Package viam.app.v1

Class AppOuterClass.MLTrainingMetadata.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder<AppOuterClass.MLTrainingMetadata,AppOuterClass.MLTrainingMetadata.Builder>
com.google.protobuf.GeneratedMessageLite.Builder<AppOuterClass.MLTrainingMetadata,AppOuterClass.MLTrainingMetadata.Builder>
viam.app.v1.AppOuterClass.MLTrainingMetadata.Builder
All Implemented Interfaces:
com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, Cloneable, AppOuterClass.MLTrainingMetadataOrBuilder
Enclosing class:
AppOuterClass.MLTrainingMetadata
public static final class AppOuterClass.MLTrainingMetadata.Builder extends com.google.protobuf.GeneratedMessageLite.Builder<AppOuterClass.MLTrainingMetadata,AppOuterClass.MLTrainingMetadata.Builder> implements AppOuterClass.MLTrainingMetadataOrBuilder
Protobuf type viam.app.v1.MLTrainingMetadata

  • Method Details

    • getVersionsList

      public List<AppOuterClass.MLTrainingVersion> getVersionsList()
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];
      Specified by:
      getVersionsList in interface AppOuterClass.MLTrainingMetadataOrBuilder

    • getVersionsCount

      public int getVersionsCount()
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];
      Specified by:
      getVersionsCount in interface AppOuterClass.MLTrainingMetadataOrBuilder

    • getVersions

      public AppOuterClass.MLTrainingVersion getVersions(int index)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];
      Specified by:
      getVersions in interface AppOuterClass.MLTrainingMetadataOrBuilder

    • setVersions

      public AppOuterClass.MLTrainingMetadata.Builder setVersions(int index, AppOuterClass.MLTrainingVersion value)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • setVersions

      public AppOuterClass.MLTrainingMetadata.Builder setVersions(int index, AppOuterClass.MLTrainingVersion.Builder builderForValue)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • addVersions

      public AppOuterClass.MLTrainingMetadata.Builder addVersions(AppOuterClass.MLTrainingVersion value)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • addVersions

      public AppOuterClass.MLTrainingMetadata.Builder addVersions(int index, AppOuterClass.MLTrainingVersion value)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • addVersions

      public AppOuterClass.MLTrainingMetadata.Builder addVersions(AppOuterClass.MLTrainingVersion.Builder builderForValue)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • addVersions

      public AppOuterClass.MLTrainingMetadata.Builder addVersions(int index, AppOuterClass.MLTrainingVersion.Builder builderForValue)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • addAllVersions

      public AppOuterClass.MLTrainingMetadata.Builder addAllVersions(Iterable<? extends AppOuterClass.MLTrainingVersion> values)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • clearVersions

      public AppOuterClass.MLTrainingMetadata.Builder clearVersions()
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • removeVersions

      public AppOuterClass.MLTrainingMetadata.Builder removeVersions(int index)
       A list of package versions for ML training source distribution
      repeated .viam.app.v1.MLTrainingVersion versions = 5 [json_name = "versions"];

    • getModelTypeValue

      public int getModelTypeValue()
      .viam.app.mltraining.v1.ModelType model_type = 2 [json_name = "modelType"];
      Specified by:
      getModelTypeValue in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The enum numeric value on the wire for modelType.

    • setModelTypeValue

      public AppOuterClass.MLTrainingMetadata.Builder setModelTypeValue(int value)
      .viam.app.mltraining.v1.ModelType model_type = 2 [json_name = "modelType"];
      Parameters:
      value - The modelType to set.
      Returns:
      This builder for chaining.

    • getModelType

      public MlTraining.ModelType getModelType()
      .viam.app.mltraining.v1.ModelType model_type = 2 [json_name = "modelType"];
      Specified by:
      getModelType in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The modelType.

    • setModelType

      public AppOuterClass.MLTrainingMetadata.Builder setModelType(MlTraining.ModelType value)
      .viam.app.mltraining.v1.ModelType model_type = 2 [json_name = "modelType"];
      Parameters:
      value - The enum numeric value on the wire for modelType to set.
      Returns:
      This builder for chaining.
      Throws:
      IllegalArgumentException - if UNRECOGNIZED is provided.

    • clearModelType

      public AppOuterClass.MLTrainingMetadata.Builder clearModelType()
      .viam.app.mltraining.v1.ModelType model_type = 2 [json_name = "modelType"];
      Returns:
      This builder for chaining.

    • getModelFrameworkValue

      public int getModelFrameworkValue()
      .viam.app.mltraining.v1.ModelFramework model_framework = 3 [json_name = "modelFramework"];
      Specified by:
      getModelFrameworkValue in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The enum numeric value on the wire for modelFramework.

    • setModelFrameworkValue

      public AppOuterClass.MLTrainingMetadata.Builder setModelFrameworkValue(int value)
      .viam.app.mltraining.v1.ModelFramework model_framework = 3 [json_name = "modelFramework"];
      Parameters:
      value - The modelFramework to set.
      Returns:
      This builder for chaining.

    • getModelFramework

      public MlTraining.ModelFramework getModelFramework()
      .viam.app.mltraining.v1.ModelFramework model_framework = 3 [json_name = "modelFramework"];
      Specified by:
      getModelFramework in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The modelFramework.

    • setModelFramework

      public AppOuterClass.MLTrainingMetadata.Builder setModelFramework(MlTraining.ModelFramework value)
      .viam.app.mltraining.v1.ModelFramework model_framework = 3 [json_name = "modelFramework"];
      Parameters:
      value - The enum numeric value on the wire for modelFramework to set.
      Returns:
      This builder for chaining.
      Throws:
      IllegalArgumentException - if UNRECOGNIZED is provided.

    • clearModelFramework

      public AppOuterClass.MLTrainingMetadata.Builder clearModelFramework()
      .viam.app.mltraining.v1.ModelFramework model_framework = 3 [json_name = "modelFramework"];
      Returns:
      This builder for chaining.

    • getDraft

      public boolean getDraft()
      bool draft = 4 [json_name = "draft"];
      Specified by:
      getDraft in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The draft.

    • setDraft

      public AppOuterClass.MLTrainingMetadata.Builder setDraft(boolean value)
      bool draft = 4 [json_name = "draft"];
      Parameters:
      value - The draft to set.
      Returns:
      This builder for chaining.

    • clearDraft

      public AppOuterClass.MLTrainingMetadata.Builder clearDraft()
      bool draft = 4 [json_name = "draft"];
      Returns:
      This builder for chaining.

    • getDeploymentModularResourcesList

      public List<String> getDeploymentModularResourcesList()
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Specified by:
      getDeploymentModularResourcesList in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      A list containing the deploymentModularResources.

    • getDeploymentModularResourcesCount

      public int getDeploymentModularResourcesCount()
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Specified by:
      getDeploymentModularResourcesCount in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Returns:
      The count of deploymentModularResources.

    • getDeploymentModularResources

      public String getDeploymentModularResources(int index)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Specified by:
      getDeploymentModularResources in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The deploymentModularResources at the given index.

    • getDeploymentModularResourcesBytes

      public com.google.protobuf.ByteString getDeploymentModularResourcesBytes(int index)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Specified by:
      getDeploymentModularResourcesBytes in interface AppOuterClass.MLTrainingMetadataOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the deploymentModularResources at the given index.

    • setDeploymentModularResources

      public AppOuterClass.MLTrainingMetadata.Builder setDeploymentModularResources(int index, String value)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Parameters:
      index - The index to set the value at.
      value - The deploymentModularResources to set.
      Returns:
      This builder for chaining.

    • addDeploymentModularResources

      public AppOuterClass.MLTrainingMetadata.Builder addDeploymentModularResources(String value)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Parameters:
      value - The deploymentModularResources to add.
      Returns:
      This builder for chaining.

    • addAllDeploymentModularResources

      public AppOuterClass.MLTrainingMetadata.Builder addAllDeploymentModularResources(Iterable<String> values)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Parameters:
      values - The deploymentModularResources to add.
      Returns:
      This builder for chaining.

    • clearDeploymentModularResources

      public AppOuterClass.MLTrainingMetadata.Builder clearDeploymentModularResources()
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Returns:
      This builder for chaining.

    • addDeploymentModularResourcesBytes

      public AppOuterClass.MLTrainingMetadata.Builder addDeploymentModularResourcesBytes(com.google.protobuf.ByteString value)
       Colon-delimited triplets of components or services from the registry used when
 model_framework is MODEL_FRAMEWORK_REGISTRY. This ties the ML model file to the
 associated component or service that consumes the files and should be deployed
 along with the model.
 Copied onto packages published by this training script.
      repeated string deployment_modular_resources = 6 [json_name = "deploymentModularResources"];
      Parameters:
      value - The bytes of the deploymentModularResources to add.
      Returns:
      This builder for chaining.