Package com.google.cloud.aiplatform.v1beta1

Interface TrainingPipelineOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    TrainingPipeline, TrainingPipeline.Builder
    public interface TrainingPipelineOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • getName

        String getName()
         Output only. Resource name of the TrainingPipeline.
        string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The name.

      • getNameBytes

        com.google.protobuf.ByteString getNameBytes()
         Output only. Resource name of the TrainingPipeline.
        string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The bytes for name.

      • getDisplayName

        String getDisplayName()
         Required. The user-defined name of this TrainingPipeline.
        string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The displayName.

      • getDisplayNameBytes

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

      • hasInputDataConfig

        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.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
        .google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;
        Returns:
        Whether the inputDataConfig field is set.

      • getInputDataConfig

        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.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
        .google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;
        Returns:
        The inputDataConfig.

      • getInputDataConfigOrBuilder

        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.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
        .google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;

      • getTrainingTaskDefinition

        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];
        Returns:
        The trainingTaskDefinition.

      • getTrainingTaskDefinitionBytes

        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];
        Returns:
        The bytes for trainingTaskDefinition.

      • hasTrainingTaskInputs

        boolean hasTrainingTaskInputs()
         Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
        .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        Whether the trainingTaskInputs field is set.

      • getTrainingTaskInputs

        com.google.protobuf.Value getTrainingTaskInputs()
         Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
        .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The trainingTaskInputs.

      • getTrainingTaskInputsOrBuilder

        com.google.protobuf.ValueOrBuilder getTrainingTaskInputsOrBuilder()
         Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
        .google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];

      • hasTrainingTaskMetadata

        boolean hasTrainingTaskMetadata()
         Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
        .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        Whether the trainingTaskMetadata field is set.

      • getTrainingTaskMetadata

        com.google.protobuf.Value getTrainingTaskMetadata()
         Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
        .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The trainingTaskMetadata.

      • getTrainingTaskMetadataOrBuilder

        com.google.protobuf.ValueOrBuilder getTrainingTaskMetadataOrBuilder()
         Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
        .google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • hasModelToUpload

        boolean hasModelToUpload()
         Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
        .google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;
        Returns:
        Whether the modelToUpload field is set.

      • getModelToUpload

        Model getModelToUpload()
         Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
        .google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;
        Returns:
        The modelToUpload.

      • getModelToUploadOrBuilder

        ModelOrBuilder getModelToUploadOrBuilder()
         Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.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.v1beta1.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.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
        .google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;

      • getModelId

        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];
        Returns:
        The modelId.

      • getModelIdBytes

        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];
        Returns:
        The bytes for modelId.

      • getParentModel

        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];
        Returns:
        The parentModel.

      • getParentModelBytes

        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];
        Returns:
        The bytes for parentModel.

      • getStateValue

        int getStateValue()
         Output only. The detailed state of the pipeline.
        .google.cloud.aiplatform.v1beta1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The enum numeric value on the wire for state.

      • getState

        PipelineState getState()
         Output only. The detailed state of the pipeline.
        .google.cloud.aiplatform.v1beta1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The state.

      • hasError

        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];
        Returns:
        Whether the error field is set.

      • getError

        com.google.rpc.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];
        Returns:
        The error.

      • getErrorOrBuilder

        com.google.rpc.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];

      • hasCreateTime

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

      • getCreateTime

        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];
        Returns:
        The createTime.

      • getCreateTimeOrBuilder

        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];

      • hasStartTime

        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];
        Returns:
        Whether the startTime field is set.

      • getStartTime

        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];
        Returns:
        The startTime.

      • getStartTimeOrBuilder

        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];

      • hasEndTime

        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];
        Returns:
        Whether the endTime field is set.

      • getEndTime

        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];
        Returns:
        The endTime.

      • getEndTimeOrBuilder

        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];

      • hasUpdateTime

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

      • getUpdateTime

        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];
        Returns:
        The updateTime.

      • getUpdateTimeOrBuilder

        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];

      • getLabelsCount

        int getLabelsCount()
         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;

      • containsLabels

        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;

      • getLabelsMap

        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;

      • getLabelsOrDefault

        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;

      • getLabelsOrThrow

        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;

      • hasEncryptionSpec

        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.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;
        Returns:
        Whether the encryptionSpec field is set.

      • getEncryptionSpec

        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.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;
        Returns:
        The encryptionSpec.

      • getEncryptionSpecOrBuilder

        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.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
        .google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;