Interface TrainingPipelineOrBuilder (3.48.0) 

public interface TrainingPipelineOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

containsLabels(String key)

public abstract 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;

Parameter
Name Description
key String
Returns
Type Description
boolean

getCreateTime()

public abstract Timestamp getCreateTime()

Output only. Time when the TrainingPipeline was created.

.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
Timestamp

The createTime.

getCreateTimeOrBuilder()

public abstract TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Time when the TrainingPipeline was created.

.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
TimestampOrBuilder

getDisplayName()

public abstract String getDisplayName()

Required. The user-defined name of this TrainingPipeline.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
String

The displayName.

getDisplayNameBytes()

public abstract ByteString getDisplayNameBytes()

Required. The user-defined name of this TrainingPipeline.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
ByteString

The bytes for displayName.

getEncryptionSpec()

public abstract 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 is not set separately.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;

Returns
Type Description
EncryptionSpec

The encryptionSpec.

getEncryptionSpecOrBuilder()

public abstract 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 is not set separately.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;

Returns
Type Description
EncryptionSpecOrBuilder

getEndTime()

public abstract 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
Type Description
Timestamp

The endTime.

getEndTimeOrBuilder()

public abstract 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];

Returns
Type Description
TimestampOrBuilder

getError()

public abstract 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
Type Description
com.google.rpc.Status

The error.

getErrorOrBuilder()

public abstract 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];

Returns
Type Description
com.google.rpc.StatusOrBuilder

getInputDataConfig()

public abstract InputDataConfig getInputDataConfig()

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's 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, then it should be assumed that the TrainingPipeline does not depend on this configuration.

.google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;

Returns
Type Description
InputDataConfig

The inputDataConfig.

getInputDataConfigOrBuilder()

public abstract InputDataConfigOrBuilder getInputDataConfigOrBuilder()

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's 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, then it should be assumed that the TrainingPipeline does not depend on this configuration.

.google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;

Returns
Type Description
InputDataConfigOrBuilder

getLabels() (deprecated)

public abstract Map<String,String> getLabels()

Use #getLabelsMap() instead.

Returns
Type Description
Map<String,String>

getLabelsCount()

public abstract 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;

Returns
Type Description
int

getLabelsMap()

public abstract 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;

Returns
Type Description
Map<String,String>

getLabelsOrDefault(String key, String defaultValue)

public abstract 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;

Parameters
Name Description
key String
defaultValue String
Returns
Type Description
String

getLabelsOrThrow(String key)

public abstract 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;

Parameter
Name Description
key String
Returns
Type Description
String

getModelId()

public abstract 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
Type Description
String

The modelId.

getModelIdBytes()

public abstract 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
Type Description
ByteString

The bytes for modelId.

getModelToUpload()

public abstract Model getModelToUpload()

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's 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, 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 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
Type Description
Model

The modelToUpload.

getModelToUploadOrBuilder()

public abstract ModelOrBuilder getModelToUploadOrBuilder()

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's 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, 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 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
Type Description
ModelOrBuilder

getName()

public abstract String getName()

Output only. Resource name of the TrainingPipeline.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
String

The name.

getNameBytes()

public abstract ByteString getNameBytes()

Output only. Resource name of the TrainingPipeline.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
ByteString

The bytes for name.

getParentModel()

public abstract 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
Type Description
String

The parentModel.

getParentModelBytes()

public abstract 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
Type Description
ByteString

The bytes for parentModel.

getStartTime()

public abstract 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
Type Description
Timestamp

The startTime.

getStartTimeOrBuilder()

public abstract 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];

Returns
Type Description
TimestampOrBuilder

getState()

public abstract PipelineState getState()

Output only. The detailed state of the pipeline.

.google.cloud.aiplatform.v1beta1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
PipelineState

The state.

getStateValue()

public abstract int getStateValue()

Output only. The detailed state of the pipeline.

.google.cloud.aiplatform.v1beta1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
int

The enum numeric value on the wire for state.

getTrainingTaskDefinition()

public abstract 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
Type Description
String

The trainingTaskDefinition.

getTrainingTaskDefinitionBytes()

public abstract 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
Type Description
ByteString

The bytes for trainingTaskDefinition.

getTrainingTaskInputs()

public abstract Value getTrainingTaskInputs()

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.

.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
Value

The trainingTaskInputs.

getTrainingTaskInputsOrBuilder()

public abstract ValueOrBuilder getTrainingTaskInputsOrBuilder()

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.

.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
ValueOrBuilder

getTrainingTaskMetadata()

public abstract Value getTrainingTaskMetadata()

Output only. The metadata information as specified in the 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 contains metadata object.

.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
Value

The trainingTaskMetadata.

getTrainingTaskMetadataOrBuilder()

public abstract ValueOrBuilder getTrainingTaskMetadataOrBuilder()

Output only. The metadata information as specified in the 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 contains metadata object.

.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
ValueOrBuilder

getUpdateTime()

public abstract 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
Type Description
Timestamp

The updateTime.

getUpdateTimeOrBuilder()

public abstract TimestampOrBuilder getUpdateTimeOrBuilder()

Output only. Time when the TrainingPipeline was most recently updated.

.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
TimestampOrBuilder

hasCreateTime()

public abstract boolean hasCreateTime()

Output only. Time when the TrainingPipeline was created.

.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
boolean

Whether the createTime field is set.

hasEncryptionSpec()

public abstract 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 is not set separately.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 18;

Returns
Type Description
boolean

Whether the encryptionSpec field is set.

hasEndTime()

public abstract 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
Type Description
boolean

Whether the endTime field is set.

hasError()

public abstract 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
Type Description
boolean

Whether the error field is set.

hasInputDataConfig()

public abstract boolean hasInputDataConfig()

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's 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, then it should be assumed that the TrainingPipeline does not depend on this configuration.

.google.cloud.aiplatform.v1beta1.InputDataConfig input_data_config = 3;

Returns
Type Description
boolean

Whether the inputDataConfig field is set.

hasModelToUpload()

public abstract boolean hasModelToUpload()

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's 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, 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 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
Type Description
boolean

Whether the modelToUpload field is set.

hasStartTime()

public abstract 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
Type Description
boolean

Whether the startTime field is set.

hasTrainingTaskInputs()

public abstract boolean hasTrainingTaskInputs()

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.

.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
boolean

Whether the trainingTaskInputs field is set.

hasTrainingTaskMetadata()

public abstract boolean hasTrainingTaskMetadata()

Output only. The metadata information as specified in the 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 contains metadata object.

.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type Description
boolean

Whether the trainingTaskMetadata field is set.

hasUpdateTime()

public abstract 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
Type Description
boolean

Whether the updateTime field is set.