Class TrainingPipeline.Builder (3.48.0) 

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.v1beta1.TrainingPipeline

Inheritance

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

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

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

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.v1beta1.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

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.v1beta1.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.v1beta1.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

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.v1beta1.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

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

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.

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.v1beta1.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.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.

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.v1beta1.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.v1beta1.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.v1beta1.InputDataConfig input_data_config = 3;

Returns
Type Description
InputDataConfigOrBuilder

getLabels() (deprecated)

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.

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.v1beta1.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.v1beta1.Model model_to_upload = 7;

Returns
Type Description
ModelOrBuilder

getMutableLabels() (deprecated)

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.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.

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.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.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

internalGetMutableMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
Parameter
Name Description
number int
Returns
Type Description
com.google.protobuf.MapFieldReflectionAccessor
Overrides
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

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.v1beta1.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
Exceptions
Type Description
IOException

mergeFrom(Message other)

public TrainingPipeline.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
TrainingPipeline.Builder
Overrides

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.v1beta1.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.v1beta1.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

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.v1beta1.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.v1beta1.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

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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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

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.v1beta1.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.v1beta1.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

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