Class TrainingPipeline.Builder (3.12.0)

Version 3.12.0

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public static final class TrainingPipeline.Builder extends GeneratedMessageV3.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 the Model to Vertex AI, and evaluate the Model.

Protobuf type google.cloud.aiplatform.v1.TrainingPipeline

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TrainingPipeline.Builder

Implements

TrainingPipelineOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TrainingPipeline.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public TrainingPipeline build()

Returns

Type	Description
TrainingPipeline

buildPartial()

public TrainingPipeline buildPartial()

Returns

Type	Description
TrainingPipeline

clear()

public TrainingPipeline.Builder clear()

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

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];

Returns

Type	Description
TrainingPipeline.Builder

clearDisplayName()

public TrainingPipeline.Builder clearDisplayName()

Required. The user-defined name of this TrainingPipeline.

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

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
TrainingPipeline.Builder

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];

Returns

Type	Description
TrainingPipeline.Builder

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];

Returns

Type	Description
TrainingPipeline.Builder

clearField(Descriptors.FieldDescriptor field)

public TrainingPipeline.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

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 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.v1.InputDataConfig input_data_config = 3;

Returns

Type	Description
TrainingPipeline.Builder

clearLabels()

public TrainingPipeline.Builder clearLabels()

Returns

Type	Description
TrainingPipeline.Builder

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

Type	Description
TrainingPipeline.Builder	This builder for chaining.

clearModelToUpload()

public TrainingPipeline.Builder clearModelToUpload()

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.v1.Model model_to_upload = 7;

Returns

Type	Description
TrainingPipeline.Builder

clearName()

public TrainingPipeline.Builder clearName()

Output only. Resource name of the TrainingPipeline.

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

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public TrainingPipeline.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

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

Type	Description
TrainingPipeline.Builder	This builder for chaining.

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];

Returns

Type	Description
TrainingPipeline.Builder

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

Type	Description
TrainingPipeline.Builder	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

Type	Description
TrainingPipeline.Builder	This builder for chaining.

clearTrainingTaskInputs()

public TrainingPipeline.Builder clearTrainingTaskInputs()

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
TrainingPipeline.Builder

clearTrainingTaskMetadata()

public TrainingPipeline.Builder clearTrainingTaskMetadata()

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
TrainingPipeline.Builder

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];

Returns

Type	Description
TrainingPipeline.Builder

clone()

public TrainingPipeline.Builder clone()

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsLabels(String key)

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;

Parameter

Name	Description
key	String

Returns

Type	Description
boolean

getCreateTime()

public 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.

getCreateTimeBuilder()

public Timestamp.Builder getCreateTimeBuilder()

Output only. Time when the TrainingPipeline was created.

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

Returns

Type	Description
Builder

getCreateTimeOrBuilder()

public 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

getDefaultInstanceForType()

public TrainingPipeline getDefaultInstanceForType()

Returns

Type	Description
TrainingPipeline

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDisplayName()

public 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 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 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.v1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
EncryptionSpec	The encryptionSpec.

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
EncryptionSpec.Builder

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
EncryptionSpecOrBuilder

getEndTime()

public 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.

getEndTimeBuilder()

public 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];

Returns

Type	Description
Builder

getEndTimeOrBuilder()

public 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 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.

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];

Returns

Type	Description
com.google.rpc.Status.Builder

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];

Returns

Type	Description
com.google.rpc.StatusOrBuilder

getInputDataConfig()

public 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.v1.InputDataConfig input_data_config = 3;

Returns

Type	Description
InputDataConfig	The inputDataConfig.

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 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.v1.InputDataConfig input_data_config = 3;

Returns

Type	Description
InputDataConfig.Builder

getInputDataConfigOrBuilder()

public 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.v1.InputDataConfig input_data_config = 3;

Returns

Type	Description
InputDataConfigOrBuilder

getLabels()

public Map<String,String> getLabels()

Use #getLabelsMap() instead.

Returns

Type	Description
Map<String,String>

getLabelsCount()

public 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 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 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 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 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 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 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.v1.Model model_to_upload = 7;

Returns

Type	Description
Model	The modelToUpload.

getModelToUploadBuilder()

public Model.Builder getModelToUploadBuilder()

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.v1.Model model_to_upload = 7;

Returns

Type	Description
Model.Builder

getModelToUploadOrBuilder()

public 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.v1.Model model_to_upload = 7;

Returns

Type	Description
ModelOrBuilder

getMutableLabels()

public Map<String,String> getMutableLabels()

Use alternate mutation accessors instead.

Returns

Type	Description
Map<String,String>

getName()

public 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 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 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 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 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.

getStartTimeBuilder()

public 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];

Returns

Type	Description
Builder

getStartTimeOrBuilder()

public 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 PipelineState getState()

Output only. The detailed state of the pipeline.

.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns

Type	Description
PipelineState	The state.

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];

Returns

Type	Description
int	The enum numeric value on the wire for state.

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];

Returns

Type	Description
String	The trainingTaskDefinition.

getTrainingTaskDefinitionBytes()

public 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 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.

getTrainingTaskInputsBuilder()

public Value.Builder getTrainingTaskInputsBuilder()

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
Builder

getTrainingTaskInputsOrBuilder()

public 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 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.

getTrainingTaskMetadataBuilder()

public Value.Builder getTrainingTaskMetadataBuilder()

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
Builder

getTrainingTaskMetadataOrBuilder()

public 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 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.

getUpdateTimeBuilder()

public 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];

Returns

Type	Description
Builder

getUpdateTimeOrBuilder()

public 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 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 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.v1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
boolean	Whether the encryptionSpec field is set.

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];

Returns

Type	Description
boolean	Whether the endTime field is set.

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];

Returns

Type	Description
boolean	Whether the error field is set.

hasInputDataConfig()

public 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.v1.InputDataConfig input_data_config = 3;

Returns

Type	Description
boolean	Whether the inputDataConfig field is set.

hasModelToUpload()

public 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.v1.Model model_to_upload = 7;

Returns

Type	Description
boolean	Whether the modelToUpload field is set.

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];

Returns

Type	Description
boolean	Whether the startTime field is set.

hasTrainingTaskInputs()

public 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 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 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.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter

Name	Description
number	int

Returns

Type	Description
MapField

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMapField(int fieldNumber)

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)

Parameter

Name	Description
number	int

Returns

Type	Description
MapField

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMutableMapField(int fieldNumber)

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeCreateTime(Timestamp value)

public TrainingPipeline.Builder mergeCreateTime(Timestamp value)

Output only. Time when the TrainingPipeline was created.

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

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

mergeEncryptionSpec(EncryptionSpec value)

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Parameter

Name	Description
value	EncryptionSpec

Returns

Type	Description
TrainingPipeline.Builder

mergeEndTime(Timestamp value)

public TrainingPipeline.Builder mergeEndTime(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];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

mergeError(Status value)

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];

Parameter

Name	Description
value	com.google.rpc.Status

Returns

Type	Description
TrainingPipeline.Builder

mergeFrom(TrainingPipeline other)

public TrainingPipeline.Builder mergeFrom(TrainingPipeline other)

Parameter

Name	Description
other	TrainingPipeline

Returns

Type	Description
TrainingPipeline.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TrainingPipeline.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public TrainingPipeline.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
TrainingPipeline.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeInputDataConfig(InputDataConfig value)

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 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.v1.InputDataConfig input_data_config = 3;

Parameter

Name	Description
value	InputDataConfig

Returns

Type	Description
TrainingPipeline.Builder

mergeModelToUpload(Model value)

public TrainingPipeline.Builder mergeModelToUpload(Model value)

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.v1.Model model_to_upload = 7;

Parameter

Name	Description
value	Model

Returns

Type	Description
TrainingPipeline.Builder

mergeStartTime(Timestamp value)

public TrainingPipeline.Builder mergeStartTime(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];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

mergeTrainingTaskInputs(Value value)

public TrainingPipeline.Builder mergeTrainingTaskInputs(Value value)

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];

Parameter

Name	Description
value	Value

Returns

Type	Description
TrainingPipeline.Builder

mergeTrainingTaskMetadata(Value value)

public TrainingPipeline.Builder mergeTrainingTaskMetadata(Value value)

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];

Parameter

Name	Description
value	Value

Returns

Type	Description
TrainingPipeline.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TrainingPipeline.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

mergeUpdateTime(Timestamp value)

public TrainingPipeline.Builder mergeUpdateTime(Timestamp value)

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

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

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

putAllLabels(Map<String,String> values)

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;

Parameter

Name	Description
values	Map<String,String>

Returns

Type	Description
TrainingPipeline.Builder

putLabels(String key, String value)

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;

Parameters

Name	Description
key	String
value	String

Returns

Type	Description
TrainingPipeline.Builder

removeLabels(String key)

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;

Parameter

Name	Description
key	String

Returns

Type	Description
TrainingPipeline.Builder

setCreateTime(Timestamp value)

public TrainingPipeline.Builder setCreateTime(Timestamp value)

Output only. Time when the TrainingPipeline was created.

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

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

setCreateTime(Timestamp.Builder builderForValue)

public TrainingPipeline.Builder setCreateTime(Timestamp.Builder builderForValue)

Output only. Time when the TrainingPipeline was created.

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

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder

setDisplayName(String value)

public TrainingPipeline.Builder setDisplayName(String value)

Required. The user-defined name of this TrainingPipeline.

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

Parameter

Name	Description
value	String The displayName to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setDisplayNameBytes(ByteString value)

public TrainingPipeline.Builder setDisplayNameBytes(ByteString value)

Required. The user-defined name of this TrainingPipeline.

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

Parameter

Name	Description
value	ByteString The bytes for displayName to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setEncryptionSpec(EncryptionSpec value)

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Parameter

Name	Description
value	EncryptionSpec

Returns

Type	Description
TrainingPipeline.Builder

setEncryptionSpec(EncryptionSpec.Builder builderForValue)

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 is not set separately.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;

Parameter

Name	Description
builderForValue	EncryptionSpec.Builder

Returns

Type	Description
TrainingPipeline.Builder

setEndTime(Timestamp value)

public TrainingPipeline.Builder setEndTime(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];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

setEndTime(Timestamp.Builder builderForValue)

public TrainingPipeline.Builder setEndTime(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];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder

setError(Status value)

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];

Parameter

Name	Description
value	com.google.rpc.Status

Returns

Type	Description
TrainingPipeline.Builder

setError(Status.Builder builderForValue)

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];

Parameter

Name	Description
builderForValue	com.google.rpc.Status.Builder

Returns

Type	Description
TrainingPipeline.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public TrainingPipeline.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setInputDataConfig(InputDataConfig value)

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 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.v1.InputDataConfig input_data_config = 3;

Parameter

Name	Description
value	InputDataConfig

Returns

Type	Description
TrainingPipeline.Builder

setInputDataConfig(InputDataConfig.Builder builderForValue)

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 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.v1.InputDataConfig input_data_config = 3;

Parameter

Name	Description
builderForValue	InputDataConfig.Builder

Returns

Type	Description
TrainingPipeline.Builder

setModelId(String value)

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];

Parameter

Name	Description
value	String The modelId to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setModelIdBytes(ByteString value)

public TrainingPipeline.Builder setModelIdBytes(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];

Parameter

Name	Description
value	ByteString The bytes for modelId to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setModelToUpload(Model value)

public TrainingPipeline.Builder setModelToUpload(Model value)

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.v1.Model model_to_upload = 7;

Parameter

Name	Description
value	Model

Returns

Type	Description
TrainingPipeline.Builder

setModelToUpload(Model.Builder builderForValue)

public TrainingPipeline.Builder setModelToUpload(Model.Builder builderForValue)

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.v1.Model model_to_upload = 7;

Parameter

Name	Description
builderForValue	Model.Builder

Returns

Type	Description
TrainingPipeline.Builder

setName(String value)

public TrainingPipeline.Builder setName(String value)

Output only. Resource name of the TrainingPipeline.

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

Parameter

Name	Description
value	String The name to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setNameBytes(ByteString value)

public TrainingPipeline.Builder setNameBytes(ByteString value)

Output only. Resource name of the TrainingPipeline.

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

Parameter

Name	Description
value	ByteString The bytes for name to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setParentModel(String value)

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];

Parameter

Name	Description
value	String The parentModel to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setParentModelBytes(ByteString value)

public TrainingPipeline.Builder setParentModelBytes(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];

Parameter

Name	Description
value	ByteString The bytes for parentModel to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TrainingPipeline.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setStartTime(Timestamp value)

public TrainingPipeline.Builder setStartTime(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];

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

setStartTime(Timestamp.Builder builderForValue)

public TrainingPipeline.Builder setStartTime(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];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder

setState(PipelineState value)

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];

Parameter

Name	Description
value	PipelineState The state to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setStateValue(int value)

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];

Parameter

Name	Description
value	int The enum numeric value on the wire for state to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setTrainingTaskDefinition(String value)

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];

Parameter

Name	Description
value	String The trainingTaskDefinition to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setTrainingTaskDefinitionBytes(ByteString value)

public TrainingPipeline.Builder setTrainingTaskDefinitionBytes(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];

Parameter

Name	Description
value	ByteString The bytes for trainingTaskDefinition to set.

Returns

Type	Description
TrainingPipeline.Builder	This builder for chaining.

setTrainingTaskInputs(Value value)

public TrainingPipeline.Builder setTrainingTaskInputs(Value value)

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];

Parameter

Name	Description
value	Value

Returns

Type	Description
TrainingPipeline.Builder

setTrainingTaskInputs(Value.Builder builderForValue)

public TrainingPipeline.Builder setTrainingTaskInputs(Value.Builder builderForValue)

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];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder

setTrainingTaskMetadata(Value value)

public TrainingPipeline.Builder setTrainingTaskMetadata(Value value)

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];

Parameter

Name	Description
value	Value

Returns

Type	Description
TrainingPipeline.Builder

setTrainingTaskMetadata(Value.Builder builderForValue)

public TrainingPipeline.Builder setTrainingTaskMetadata(Value.Builder builderForValue)

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];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final TrainingPipeline.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)

setUpdateTime(Timestamp value)

public TrainingPipeline.Builder setUpdateTime(Timestamp value)

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

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

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TrainingPipeline.Builder

setUpdateTime(Timestamp.Builder builderForValue)

public TrainingPipeline.Builder setUpdateTime(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];

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TrainingPipeline.Builder