder clearContainerSpec()
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

      • getContainerSpecBuilder

        public ModelContainerSpec.Builder getContainerSpecBuilder()
         Input only. The specification of the container that is to be used when
 deploying this Model. The specification is ingested upon
 [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
 and all binaries it contains are copied and stored internally by Vertex AI.
 Not present for AutoML Models or Large Models.
        .google.cloud.aiplatform.v1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];

      • 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 present for AutoML Models or Large 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 present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Specified by:
        getArtifactUri in interface ModelOrBuilder
        Returns:
        The artifactUri.

      • getArtifactUriBytes

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

      • setArtifactUri

        public Model.Builder setArtifactUri​(String value)
         Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Parameters:
        value - The artifactUri to set.
        Returns:
        This builder for chaining.

      • clearArtifactUri

        public Model.Builder clearArtifactUri()
         Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Returns:
        This builder for chaining.

      • setArtifactUriBytes

        public Model.Builder setArtifactUriBytes​(com.google.protobuf.ByteString value)
         Immutable. The path to the directory containing the Model artifact and any
 of its supporting files. Not present for AutoML Models or Large Models.
        string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];
        Parameters:
        value - The bytes for artifactUri to set.
        Returns:
        This builder for chaining.

      • 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.

      • setSupportedDeploymentResourcesTypes

        public Model.Builder setSupportedDeploymentResourcesTypes​(int index,
                                                          Model.DeploymentResourcesType value)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        index - The index to set the value at.
        value - The supportedDeploymentResourcesTypes to set.
        Returns:
        This builder for chaining.

      • addSupportedDeploymentResourcesTypes

        public Model.Builder addSupportedDeploymentResourcesTypes​(Model.DeploymentResourcesType value)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        value - The supportedDeploymentResourcesTypes to add.
        Returns:
        This builder for chaining.

      • addAllSupportedDeploymentResourcesTypes

        public Model.Builder addAllSupportedDeploymentResourcesTypes​(Iterable<? extends Model.DeploymentResourcesType> values)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        values - The supportedDeploymentResourcesTypes to add.
        Returns:
        This builder for chaining.

      • clearSupportedDeploymentResourcesTypes

        public Model.Builder clearSupportedDeploymentResourcesTypes()
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Returns:
        This builder for chaining.

      • 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.

      • setSupportedDeploymentResourcesTypesValue

        public Model.Builder setSupportedDeploymentResourcesTypesValue​(int index,
                                                               int value)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        index - The index to set the value at.
        value - The enum numeric value on the wire for supportedDeploymentResourcesTypes to set.
        Returns:
        This builder for chaining.

      • addSupportedDeploymentResourcesTypesValue

        public Model.Builder addSupportedDeploymentResourcesTypesValue​(int value)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        value - The enum numeric value on the wire for supportedDeploymentResourcesTypes to add.
        Returns:
        This builder for chaining.

      • addAllSupportedDeploymentResourcesTypesValue

        public Model.Builder addAllSupportedDeploymentResourcesTypesValue​(Iterable<Integer> values)
         Output only. When this Model is deployed, its prediction resources are
 described by the `prediction_resources` field of the
 [Endpoint.deployed_models][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];
        Parameters:
        values - The enum numeric values on the wire for supportedDeploymentResourcesTypes to add.
        Returns:
        This builder for chaining.

      • 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.

      • setSupportedInputStorageFormats

        public Model.Builder setSupportedInputStorageFormats​(int index,
                                                     String value)
         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];
        Parameters:
        index - The index to set the value at.
        value - The supportedInputStorageFormats to set.
        Returns:
        This builder for chaining.

      • addSupportedInputStorageFormats

        public Model.Builder addSupportedInputStorageFormats​(String value)
         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];
        Parameters:
        value - The supportedInputStorageFormats to add.
        Returns:
        This builder for chaining.

      • addAllSupportedInputStorageFormats

        public Model.Builder addAllSupportedInputStorageFormats​(Iterable<String> values)
         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];
        Parameters:
        values - The supportedInputStorageFormats to add.
        Returns:
        This builder for chaining.

      • clearSupportedInputStorageFormats

        public Model.Builder clearSupportedInputStorageFormats()
         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];
        Returns:
        This builder for chaining.

      • addSupportedInputStorageFormatsBytes

        public Model.Builder addSupportedInputStorageFormatsBytes​(com.google.protobuf.ByteString value)
         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];
        Parameters:
        value - The bytes of the supportedInputStorageFormats to add.
        Returns:
        This builder for chaining.

      • 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.

      • setSupportedOutputStorageFormats

        public Model.Builder setSupportedOutputStorageFormats​(int index,
                                                      String value)
         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];
        Parameters:
        index - The index to set the value at.
        value - The supportedOutputStorageFormats to set.
        Returns:
        This builder for chaining.

      • addSupportedOutputStorageFormats

        public Model.Builder addSupportedOutputStorageFormats​(String value)
         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];
        Parameters:
        value - The supportedOutputStorageFormats to add.
        Returns:
        This builder for chaining.

      • addAllSupportedOutputStorageFormats

        public Model.Builder addAllSupportedOutputStorageFormats​(Iterable<String> values)
         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];
        Parameters:
        values - The supportedOutputStorageFormats to add.
        Returns:
        This builder for chaining.

      • clearSupportedOutputStorageFormats

        public Model.Builder clearSupportedOutputStorageFormats()
         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];
        Returns:
        This builder for chaining.

      • addSupportedOutputStorageFormatsBytes

        public Model.Builder addSupportedOutputStorageFormatsBytes​(com.google.protobuf.ByteString value)
         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];
        Parameters:
        value - The bytes of the supportedOutputStorageFormats to add.
        Returns:
        This builder for chaining.

      • 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.

      • setCreateTime

        public Model.Builder setCreateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setCreateTime

        public Model.Builder setCreateTime​(com.google.protobuf.Timestamp.Builder builderForValue)
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeCreateTime

        public Model.Builder mergeCreateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearCreateTime

        public Model.Builder clearCreateTime()
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getCreateTimeBuilder

        public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()
         Output only. Timestamp when this Model was uploaded into Vertex AI.
        .google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • 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.

      • setUpdateTime

        public Model.Builder setUpdateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setUpdateTime

        public Model.Builder setUpdateTime​(com.google.protobuf.Timestamp.Builder builderForValue)
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeUpdateTime

        public Model.Builder mergeUpdateTime​(com.google.protobuf.Timestamp value)
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearUpdateTime

        public Model.Builder clearUpdateTime()
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getUpdateTimeBuilder

        public com.google.protobuf.Timestamp.Builder getUpdateTimeBuilder()
         Output only. Timestamp when this Model was most recently updated.
        .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • 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

      • 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

      • setDeployedModels

        public Model.Builder setDeployedModels​(int index,
                                       DeployedModelRef value)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setDeployedModels

        public Model.Builder setDeployedModels​(int index,
                                       DeployedModelRef.Builder builderForValue)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addDeployedModels

        public Model.Builder addDeployedModels​(DeployedModelRef value)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addDeployedModels

        public Model.Builder addDeployedModels​(int index,
                                       DeployedModelRef value)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addDeployedModels

        public Model.Builder addDeployedModels​(DeployedModelRef.Builder builderForValue)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addDeployedModels

        public Model.Builder addDeployedModels​(int index,
                                       DeployedModelRef.Builder builderForValue)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • addAllDeployedModels

        public Model.Builder addAllDeployedModels​(Iterable<? extends DeployedModelRef> values)
         Output only. The pointers to DeployedModels created from this Model. Note
 that Model could have been deployed to Endpoints in different Locations.
        repeated .google.cloud.aiplatform.v1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearDeployedModels

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

      • removeDeployedModels

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

      • getDeployedModelsBuilder

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

      • 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

      • 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

      • addDeployedModelsBuilder

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

      • addDeployedModelsBuilder

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

      • getDeployedModelsBuilderList

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

      • 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.

      • setExplanationSpec

        public Model.Builder setExplanationSpec​(ExplanationSpec value)
         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;

      • setExplanationSpec

        public Model.Builder setExplanationSpec​(ExplanationSpec.Builder builderForValue)
         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;

      • mergeExplanationSpec

        public Model.Builder mergeExplanationSpec​(ExplanationSpec value)
         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;

      • clearExplanationSpec

        public Model.Builder clearExplanationSpec()
         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;

      • getExplanationSpecBuilder

        public ExplanationSpec.Builder getExplanationSpecBuilder()
         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;

      • 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.

      • setEtag

        public Model.Builder setEtag​(String value)
         Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
        string etag = 16;
        Parameters:
        value - The etag to set.
        Returns:
        This builder for chaining.

      • clearEtag

        public Model.Builder clearEtag()
         Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
        string etag = 16;
        Returns:
        This builder for chaining.

      • setEtagBytes

        public Model.Builder setEtagBytes​(com.google.protobuf.ByteString value)
         Used to perform consistent read-modify-write updates. If not set, a blind
 "overwrite" update happens.
        string etag = 16;
        Parameters:
        value - The bytes for etag to set.
        Returns:
        This builder for chaining.

      • getLabelsCount

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

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

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

      • containsLabels

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

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

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

      • getLabelsMap

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

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

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

      • getLabelsOrDefault

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

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

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

      • getLabelsOrThrow

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

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

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

      • removeLabels

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

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

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;

      • getMutableLabels

        @Deprecated
public Map<String,​String> getMutableLabels()
        Deprecated.
        Use alternate mutation accessors instead.

      • putLabels

        public Model.Builder putLabels​(String key,
                               String value)
         The labels with user-defined metadata to organize your Models.

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

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;

      • putAllLabels

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

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

 See https://goo.gl/xmQnxf for more information and examples of labels.
        map<string, string> labels = 17;

      • 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.

      • setEncryptionSpec

        public Model.Builder setEncryptionSpec​(EncryptionSpec value)
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;

      • setEncryptionSpec

        public Model.Builder setEncryptionSpec​(EncryptionSpec.Builder builderForValue)
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;

      • mergeEncryptionSpec

        public Model.Builder mergeEncryptionSpec​(EncryptionSpec value)
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;

      • clearEncryptionSpec

        public Model.Builder clearEncryptionSpec()
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;

      • getEncryptionSpecBuilder

        public EncryptionSpec.Builder getEncryptionSpecBuilder()
         Customer-managed encryption key spec for a Model. If set, this
 Model and all sub-resources of this Model will be secured by this key.
        .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 24;

      • 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 existing Vertex AI Model.
        .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 existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Specified by:
        getModelSourceInfo in interface ModelOrBuilder
        Returns:
        The modelSourceInfo.

      • setModelSourceInfo

        public Model.Builder setModelSourceInfo​(ModelSourceInfo value)
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setModelSourceInfo

        public Model.Builder setModelSourceInfo​(ModelSourceInfo.Builder builderForValue)
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeModelSourceInfo

        public Model.Builder mergeModelSourceInfo​(ModelSourceInfo value)
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearModelSourceInfo

        public Model.Builder clearModelSourceInfo()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getModelSourceInfoBuilder

        public ModelSourceInfo.Builder getModelSourceInfoBuilder()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.v1.ModelSourceInfo model_source_info = 38 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getModelSourceInfoOrBuilder

        public ModelSourceInfoOrBuilder getModelSourceInfoOrBuilder()
         Output only. Source of a model. It can either be automl training pipeline,
 custom training pipeline, BigQuery ML, or existing Vertex AI Model.
        .google.cloud.aiplatform.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.

      • setOriginalModelInfo

        public Model.Builder setOriginalModelInfo​(Model.OriginalModelInfo value)
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • setOriginalModelInfo

        public Model.Builder setOriginalModelInfo​(Model.OriginalModelInfo.Builder builderForValue)
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • mergeOriginalModelInfo

        public Model.Builder mergeOriginalModelInfo​(Model.OriginalModelInfo value)
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • clearOriginalModelInfo

        public Model.Builder clearOriginalModelInfo()
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • getOriginalModelInfoBuilder

        public Model.OriginalModelInfo.Builder getOriginalModelInfoBuilder()
         Output only. If this Model is a copy of another Model, this contains info
 about the original.
        .google.cloud.aiplatform.v1.Model.OriginalModelInfo original_model_info = 34 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • 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.

      • setMetadataArtifact

        public Model.Builder setMetadataArtifact​(String value)
         Output only. The resource name of the Artifact that was created in
 MetadataStore when creating the Model. The Artifact resource name pattern
 is
 `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
        string metadata_artifact = 44 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Parameters:
        value - The metadataArtifact to set.
        Returns:
        This builder for chaining.

      • clearMetadataArtifact

        public Model.Builder clearMetadataArtifact()
         Output only. The resource name of the Artifact that was created in
 MetadataStore when creating the Model. The Artifact resource name pattern
 is
 `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
        string metadata_artifact = 44 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        This builder for chaining.

      • setMetadataArtifactBytes

        public Model.Builder setMetadataArtifactBytes​(com.google.protobuf.ByteString value)
         Output only. The resource name of the Artifact that was created in
 MetadataStore when creating the Model. The Artifact resource name pattern
 is
 `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
        string metadata_artifact = 44 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Parameters:
        value - The bytes for metadataArtifact to set.
        Returns:
        This builder for chaining.

      • setUnknownFields

        public final Model.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>

      • mergeUnknownFields

        public final Model.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>