Class TrainingPipeline.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
com.google.cloud.aiplatform.v1.TrainingPipeline.Builder
All Implemented Interfaces:
TrainingPipelineOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
TrainingPipeline

public static final class TrainingPipeline.Builder extends com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder> implements TrainingPipelineOrBuilder
 The TrainingPipeline orchestrates tasks associated with training a Model. It
 always executes the training task, and optionally may also
 export data from Vertex AI's Dataset which becomes the training input,
 [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to
 Vertex AI, and evaluate the Model.
 
Protobuf type google.cloud.aiplatform.v1.TrainingPipeline
  • Method Details

    • getDescriptor

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

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
      Overrides:
      internalGetMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
    • internalGetMutableMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
      Overrides:
      internalGetMutableMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
    • clear

      public TrainingPipeline.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.GeneratedMessage.Builder<TrainingPipeline.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.GeneratedMessage.Builder<TrainingPipeline.Builder>
    • getDefaultInstanceForType

      public TrainingPipeline getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder
    • build

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

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

      public TrainingPipeline.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<TrainingPipeline.Builder>
    • mergeFrom

      public TrainingPipeline.Builder mergeFrom(TrainingPipeline other)
    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
    • mergeFrom

      public TrainingPipeline.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<TrainingPipeline.Builder>
      Throws:
      IOException
    • getName

      public String getName()
       Output only. Resource name of the TrainingPipeline.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getName in interface TrainingPipelineOrBuilder
      Returns:
      The name.
    • getNameBytes

      public com.google.protobuf.ByteString getNameBytes()
       Output only. Resource name of the TrainingPipeline.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNameBytes in interface TrainingPipelineOrBuilder
      Returns:
      The bytes for name.
    • setName

      public TrainingPipeline.Builder setName(String value)
       Output only. Resource name of the TrainingPipeline.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The name to set.
      Returns:
      This builder for chaining.
    • clearName

      public TrainingPipeline.Builder clearName()
       Output only. Resource name of the TrainingPipeline.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • setNameBytes

      public TrainingPipeline.Builder setNameBytes(com.google.protobuf.ByteString value)
       Output only. Resource name of the TrainingPipeline.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The bytes for name to set.
      Returns:
      This builder for chaining.
    • getDisplayName

      public String getDisplayName()
       Required. The user-defined name of this TrainingPipeline.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getDisplayName in interface TrainingPipelineOrBuilder
      Returns:
      The displayName.
    • getDisplayNameBytes

      public com.google.protobuf.ByteString getDisplayNameBytes()
       Required. The user-defined name of this TrainingPipeline.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getDisplayNameBytes in interface TrainingPipelineOrBuilder
      Returns:
      The bytes for displayName.
    • setDisplayName

      public TrainingPipeline.Builder setDisplayName(String value)
       Required. The user-defined name of this TrainingPipeline.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The displayName to set.
      Returns:
      This builder for chaining.
    • clearDisplayName

      public TrainingPipeline.Builder clearDisplayName()
       Required. The user-defined name of this TrainingPipeline.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      This builder for chaining.
    • setDisplayNameBytes

      public TrainingPipeline.Builder setDisplayNameBytes(com.google.protobuf.ByteString value)
       Required. The user-defined name of this TrainingPipeline.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The bytes for displayName to set.
      Returns:
      This builder for chaining.
    • hasInputDataConfig

      public boolean hasInputDataConfig()
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
      Specified by:
      hasInputDataConfig in interface TrainingPipelineOrBuilder
      Returns:
      Whether the inputDataConfig field is set.
    • getInputDataConfig

      public InputDataConfig getInputDataConfig()
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
      Specified by:
      getInputDataConfig in interface TrainingPipelineOrBuilder
      Returns:
      The inputDataConfig.
    • setInputDataConfig

      public TrainingPipeline.Builder setInputDataConfig(InputDataConfig value)
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
    • setInputDataConfig

      public TrainingPipeline.Builder setInputDataConfig(InputDataConfig.Builder builderForValue)
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
    • mergeInputDataConfig

      public TrainingPipeline.Builder mergeInputDataConfig(InputDataConfig value)
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
    • clearInputDataConfig

      public TrainingPipeline.Builder clearInputDataConfig()
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
    • getInputDataConfigBuilder

      public InputDataConfig.Builder getInputDataConfigBuilder()
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
    • getInputDataConfigOrBuilder

      public InputDataConfigOrBuilder getInputDataConfigOrBuilder()
       Specifies Vertex AI owned input data that may be used for training the
       Model. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this config is used and if there are any special
       requirements on how it should be filled. If nothing about this config is
       mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that the TrainingPipeline does not depend on this
       configuration.
       
      .google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
      Specified by:
      getInputDataConfigOrBuilder in interface TrainingPipelineOrBuilder
    • getTrainingTaskDefinition

      public String getTrainingTaskDefinition()
       Required. A Google Cloud Storage path to the YAML file that defines the
       training task which is responsible for producing the model artifact, and
       may also include additional auxiliary work. The definition files that can
       be used here are found in
       gs://google-cloud-aiplatform/schema/trainingjob/definition/.
       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 training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getTrainingTaskDefinition in interface TrainingPipelineOrBuilder
      Returns:
      The trainingTaskDefinition.
    • getTrainingTaskDefinitionBytes

      public com.google.protobuf.ByteString getTrainingTaskDefinitionBytes()
       Required. A Google Cloud Storage path to the YAML file that defines the
       training task which is responsible for producing the model artifact, and
       may also include additional auxiliary work. The definition files that can
       be used here are found in
       gs://google-cloud-aiplatform/schema/trainingjob/definition/.
       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 training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getTrainingTaskDefinitionBytes in interface TrainingPipelineOrBuilder
      Returns:
      The bytes for trainingTaskDefinition.
    • setTrainingTaskDefinition

      public TrainingPipeline.Builder setTrainingTaskDefinition(String value)
       Required. A Google Cloud Storage path to the YAML file that defines the
       training task which is responsible for producing the model artifact, and
       may also include additional auxiliary work. The definition files that can
       be used here are found in
       gs://google-cloud-aiplatform/schema/trainingjob/definition/.
       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 training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The trainingTaskDefinition to set.
      Returns:
      This builder for chaining.
    • clearTrainingTaskDefinition

      public TrainingPipeline.Builder clearTrainingTaskDefinition()
       Required. A Google Cloud Storage path to the YAML file that defines the
       training task which is responsible for producing the model artifact, and
       may also include additional auxiliary work. The definition files that can
       be used here are found in
       gs://google-cloud-aiplatform/schema/trainingjob/definition/.
       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 training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      This builder for chaining.
    • setTrainingTaskDefinitionBytes

      public TrainingPipeline.Builder setTrainingTaskDefinitionBytes(com.google.protobuf.ByteString value)
       Required. A Google Cloud Storage path to the YAML file that defines the
       training task which is responsible for producing the model artifact, and
       may also include additional auxiliary work. The definition files that can
       be used here are found in
       gs://google-cloud-aiplatform/schema/trainingjob/definition/.
       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 training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The bytes for trainingTaskDefinition to set.
      Returns:
      This builder for chaining.
    • hasTrainingTaskInputs

      public boolean hasTrainingTaskInputs()
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      hasTrainingTaskInputs in interface TrainingPipelineOrBuilder
      Returns:
      Whether the trainingTaskInputs field is set.
    • getTrainingTaskInputs

      public com.google.protobuf.Value getTrainingTaskInputs()
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getTrainingTaskInputs in interface TrainingPipelineOrBuilder
      Returns:
      The trainingTaskInputs.
    • setTrainingTaskInputs

      public TrainingPipeline.Builder setTrainingTaskInputs(com.google.protobuf.Value value)
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
    • setTrainingTaskInputs

      public TrainingPipeline.Builder setTrainingTaskInputs(com.google.protobuf.Value.Builder builderForValue)
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
    • mergeTrainingTaskInputs

      public TrainingPipeline.Builder mergeTrainingTaskInputs(com.google.protobuf.Value value)
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
    • clearTrainingTaskInputs

      public TrainingPipeline.Builder clearTrainingTaskInputs()
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
    • getTrainingTaskInputsBuilder

      public com.google.protobuf.Value.Builder getTrainingTaskInputsBuilder()
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
    • getTrainingTaskInputsOrBuilder

      public com.google.protobuf.ValueOrBuilder getTrainingTaskInputsOrBuilder()
       Required. The training task's parameter(s), as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `inputs`.
       
      .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getTrainingTaskInputsOrBuilder in interface TrainingPipelineOrBuilder
    • hasTrainingTaskMetadata

      public boolean hasTrainingTaskMetadata()
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasTrainingTaskMetadata in interface TrainingPipelineOrBuilder
      Returns:
      Whether the trainingTaskMetadata field is set.
    • getTrainingTaskMetadata

      public com.google.protobuf.Value getTrainingTaskMetadata()
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getTrainingTaskMetadata in interface TrainingPipelineOrBuilder
      Returns:
      The trainingTaskMetadata.
    • setTrainingTaskMetadata

      public TrainingPipeline.Builder setTrainingTaskMetadata(com.google.protobuf.Value value)
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setTrainingTaskMetadata

      public TrainingPipeline.Builder setTrainingTaskMetadata(com.google.protobuf.Value.Builder builderForValue)
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeTrainingTaskMetadata

      public TrainingPipeline.Builder mergeTrainingTaskMetadata(com.google.protobuf.Value value)
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearTrainingTaskMetadata

      public TrainingPipeline.Builder clearTrainingTaskMetadata()
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getTrainingTaskMetadataBuilder

      public com.google.protobuf.Value.Builder getTrainingTaskMetadataBuilder()
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getTrainingTaskMetadataOrBuilder

      public com.google.protobuf.ValueOrBuilder getTrainingTaskMetadataOrBuilder()
       Output only. The metadata information as specified in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s
       `metadata`. This metadata is an auxiliary runtime and final information
       about the training task. While the pipeline is running this information is
       populated only at a best effort basis. Only present if the
       pipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       contains `metadata` object.
       
      .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getTrainingTaskMetadataOrBuilder in interface TrainingPipelineOrBuilder
    • hasModelToUpload

      public boolean hasModelToUpload()
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
      Specified by:
      hasModelToUpload in interface TrainingPipelineOrBuilder
      Returns:
      Whether the modelToUpload field is set.
    • getModelToUpload

      public Model getModelToUpload()
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
      Specified by:
      getModelToUpload in interface TrainingPipelineOrBuilder
      Returns:
      The modelToUpload.
    • setModelToUpload

      public TrainingPipeline.Builder setModelToUpload(Model value)
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
    • setModelToUpload

      public TrainingPipeline.Builder setModelToUpload(Model.Builder builderForValue)
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
    • mergeModelToUpload

      public TrainingPipeline.Builder mergeModelToUpload(Model value)
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
    • clearModelToUpload

      public TrainingPipeline.Builder clearModelToUpload()
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
    • getModelToUploadBuilder

      public Model.Builder getModelToUploadBuilder()
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
    • getModelToUploadOrBuilder

      public ModelOrBuilder getModelToUploadOrBuilder()
       Describes the Model that may be uploaded (via
       [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel])
       by this TrainingPipeline. The TrainingPipeline's
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]
       should make clear whether this Model description should be populated, and
       if there are any special requirements regarding how it should be filled. If
       nothing is mentioned in the
       [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition],
       then it should be assumed that this field should not be filled and the
       training task either uploads the Model without a need of this information,
       or that training task does not support uploading a Model as part of the
       pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
       the trained Model had been uploaded into Vertex AI, then the
       model_to_upload's resource [name][google.cloud.aiplatform.v1.Model.name] is
       populated. The Model is always uploaded into the Project and Location in
       which this pipeline is.
       
      .google.cloud.aiplatform.v1.Model model_to_upload = 7;
      Specified by:
      getModelToUploadOrBuilder in interface TrainingPipelineOrBuilder
    • getModelId

      public String getModelId()
       Optional. The ID to use for the uploaded Model, which will become the final
       component of the model resource name.
      
       This value may be up to 63 characters, and valid characters are
       `[a-z0-9_-]`. The first character cannot be a number or hyphen.
       
      string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getModelId in interface TrainingPipelineOrBuilder
      Returns:
      The modelId.
    • getModelIdBytes

      public com.google.protobuf.ByteString getModelIdBytes()
       Optional. The ID to use for the uploaded Model, which will become the final
       component of the model resource name.
      
       This value may be up to 63 characters, and valid characters are
       `[a-z0-9_-]`. The first character cannot be a number or hyphen.
       
      string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getModelIdBytes in interface TrainingPipelineOrBuilder
      Returns:
      The bytes for modelId.
    • setModelId

      public TrainingPipeline.Builder setModelId(String value)
       Optional. The ID to use for the uploaded Model, which will become the final
       component of the model resource name.
      
       This value may be up to 63 characters, and valid characters are
       `[a-z0-9_-]`. The first character cannot be a number or hyphen.
       
      string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The modelId to set.
      Returns:
      This builder for chaining.
    • clearModelId

      public TrainingPipeline.Builder clearModelId()
       Optional. The ID to use for the uploaded Model, which will become the final
       component of the model resource name.
      
       This value may be up to 63 characters, and valid characters are
       `[a-z0-9_-]`. The first character cannot be a number or hyphen.
       
      string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      This builder for chaining.
    • setModelIdBytes

      public TrainingPipeline.Builder setModelIdBytes(com.google.protobuf.ByteString value)
       Optional. The ID to use for the uploaded Model, which will become the final
       component of the model resource name.
      
       This value may be up to 63 characters, and valid characters are
       `[a-z0-9_-]`. The first character cannot be a number or hyphen.
       
      string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The bytes for modelId to set.
      Returns:
      This builder for chaining.
    • getParentModel

      public String getParentModel()
       Optional. When specify this field, the `model_to_upload` will not be
       uploaded as a new model, instead, it will become a new version of this
       `parent_model`.
       
      string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getParentModel in interface TrainingPipelineOrBuilder
      Returns:
      The parentModel.
    • getParentModelBytes

      public com.google.protobuf.ByteString getParentModelBytes()
       Optional. When specify this field, the `model_to_upload` will not be
       uploaded as a new model, instead, it will become a new version of this
       `parent_model`.
       
      string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getParentModelBytes in interface TrainingPipelineOrBuilder
      Returns:
      The bytes for parentModel.
    • setParentModel

      public TrainingPipeline.Builder setParentModel(String value)
       Optional. When specify this field, the `model_to_upload` will not be
       uploaded as a new model, instead, it will become a new version of this
       `parent_model`.
       
      string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The parentModel to set.
      Returns:
      This builder for chaining.
    • clearParentModel

      public TrainingPipeline.Builder clearParentModel()
       Optional. When specify this field, the `model_to_upload` will not be
       uploaded as a new model, instead, it will become a new version of this
       `parent_model`.
       
      string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      This builder for chaining.
    • setParentModelBytes

      public TrainingPipeline.Builder setParentModelBytes(com.google.protobuf.ByteString value)
       Optional. When specify this field, the `model_to_upload` will not be
       uploaded as a new model, instead, it will become a new version of this
       `parent_model`.
       
      string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
      Parameters:
      value - The bytes for parentModel to set.
      Returns:
      This builder for chaining.
    • getStateValue

      public int getStateValue()
       Output only. The detailed state of the pipeline.
       
      .google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getStateValue in interface TrainingPipelineOrBuilder
      Returns:
      The enum numeric value on the wire for state.
    • setStateValue

      public TrainingPipeline.Builder setStateValue(int value)
       Output only. The detailed state of the pipeline.
       
      .google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The enum numeric value on the wire for state to set.
      Returns:
      This builder for chaining.
    • getState

      public PipelineState getState()
       Output only. The detailed state of the pipeline.
       
      .google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getState in interface TrainingPipelineOrBuilder
      Returns:
      The state.
    • setState

      public TrainingPipeline.Builder setState(PipelineState value)
       Output only. The detailed state of the pipeline.
       
      .google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The state to set.
      Returns:
      This builder for chaining.
    • clearState

      public TrainingPipeline.Builder clearState()
       Output only. The detailed state of the pipeline.
       
      .google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • hasError

      public boolean hasError()
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasError in interface TrainingPipelineOrBuilder
      Returns:
      Whether the error field is set.
    • getError

      public Status getError()
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getError in interface TrainingPipelineOrBuilder
      Returns:
      The error.
    • setError

      public TrainingPipeline.Builder setError(Status value)
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setError

      public TrainingPipeline.Builder setError(Status.Builder builderForValue)
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeError

      public TrainingPipeline.Builder mergeError(Status value)
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearError

      public TrainingPipeline.Builder clearError()
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getErrorBuilder

      public Status.Builder getErrorBuilder()
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getErrorOrBuilder

      public StatusOrBuilder getErrorOrBuilder()
       Output only. Only populated when the pipeline's state is
       `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
       
      .google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getErrorOrBuilder in interface TrainingPipelineOrBuilder
    • hasCreateTime

      public boolean hasCreateTime()
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasCreateTime in interface TrainingPipelineOrBuilder
      Returns:
      Whether the createTime field is set.
    • getCreateTime

      public com.google.protobuf.Timestamp getCreateTime()
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTime in interface TrainingPipelineOrBuilder
      Returns:
      The createTime.
    • setCreateTime

      public TrainingPipeline.Builder setCreateTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setCreateTime

      public TrainingPipeline.Builder setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeCreateTime

      public TrainingPipeline.Builder mergeCreateTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearCreateTime

      public TrainingPipeline.Builder clearCreateTime()
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getCreateTimeBuilder

      public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getCreateTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
       Output only. Time when the TrainingPipeline was created.
       
      .google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTimeOrBuilder in interface TrainingPipelineOrBuilder
    • hasStartTime

      public boolean hasStartTime()
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasStartTime in interface TrainingPipelineOrBuilder
      Returns:
      Whether the startTime field is set.
    • getStartTime

      public com.google.protobuf.Timestamp getStartTime()
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getStartTime in interface TrainingPipelineOrBuilder
      Returns:
      The startTime.
    • setStartTime

      public TrainingPipeline.Builder setStartTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setStartTime

      public TrainingPipeline.Builder setStartTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeStartTime

      public TrainingPipeline.Builder mergeStartTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearStartTime

      public TrainingPipeline.Builder clearStartTime()
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getStartTimeBuilder

      public com.google.protobuf.Timestamp.Builder getStartTimeBuilder()
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getStartTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getStartTimeOrBuilder()
       Output only. Time when the TrainingPipeline for the first time entered the
       `PIPELINE_STATE_RUNNING` state.
       
      .google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getStartTimeOrBuilder in interface TrainingPipelineOrBuilder
    • hasEndTime

      public boolean hasEndTime()
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasEndTime in interface TrainingPipelineOrBuilder
      Returns:
      Whether the endTime field is set.
    • getEndTime

      public com.google.protobuf.Timestamp getEndTime()
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getEndTime in interface TrainingPipelineOrBuilder
      Returns:
      The endTime.
    • setEndTime

      public TrainingPipeline.Builder setEndTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setEndTime

      public TrainingPipeline.Builder setEndTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeEndTime

      public TrainingPipeline.Builder mergeEndTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearEndTime

      public TrainingPipeline.Builder clearEndTime()
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getEndTimeBuilder

      public com.google.protobuf.Timestamp.Builder getEndTimeBuilder()
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getEndTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getEndTimeOrBuilder()
       Output only. Time when the TrainingPipeline entered any of the following
       states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
       `PIPELINE_STATE_CANCELLED`.
       
      .google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getEndTimeOrBuilder in interface TrainingPipelineOrBuilder
    • hasUpdateTime

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

      public com.google.protobuf.Timestamp getUpdateTime()
       Output only. Time when the TrainingPipeline was most recently updated.
       
      .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTime in interface TrainingPipelineOrBuilder
      Returns:
      The updateTime.
    • setUpdateTime

      public TrainingPipeline.Builder setUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline was most recently updated.
       
      .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setUpdateTime

      public TrainingPipeline.Builder setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Time when the TrainingPipeline was most recently updated.
       
      .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeUpdateTime

      public TrainingPipeline.Builder mergeUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Time when the TrainingPipeline was most recently updated.
       
      .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearUpdateTime

      public TrainingPipeline.Builder clearUpdateTime()
       Output only. Time when the TrainingPipeline 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. Time when the TrainingPipeline 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. Time when the TrainingPipeline was most recently updated.
       
      .google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTimeOrBuilder in interface TrainingPipelineOrBuilder
    • getLabelsCount

      public int getLabelsCount()
      Description copied from interface: TrainingPipelineOrBuilder
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
      Specified by:
      getLabelsCount in interface TrainingPipelineOrBuilder
    • containsLabels

      public boolean containsLabels(String key)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
      Specified by:
      containsLabels in interface TrainingPipelineOrBuilder
    • getLabels

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

      public Map<String,String> getLabelsMap()
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
      Specified by:
      getLabelsMap in interface TrainingPipelineOrBuilder
    • getLabelsOrDefault

      public String getLabelsOrDefault(String key, String defaultValue)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
      Specified by:
      getLabelsOrDefault in interface TrainingPipelineOrBuilder
    • getLabelsOrThrow

      public String getLabelsOrThrow(String key)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
      Specified by:
      getLabelsOrThrow in interface TrainingPipelineOrBuilder
    • clearLabels

      public TrainingPipeline.Builder clearLabels()
    • removeLabels

      public TrainingPipeline.Builder removeLabels(String key)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
    • getMutableLabels

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

      public TrainingPipeline.Builder putLabels(String key, String value)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
    • putAllLabels

      public TrainingPipeline.Builder putAllLabels(Map<String,String> values)
       The labels with user-defined metadata to organize TrainingPipelines.
      
       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 = 15;
    • hasEncryptionSpec

      public boolean hasEncryptionSpec()
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
      Specified by:
      hasEncryptionSpec in interface TrainingPipelineOrBuilder
      Returns:
      Whether the encryptionSpec field is set.
    • getEncryptionSpec

      public EncryptionSpec getEncryptionSpec()
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
      Specified by:
      getEncryptionSpec in interface TrainingPipelineOrBuilder
      Returns:
      The encryptionSpec.
    • setEncryptionSpec

      public TrainingPipeline.Builder setEncryptionSpec(EncryptionSpec value)
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
    • setEncryptionSpec

      public TrainingPipeline.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
    • mergeEncryptionSpec

      public TrainingPipeline.Builder mergeEncryptionSpec(EncryptionSpec value)
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
    • clearEncryptionSpec

      public TrainingPipeline.Builder clearEncryptionSpec()
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
    • getEncryptionSpecBuilder

      public EncryptionSpec.Builder getEncryptionSpecBuilder()
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
    • getEncryptionSpecOrBuilder

      public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
       Customer-managed encryption key spec for a TrainingPipeline. If set, this
       TrainingPipeline will be secured by this key.
      
       Note: Model trained by this TrainingPipeline is also secured by this key if
       [model_to_upload][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec]
       is not set separately.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
      Specified by:
      getEncryptionSpecOrBuilder in interface TrainingPipelineOrBuilder