Class TrainingPipeline (3.4.1)

Version 3.4.1

• 3.55.0 (latest)
• 3.54.0
• 3.53.0
• 3.52.0
• 3.50.0
• 3.49.0
• 3.48.0
• 3.47.0
• 3.46.0
• 3.45.0
• 3.44.0
• 3.43.0
• 3.42.0
• 3.41.0
• 3.40.0
• 3.38.0
• 3.37.0
• 3.36.0
• 3.35.0
• 3.34.0
• 3.33.0
• 3.32.0
• 3.31.0
• 3.30.0
• 3.29.0
• 3.28.0
• 3.25.0
• 3.24.0
• 3.23.0
• 3.22.0
• 3.21.0
• 3.20.0
• 3.19.0
• 3.18.0
• 3.17.0
• 3.16.0
• 3.15.0
• 3.14.0
• 3.13.0
• 3.12.0
• 3.11.0
• 3.10.0
• 3.9.0
• 3.8.0
• 3.7.0
• 3.6.0
• 3.5.0
• 3.4.2
• 3.3.0
• 3.2.0
• 3.0.0
• 2.9.8
• 2.8.9
• 2.7.4
• 2.5.3
• 2.4.0

public final class TrainingPipeline extends GeneratedMessageV3 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.v1beta1.TrainingPipeline

Inheritance

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

Implements

TrainingPipelineOrBuilder

Inherited Members

AbstractMessage.equals(Object)

AbstractMessage.findInitializationErrors()

AbstractMessage.getInitializationErrorString()

AbstractMessage.hashBoolean(boolean)

AbstractMessage.hashCode()

AbstractMessage.hashEnum(Internal.EnumLite)

AbstractMessage.hashEnumList(List<? extends Internal.EnumLite>)

AbstractMessage.hashFields(int,Map<Descriptors.FieldDescriptor,Object>)

AbstractMessage.hashLong(long)

AbstractMessage.toString()

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

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

AbstractMessageLite.checkByteStringIsUtf8(ByteString)

AbstractMessageLite.toByteArray()

AbstractMessageLite.toByteString()

AbstractMessageLite.writeDelimitedTo(OutputStream)

AbstractMessageLite.writeTo(OutputStream)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

GeneratedMessageV3.<V>serializeBooleanMapTo(CodedOutputStream,MapField<Boolean,V>,MapEntry<Boolean,V>,int)

GeneratedMessageV3.<V>serializeIntegerMapTo(CodedOutputStream,MapField<Integer,V>,MapEntry<Integer,V>,int)

GeneratedMessageV3.<V>serializeLongMapTo(CodedOutputStream,MapField<Long,V>,MapEntry<Long,V>,int)

GeneratedMessageV3.<V>serializeStringMapTo(CodedOutputStream,MapField<String,V>,MapEntry<String,V>,int)

GeneratedMessageV3.canUseUnsafe()

GeneratedMessageV3.computeStringSize(int,Object)

GeneratedMessageV3.computeStringSizeNoTag(Object)

GeneratedMessageV3.emptyBooleanList()

GeneratedMessageV3.emptyDoubleList()

GeneratedMessageV3.emptyFloatList()

GeneratedMessageV3.emptyIntList()

GeneratedMessageV3.emptyLongList()

GeneratedMessageV3.getAllFields()

GeneratedMessageV3.getDescriptorForType()

GeneratedMessageV3.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.getParserForType()

GeneratedMessageV3.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.getSerializedSize()

GeneratedMessageV3.getUnknownFields()

GeneratedMessageV3.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.internalGetFieldAccessorTable()

GeneratedMessageV3.internalGetMapField(int)

GeneratedMessageV3.isInitialized()

GeneratedMessageV3.isStringEmpty(Object)

GeneratedMessageV3.makeExtensionsImmutable()

GeneratedMessageV3.mergeFromAndMakeImmutableInternal(CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.mutableCopy(Internal.BooleanList)

GeneratedMessageV3.mutableCopy(Internal.DoubleList)

GeneratedMessageV3.mutableCopy(Internal.FloatList)

GeneratedMessageV3.mutableCopy(Internal.IntList)

GeneratedMessageV3.mutableCopy(Internal.LongList)

GeneratedMessageV3.newBooleanList()

GeneratedMessageV3.newBuilderForType(AbstractMessage.BuilderParent)

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent)

GeneratedMessageV3.newDoubleList()

GeneratedMessageV3.newFloatList()

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter)

GeneratedMessageV3.newIntList()

GeneratedMessageV3.newLongList()

GeneratedMessageV3.parseUnknownField(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.parseUnknownFieldProto3(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.writeReplace()

GeneratedMessageV3.writeString(CodedOutputStream,int,Object)

GeneratedMessageV3.writeStringNoTag(CodedOutputStream,Object)

GeneratedMessageV3.writeTo(CodedOutputStream)

Object.clone()

Object.finalize()

Object.getClass()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Fields

CREATE_TIME_FIELD_NUMBER

public static final int CREATE_TIME_FIELD_NUMBER

Field Value

Type	Description
int

DISPLAY_NAME_FIELD_NUMBER

public static final int DISPLAY_NAME_FIELD_NUMBER

Field Value

Type	Description
int

ENCRYPTION_SPEC_FIELD_NUMBER

public static final int ENCRYPTION_SPEC_FIELD_NUMBER

Field Value

Type	Description
int

END_TIME_FIELD_NUMBER

public static final int END_TIME_FIELD_NUMBER

Field Value

Type	Description
int

ERROR_FIELD_NUMBER

public static final int ERROR_FIELD_NUMBER

Field Value

Type	Description
int

INPUT_DATA_CONFIG_FIELD_NUMBER

public static final int INPUT_DATA_CONFIG_FIELD_NUMBER

Field Value

Type	Description
int

LABELS_FIELD_NUMBER

public static final int LABELS_FIELD_NUMBER

Field Value

Type	Description
int

MODEL_ID_FIELD_NUMBER

public static final int MODEL_ID_FIELD_NUMBER

Field Value

Type	Description
int

MODEL_TO_UPLOAD_FIELD_NUMBER

public static final int MODEL_TO_UPLOAD_FIELD_NUMBER

Field Value

Type	Description
int

NAME_FIELD_NUMBER

public static final int NAME_FIELD_NUMBER

Field Value

Type	Description
int

PARENT_MODEL_FIELD_NUMBER

public static final int PARENT_MODEL_FIELD_NUMBER

Field Value

Type	Description
int

START_TIME_FIELD_NUMBER

public static final int START_TIME_FIELD_NUMBER

Field Value

Type	Description
int

STATE_FIELD_NUMBER

public static final int STATE_FIELD_NUMBER

Field Value

Type	Description
int

TRAINING_TASK_DEFINITION_FIELD_NUMBER

public static final int TRAINING_TASK_DEFINITION_FIELD_NUMBER

Field Value

Type	Description
int

TRAINING_TASK_INPUTS_FIELD_NUMBER

public static final int TRAINING_TASK_INPUTS_FIELD_NUMBER

Field Value

Type	Description
int

TRAINING_TASK_METADATA_FIELD_NUMBER

public static final int TRAINING_TASK_METADATA_FIELD_NUMBER

Field Value

Type	Description
int

UPDATE_TIME_FIELD_NUMBER

public static final int UPDATE_TIME_FIELD_NUMBER

Field Value

Type	Description
int

Static Methods

getDefaultInstance()

public static TrainingPipeline getDefaultInstance()

Returns

Type	Description
TrainingPipeline

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

newBuilder()

public static TrainingPipeline.Builder newBuilder()

Returns

Type	Description
TrainingPipeline.Builder

newBuilder(TrainingPipeline prototype)

public static TrainingPipeline.Builder newBuilder(TrainingPipeline prototype)

Parameter

Name	Description
prototype	TrainingPipeline

Returns

Type	Description
TrainingPipeline.Builder

parseDelimitedFrom(InputStream input)

public static TrainingPipeline parseDelimitedFrom(InputStream input)

Parameter

Name	Description
input	InputStream

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseFrom(byte[] data)

public static TrainingPipeline parseFrom(byte[] data)

Parameter

Name	Description
data	byte[]

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
data	byte[]
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static TrainingPipeline parseFrom(ByteString data)

Parameter

Name	Description
data	ByteString

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
data	ByteString
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static TrainingPipeline parseFrom(CodedInputStream input)

Parameter

Name	Description
input	CodedInputStream

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseFrom(InputStream input)

public static TrainingPipeline parseFrom(InputStream input)

Parameter

Name	Description
input	InputStream

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
IOException

parseFrom(ByteBuffer data)

public static TrainingPipeline parseFrom(ByteBuffer data)

Parameter

Name	Description
data	ByteBuffer

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static TrainingPipeline parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
data	ByteBuffer
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TrainingPipeline

Exceptions

Type	Description
InvalidProtocolBufferException

parser()

public static Parser<TrainingPipeline> parser()

Returns

Type	Description
Parser<TrainingPipeline>

Methods

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

equals(Object obj)

public boolean equals(Object obj)

Parameter

Name	Description
obj	Object

Returns

Type	Description
boolean

Overrides

AbstractMessage.equals(Object other)

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.

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

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.v1beta1.EncryptionSpec encryption_spec = 18;

Returns

Type	Description
EncryptionSpec	The encryptionSpec.

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.v1beta1.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.

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.

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.v1beta1.InputDataConfig input_data_config = 3;

Returns

Type	Description
InputDataConfig	The inputDataConfig.

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.v1beta1.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.v1beta1.Model model_to_upload = 7;

Returns

Type	Description
Model	The modelToUpload.

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.v1beta1.Model model_to_upload = 7;

Returns

Type	Description
ModelOrBuilder

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.

getParserForType()

public Parser<TrainingPipeline> getParserForType()

Returns

Type	Description
Parser<TrainingPipeline>

Overrides

GeneratedMessageV3.getParserForType()

getSerializedSize()

public int getSerializedSize()

Returns

Type	Description
int

Overrides

GeneratedMessageV3.getSerializedSize()

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.

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.v1beta1.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.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 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.

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.

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

getUnknownFields()

public final UnknownFieldSet getUnknownFields()

Returns

Type	Description
UnknownFieldSet

Overrides

GeneratedMessageV3.getUnknownFields()

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.

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.v1beta1.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.v1beta1.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.v1beta1.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.

hashCode()

public int hashCode()

Returns

Type	Description
int

Overrides

AbstractMessage.hashCode()

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.internalGetFieldAccessorTable()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter

Name	Description
number	int

Returns

Type	Description
MapField

Overrides

GeneratedMessageV3.internalGetMapField(int fieldNumber)

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.isInitialized()

newBuilderForType()

public TrainingPipeline.Builder newBuilderForType()

Returns

Type	Description
TrainingPipeline.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected TrainingPipeline.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)

Parameter

Name	Description
parent	BuilderParent

Returns

Type	Description
TrainingPipeline.Builder

Overrides

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent parent)

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

Parameter

Name	Description
unused	UnusedPrivateParameter

Returns

Type	Description
Object

Overrides

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

toBuilder()

public TrainingPipeline.Builder toBuilder()

Returns

Type	Description
TrainingPipeline.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)

Parameter

Name	Description
output	CodedOutputStream

Overrides

GeneratedMessageV3.writeTo(CodedOutputStream output)

Exceptions

Type	Description
IOException