com.google.cloud.aiplatform.v1beta1

Interface TrainingPipelineOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

TrainingPipeline, TrainingPipeline.Builder

public interface TrainingPipelineOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
boolean	containsLabels(String key) The labels with user-defined metadata to organize TrainingPipelines.
com.google.protobuf.Timestamp	getCreateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getCreateTimeOrBuilder() Output only.
String	getDisplayName() Required.
com.google.protobuf.ByteString	getDisplayNameBytes() Required.
EncryptionSpec	getEncryptionSpec() Customer-managed encryption key spec for a TrainingPipeline.
EncryptionSpecOrBuilder	getEncryptionSpecOrBuilder() Customer-managed encryption key spec for a TrainingPipeline.
com.google.protobuf.Timestamp	getEndTime() Output only.
com.google.protobuf.TimestampOrBuilder	getEndTimeOrBuilder() Output only.
com.google.rpc.Status	getError() Output only.
com.google.rpc.StatusOrBuilder	getErrorOrBuilder() Output only.
InputDataConfig	getInputDataConfig() Specifies Vertex AI owned input data that may be used for training the Model.
InputDataConfigOrBuilder	getInputDataConfigOrBuilder() Specifies Vertex AI owned input data that may be used for training the Model.
Map<String,String>	getLabels() Deprecated.
int	getLabelsCount() The labels with user-defined metadata to organize TrainingPipelines.
Map<String,String>	getLabelsMap() The labels with user-defined metadata to organize TrainingPipelines.
String	getLabelsOrDefault(String key, String defaultValue) The labels with user-defined metadata to organize TrainingPipelines.
String	getLabelsOrThrow(String key) The labels with user-defined metadata to organize TrainingPipelines.
String	getModelId() Optional.
com.google.protobuf.ByteString	getModelIdBytes() Optional.
Model	getModelToUpload() Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel]) by this TrainingPipeline.
ModelOrBuilder	getModelToUploadOrBuilder() Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel]) by this TrainingPipeline.
String	getName() Output only.
com.google.protobuf.ByteString	getNameBytes() Output only.
String	getParentModel() Optional.
com.google.protobuf.ByteString	getParentModelBytes() Optional.
com.google.protobuf.Timestamp	getStartTime() Output only.
com.google.protobuf.TimestampOrBuilder	getStartTimeOrBuilder() Output only.
PipelineState	getState() Output only.
int	getStateValue() Output only.
String	getTrainingTaskDefinition() Required.
com.google.protobuf.ByteString	getTrainingTaskDefinitionBytes() Required.
com.google.protobuf.Value	getTrainingTaskInputs() Required.
com.google.protobuf.ValueOrBuilder	getTrainingTaskInputsOrBuilder() Required.
com.google.protobuf.Value	getTrainingTaskMetadata() Output only.
com.google.protobuf.ValueOrBuilder	getTrainingTaskMetadataOrBuilder() Output only.
com.google.protobuf.Timestamp	getUpdateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getUpdateTimeOrBuilder() Output only.
boolean	hasCreateTime() Output only.
boolean	hasEncryptionSpec() Customer-managed encryption key spec for a TrainingPipeline.
boolean	hasEndTime() Output only.
boolean	hasError() Output only.
boolean	hasInputDataConfig() Specifies Vertex AI owned input data that may be used for training the Model.
boolean	hasModelToUpload() Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel]) by this TrainingPipeline.
boolean	hasStartTime() Output only.
boolean	hasTrainingTaskInputs() Required.
boolean	hasTrainingTaskMetadata() Output only.
boolean	hasUpdateTime() Output only.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getName

String getName()

 Output only. Resource name of the TrainingPipeline.
 

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

Returns:

The name.

getNameBytes

com.google.protobuf.ByteString getNameBytes()

 Output only. Resource name of the TrainingPipeline.
 

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

Returns:

The bytes for name.

getDisplayName

String getDisplayName()

 Required. The user-defined name of this TrainingPipeline.
 

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

Returns:

The displayName.

getDisplayNameBytes

com.google.protobuf.ByteString getDisplayNameBytes()

 Required. The user-defined name of this TrainingPipeline.
 

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

Returns:

The bytes for displayName.

hasInputDataConfig

boolean hasInputDataConfig()

 Specifies Vertex AI owned input data that may be used for training the
 Model. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this config is used and if there are any special
 requirements on how it should be filled. If nothing about this config is
 mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
 

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

Returns:

Whether the inputDataConfig field is set.

getInputDataConfig

InputDataConfig getInputDataConfig()

 Specifies Vertex AI owned input data that may be used for training the
 Model. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this config is used and if there are any special
 requirements on how it should be filled. If nothing about this config is
 mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
 

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

Returns:

The inputDataConfig.

getInputDataConfigOrBuilder

InputDataConfigOrBuilder getInputDataConfigOrBuilder()

 Specifies Vertex AI owned input data that may be used for training the
 Model. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this config is used and if there are any special
 requirements on how it should be filled. If nothing about this config is
 mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that the TrainingPipeline does not depend on this
 configuration.
 

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

getTrainingTaskDefinition

String getTrainingTaskDefinition()

 Required. A Google Cloud Storage path to the YAML file that defines the
 training task which is responsible for producing the model artifact, and
 may also include additional auxiliary work. The definition files that can
 be used here are found in
 gs://google-cloud-aiplatform/schema/trainingjob/definition/.
 Note: The URI given on output will be immutable and probably different,
 including the URI scheme, than the one given on input. The output URI will
 point to a location where the user only has a read access.
 

string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];

Returns:

The trainingTaskDefinition.

getTrainingTaskDefinitionBytes

com.google.protobuf.ByteString getTrainingTaskDefinitionBytes()

 Required. A Google Cloud Storage path to the YAML file that defines the
 training task which is responsible for producing the model artifact, and
 may also include additional auxiliary work. The definition files that can
 be used here are found in
 gs://google-cloud-aiplatform/schema/trainingjob/definition/.
 Note: The URI given on output will be immutable and probably different,
 including the URI scheme, than the one given on input. The output URI will
 point to a location where the user only has a read access.
 

string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];

Returns:

The bytes for trainingTaskDefinition.

hasTrainingTaskInputs

boolean hasTrainingTaskInputs()

 Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
 

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

Returns:

Whether the trainingTaskInputs field is set.

getTrainingTaskInputs

com.google.protobuf.Value getTrainingTaskInputs()

 Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
 

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

Returns:

The trainingTaskInputs.

getTrainingTaskInputsOrBuilder

com.google.protobuf.ValueOrBuilder getTrainingTaskInputsOrBuilder()

 Required. The training task's parameter(s), as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `inputs`.
 

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

hasTrainingTaskMetadata

boolean hasTrainingTaskMetadata()

 Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `metadata`. This metadata is an auxiliary runtime and final information
 about the training task. While the pipeline is running this information is
 populated only at a best effort basis. Only present if the
 pipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
 

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

Returns:

Whether the trainingTaskMetadata field is set.

getTrainingTaskMetadata

com.google.protobuf.Value getTrainingTaskMetadata()

 Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `metadata`. This metadata is an auxiliary runtime and final information
 about the training task. While the pipeline is running this information is
 populated only at a best effort basis. Only present if the
 pipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
 

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

Returns:

The trainingTaskMetadata.

getTrainingTaskMetadataOrBuilder

com.google.protobuf.ValueOrBuilder getTrainingTaskMetadataOrBuilder()

 Output only. The metadata information as specified in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]'s
 `metadata`. This metadata is an auxiliary runtime and final information
 about the training task. While the pipeline is running this information is
 populated only at a best effort basis. Only present if the
 pipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 contains `metadata` object.
 

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

hasModelToUpload

boolean hasModelToUpload()

 Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this Model description should be populated, and
 if there are any special requirements regarding how it should be filled. If
 nothing is mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that this field should not be filled and the
 training task either uploads the Model without a need of this information,
 or that training task does not support uploading a Model as part of the
 pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
 the trained Model had been uploaded into Vertex AI, then the
 model_to_upload's resource
 [name][google.cloud.aiplatform.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
 

.google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;

Returns:

Whether the modelToUpload field is set.

getModelToUpload

Model getModelToUpload()

 Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this Model description should be populated, and
 if there are any special requirements regarding how it should be filled. If
 nothing is mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that this field should not be filled and the
 training task either uploads the Model without a need of this information,
 or that training task does not support uploading a Model as part of the
 pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
 the trained Model had been uploaded into Vertex AI, then the
 model_to_upload's resource
 [name][google.cloud.aiplatform.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
 

.google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;

Returns:

The modelToUpload.

getModelToUploadOrBuilder

ModelOrBuilder getModelToUploadOrBuilder()

 Describes the Model that may be uploaded (via
 [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel])
 by this TrainingPipeline. The TrainingPipeline's
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition]
 should make clear whether this Model description should be populated, and
 if there are any special requirements regarding how it should be filled. If
 nothing is mentioned in the
 [training_task_definition][google.cloud.aiplatform.v1beta1.TrainingPipeline.training_task_definition],
 then it should be assumed that this field should not be filled and the
 training task either uploads the Model without a need of this information,
 or that training task does not support uploading a Model as part of the
 pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and
 the trained Model had been uploaded into Vertex AI, then the
 model_to_upload's resource
 [name][google.cloud.aiplatform.v1beta1.Model.name] is populated. The Model
 is always uploaded into the Project and Location in which this pipeline
 is.
 

.google.cloud.aiplatform.v1beta1.Model model_to_upload = 7;

getModelId

String getModelId()

 Optional. The ID to use for the uploaded Model, which will become the final
 component of the model resource name.

 This value may be up to 63 characters, and valid characters are
 `[a-z0-9_-]`. The first character cannot be a number or hyphen.
 

string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The modelId.

getModelIdBytes

com.google.protobuf.ByteString getModelIdBytes()

 Optional. The ID to use for the uploaded Model, which will become the final
 component of the model resource name.

 This value may be up to 63 characters, and valid characters are
 `[a-z0-9_-]`. The first character cannot be a number or hyphen.
 

string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The bytes for modelId.

getParentModel

String getParentModel()

 Optional. When specify this field, the `model_to_upload` will not be
 uploaded as a new model, instead, it will become a new version of this
 `parent_model`.
 

string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The parentModel.

getParentModelBytes

com.google.protobuf.ByteString getParentModelBytes()

 Optional. When specify this field, the `model_to_upload` will not be
 uploaded as a new model, instead, it will become a new version of this
 `parent_model`.
 

string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The bytes for parentModel.

getStateValue

int getStateValue()

 Output only. The detailed state of the pipeline.
 

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

Returns:

The enum numeric value on the wire for state.

getState

PipelineState getState()

 Output only. The detailed state of the pipeline.
 

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

Returns:

The state.

hasError

boolean hasError()

 Output only. Only populated when the pipeline's state is
 `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
 

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the error field is set.

getError

com.google.rpc.Status getError()

 Output only. Only populated when the pipeline's state is
 `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
 

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The error.

getErrorOrBuilder

com.google.rpc.StatusOrBuilder getErrorOrBuilder()

 Output only. Only populated when the pipeline's state is
 `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
 

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

hasCreateTime

boolean hasCreateTime()

 Output only. Time when the TrainingPipeline was created.
 

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

Returns:

Whether the createTime field is set.

getCreateTime

com.google.protobuf.Timestamp getCreateTime()

 Output only. Time when the TrainingPipeline was created.
 

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

Returns:

The createTime.

getCreateTimeOrBuilder

com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()

 Output only. Time when the TrainingPipeline was created.
 

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

hasStartTime

boolean hasStartTime()

 Output only. Time when the TrainingPipeline for the first time entered the
 `PIPELINE_STATE_RUNNING` state.
 

.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the startTime field is set.

getStartTime

com.google.protobuf.Timestamp getStartTime()

 Output only. Time when the TrainingPipeline for the first time entered the
 `PIPELINE_STATE_RUNNING` state.
 

.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The startTime.

getStartTimeOrBuilder

com.google.protobuf.TimestampOrBuilder getStartTimeOrBuilder()

 Output only. Time when the TrainingPipeline for the first time entered the
 `PIPELINE_STATE_RUNNING` state.
 

.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

hasEndTime

boolean hasEndTime()

 Output only. Time when the TrainingPipeline entered any of the following
 states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
 `PIPELINE_STATE_CANCELLED`.
 

.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the endTime field is set.

getEndTime

com.google.protobuf.Timestamp getEndTime()

 Output only. Time when the TrainingPipeline entered any of the following
 states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
 `PIPELINE_STATE_CANCELLED`.
 

.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The endTime.

getEndTimeOrBuilder

com.google.protobuf.TimestampOrBuilder getEndTimeOrBuilder()

 Output only. Time when the TrainingPipeline entered any of the following
 states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`,
 `PIPELINE_STATE_CANCELLED`.
 

.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

hasUpdateTime

boolean hasUpdateTime()

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

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

Returns:

Whether the updateTime field is set.

getUpdateTime

com.google.protobuf.Timestamp getUpdateTime()

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

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

Returns:

The updateTime.

getUpdateTimeOrBuilder

com.google.protobuf.TimestampOrBuilder getUpdateTimeOrBuilder()

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

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

getLabelsCount

int getLabelsCount()

 The labels with user-defined metadata to organize TrainingPipelines.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
 

map<string, string> labels = 15;

containsLabels

boolean containsLabels(String key)

 The labels with user-defined metadata to organize TrainingPipelines.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
 

map<string, string> labels = 15;

getLabels

@Deprecated
Map<String,String> getLabels()

Deprecated.

Use getLabelsMap() instead.

getLabelsMap

Map<String,String> getLabelsMap()

 The labels with user-defined metadata to organize TrainingPipelines.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
 

map<string, string> labels = 15;

getLabelsOrDefault

String getLabelsOrDefault(String key,
                          String defaultValue)

 The labels with user-defined metadata to organize TrainingPipelines.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
 

map<string, string> labels = 15;

getLabelsOrThrow

String getLabelsOrThrow(String key)

 The labels with user-defined metadata to organize TrainingPipelines.

 Label keys and values can be no longer than 64 characters
 (Unicode codepoints), can only contain lowercase letters, numeric
 characters, underscores and dashes. International characters are allowed.

 See https://goo.gl/xmQnxf for more information and examples of labels.
 

map<string, string> labels = 15;

hasEncryptionSpec

boolean hasEncryptionSpec()

 Customer-managed encryption key spec for a TrainingPipeline. If set, this
 TrainingPipeline will be secured by this key.

 Note: Model trained by this TrainingPipeline is also secured by this key if
 [model_to_upload][google.cloud.aiplatform.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
 

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

Returns:

Whether the encryptionSpec field is set.

getEncryptionSpec

EncryptionSpec getEncryptionSpec()

 Customer-managed encryption key spec for a TrainingPipeline. If set, this
 TrainingPipeline will be secured by this key.

 Note: Model trained by this TrainingPipeline is also secured by this key if
 [model_to_upload][google.cloud.aiplatform.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
 

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

Returns:

The encryptionSpec.

getEncryptionSpecOrBuilder

EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()

 Customer-managed encryption key spec for a TrainingPipeline. If set, this
 TrainingPipeline will be secured by this key.

 Note: Model trained by this TrainingPipeline is also secured by this key if
 [model_to_upload][google.cloud.aiplatform.v1beta1.TrainingPipeline.encryption_spec]
 is not set separately.
 

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