Package com.google.cloud.aiplatform.v1
Class TrainingPipeline.Builder
java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
com.google.cloud.aiplatform.v1.TrainingPipeline.Builder
- All Implemented Interfaces:
TrainingPipelineOrBuilder,com.google.protobuf.Message.Builder,com.google.protobuf.MessageLite.Builder,com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder,Cloneable
- Enclosing class:
- TrainingPipeline
public static final class TrainingPipeline.Builder
extends com.google.protobuf.GeneratedMessage.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][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.Protobuf type
google.cloud.aiplatform.v1.TrainingPipeline-
Method Summary
Modifier and TypeMethodDescriptionbuild()clear()Output only.Required.Customer-managed encryption key spec for a TrainingPipeline.Output only.Output only.Specifies Vertex AI owned input data that may be used for training the Model.Optional.Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.Output only.Optional.Output only.Output only.Required.Required.Output only.Output only.booleancontainsLabels(String key) The labels with user-defined metadata to organize TrainingPipelines.com.google.protobuf.TimestampOutput only.com.google.protobuf.Timestamp.BuilderOutput only.com.google.protobuf.TimestampOrBuilderOutput only.static final com.google.protobuf.Descriptors.Descriptorcom.google.protobuf.Descriptors.DescriptorRequired.com.google.protobuf.ByteStringRequired.Customer-managed encryption key spec for a TrainingPipeline.Customer-managed encryption key spec for a TrainingPipeline.Customer-managed encryption key spec for a TrainingPipeline.com.google.protobuf.TimestampOutput only.com.google.protobuf.Timestamp.BuilderOutput only.com.google.protobuf.TimestampOrBuilderOutput only.getError()Output only.Output only.Output only.Specifies Vertex AI owned input data that may be used for training the Model.Specifies Vertex AI owned input data that may be used for training the Model.Specifies Vertex AI owned input data that may be used for training the Model.Deprecated.intThe labels with user-defined metadata to organize TrainingPipelines.The labels with user-defined metadata to organize TrainingPipelines.getLabelsOrDefault(String key, String defaultValue) The labels with user-defined metadata to organize TrainingPipelines.getLabelsOrThrow(String key) The labels with user-defined metadata to organize TrainingPipelines.Optional.com.google.protobuf.ByteStringOptional.Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.Deprecated.getName()Output only.com.google.protobuf.ByteStringOutput only.Optional.com.google.protobuf.ByteStringOptional.com.google.protobuf.TimestampOutput only.com.google.protobuf.Timestamp.BuilderOutput only.com.google.protobuf.TimestampOrBuilderOutput only.getState()Output only.intOutput only.Required.com.google.protobuf.ByteStringRequired.com.google.protobuf.ValueRequired.com.google.protobuf.Value.BuilderRequired.com.google.protobuf.ValueOrBuilderRequired.com.google.protobuf.ValueOutput only.com.google.protobuf.Value.BuilderOutput only.com.google.protobuf.ValueOrBuilderOutput only.com.google.protobuf.TimestampOutput only.com.google.protobuf.Timestamp.BuilderOutput only.com.google.protobuf.TimestampOrBuilderOutput only.booleanOutput only.booleanCustomer-managed encryption key spec for a TrainingPipeline.booleanOutput only.booleanhasError()Output only.booleanSpecifies Vertex AI owned input data that may be used for training the Model.booleanDescribes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.booleanOutput only.booleanRequired.booleanOutput only.booleanOutput only.protected com.google.protobuf.GeneratedMessage.FieldAccessorTableprotected com.google.protobuf.MapFieldReflectionAccessorinternalGetMapFieldReflection(int number) protected com.google.protobuf.MapFieldReflectionAccessorinternalGetMutableMapFieldReflection(int number) final booleanmergeCreateTime(com.google.protobuf.Timestamp value) Output only.Customer-managed encryption key spec for a TrainingPipeline.mergeEndTime(com.google.protobuf.Timestamp value) Output only.mergeError(Status value) Output only.mergeFrom(TrainingPipeline other) mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) mergeFrom(com.google.protobuf.Message other) Specifies Vertex AI owned input data that may be used for training the Model.mergeModelToUpload(Model value) Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.mergeStartTime(com.google.protobuf.Timestamp value) Output only.mergeTrainingTaskInputs(com.google.protobuf.Value value) Required.mergeTrainingTaskMetadata(com.google.protobuf.Value value) Output only.mergeUpdateTime(com.google.protobuf.Timestamp value) Output only.putAllLabels(Map<String, String> values) The labels with user-defined metadata to organize TrainingPipelines.The labels with user-defined metadata to organize TrainingPipelines.removeLabels(String key) The labels with user-defined metadata to organize TrainingPipelines.setCreateTime(com.google.protobuf.Timestamp value) Output only.setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only.setDisplayName(String value) Required.setDisplayNameBytes(com.google.protobuf.ByteString value) Required.setEncryptionSpec(EncryptionSpec value) Customer-managed encryption key spec for a TrainingPipeline.setEncryptionSpec(EncryptionSpec.Builder builderForValue) Customer-managed encryption key spec for a TrainingPipeline.setEndTime(com.google.protobuf.Timestamp value) Output only.setEndTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only.Output only.setError(Status.Builder builderForValue) Output only.Specifies Vertex AI owned input data that may be used for training the Model.setInputDataConfig(InputDataConfig.Builder builderForValue) Specifies Vertex AI owned input data that may be used for training the Model.setModelId(String value) Optional.setModelIdBytes(com.google.protobuf.ByteString value) Optional.setModelToUpload(Model value) Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.setModelToUpload(Model.Builder builderForValue) Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline.Output only.setNameBytes(com.google.protobuf.ByteString value) Output only.setParentModel(String value) Optional.setParentModelBytes(com.google.protobuf.ByteString value) Optional.setStartTime(com.google.protobuf.Timestamp value) Output only.setStartTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only.setState(PipelineState value) Output only.setStateValue(int value) Output only.setTrainingTaskDefinition(String value) Required.setTrainingTaskDefinitionBytes(com.google.protobuf.ByteString value) Required.setTrainingTaskInputs(com.google.protobuf.Value value) Required.setTrainingTaskInputs(com.google.protobuf.Value.Builder builderForValue) Required.setTrainingTaskMetadata(com.google.protobuf.Value value) Output only.setTrainingTaskMetadata(com.google.protobuf.Value.Builder builderForValue) Output only.setUpdateTime(com.google.protobuf.Timestamp value) Output only.setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only.Methods inherited from class com.google.protobuf.GeneratedMessage.Builder
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageExceptionMethods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.Message.Builder
mergeDelimitedFrom, mergeDelimitedFromMethods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFromMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetMapFieldReflection
protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number) - Overrides:
internalGetMapFieldReflectionin classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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internalGetMutableMapFieldReflection
protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number) - Overrides:
internalGetMutableMapFieldReflectionin classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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clear
- Specified by:
clearin interfacecom.google.protobuf.Message.Builder- Specified by:
clearin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clearin classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
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build
- Specified by:
buildin interfacecom.google.protobuf.Message.Builder- Specified by:
buildin interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
- Specified by:
buildPartialin interfacecom.google.protobuf.Message.Builder- Specified by:
buildPartialin interfacecom.google.protobuf.MessageLite.Builder
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mergeFrom
- Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<TrainingPipeline.Builder>
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mergeFrom
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessage.Builder<TrainingPipeline.Builder>
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mergeFrom
public TrainingPipeline.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Specified by:
mergeFromin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<TrainingPipeline.Builder>- Throws:
IOException
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getName
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getNamein interfaceTrainingPipelineOrBuilder- Returns:
- The name.
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getNameBytes
public com.google.protobuf.ByteString getNameBytes()Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getNameBytesin interfaceTrainingPipelineOrBuilder- Returns:
- The bytes for name.
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setName
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The name to set.- Returns:
- This builder for chaining.
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clearName
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];- Returns:
- This builder for chaining.
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setNameBytes
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The bytes for name to set.- Returns:
- This builder for chaining.
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getDisplayName
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];- Specified by:
getDisplayNamein interfaceTrainingPipelineOrBuilder- Returns:
- The displayName.
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getDisplayNameBytes
public com.google.protobuf.ByteString getDisplayNameBytes()Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];- Specified by:
getDisplayNameBytesin interfaceTrainingPipelineOrBuilder- Returns:
- The bytes for displayName.
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setDisplayName
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];- Parameters:
value- The displayName to set.- Returns:
- This builder for chaining.
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clearDisplayName
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];- Returns:
- This builder for chaining.
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setDisplayNameBytes
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];- Parameters:
value- The bytes for displayName to set.- Returns:
- This builder for chaining.
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hasInputDataConfig
public 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.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;- Specified by:
hasInputDataConfigin interfaceTrainingPipelineOrBuilder- Returns:
- Whether the inputDataConfig field is set.
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getInputDataConfig
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;- Specified by:
getInputDataConfigin interfaceTrainingPipelineOrBuilder- Returns:
- The inputDataConfig.
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setInputDataConfig
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3; -
setInputDataConfig
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3; -
mergeInputDataConfig
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3; -
clearInputDataConfig
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3; -
getInputDataConfigBuilder
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3; -
getInputDataConfigOrBuilder
Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition], then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;- Specified by:
getInputDataConfigOrBuilderin interfaceTrainingPipelineOrBuilder
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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];- Specified by:
getTrainingTaskDefinitionin interfaceTrainingPipelineOrBuilder- Returns:
- The trainingTaskDefinition.
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getTrainingTaskDefinitionBytes
public 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];- Specified by:
getTrainingTaskDefinitionBytesin interfaceTrainingPipelineOrBuilder- Returns:
- The bytes for trainingTaskDefinition.
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setTrainingTaskDefinition
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];- Parameters:
value- The trainingTaskDefinition to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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setTrainingTaskDefinitionBytes
public TrainingPipeline.Builder setTrainingTaskDefinitionBytes(com.google.protobuf.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];- Parameters:
value- The bytes for trainingTaskDefinition to set.- Returns:
- This builder for chaining.
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hasTrainingTaskInputs
public boolean hasTrainingTaskInputs()Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];- Specified by:
hasTrainingTaskInputsin interfaceTrainingPipelineOrBuilder- Returns:
- Whether the trainingTaskInputs field is set.
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getTrainingTaskInputs
public com.google.protobuf.Value getTrainingTaskInputs()Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];- Specified by:
getTrainingTaskInputsin interfaceTrainingPipelineOrBuilder- Returns:
- The trainingTaskInputs.
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setTrainingTaskInputs
Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED]; -
setTrainingTaskInputs
public TrainingPipeline.Builder setTrainingTaskInputs(com.google.protobuf.Value.Builder builderForValue) Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED]; -
mergeTrainingTaskInputs
Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED]; -
clearTrainingTaskInputs
Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED]; -
getTrainingTaskInputsBuilder
public com.google.protobuf.Value.Builder getTrainingTaskInputsBuilder()Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED]; -
getTrainingTaskInputsOrBuilder
public com.google.protobuf.ValueOrBuilder getTrainingTaskInputsOrBuilder()Required. The training task's parameter(s), as specified in the [training_task_definition][google.cloud.aiplatform.v1.TrainingPipeline.training_task_definition]'s `inputs`.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];- Specified by:
getTrainingTaskInputsOrBuilderin interfaceTrainingPipelineOrBuilder
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hasTrainingTaskMetadata
public boolean hasTrainingTaskMetadata()Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
hasTrainingTaskMetadatain interfaceTrainingPipelineOrBuilder- Returns:
- Whether the trainingTaskMetadata field is set.
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getTrainingTaskMetadata
public com.google.protobuf.Value getTrainingTaskMetadata()Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getTrainingTaskMetadatain interfaceTrainingPipelineOrBuilder- Returns:
- The trainingTaskMetadata.
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setTrainingTaskMetadata
Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setTrainingTaskMetadata
public TrainingPipeline.Builder setTrainingTaskMetadata(com.google.protobuf.Value.Builder builderForValue) Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
mergeTrainingTaskMetadata
Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
clearTrainingTaskMetadata
Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getTrainingTaskMetadataBuilder
public com.google.protobuf.Value.Builder getTrainingTaskMetadataBuilder()Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getTrainingTaskMetadataOrBuilder
public com.google.protobuf.ValueOrBuilder getTrainingTaskMetadataOrBuilder()Output only. The metadata information as specified in the [training_task_definition][google.cloud.aiplatform.v1.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.v1.TrainingPipeline.training_task_definition] contains `metadata` object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getTrainingTaskMetadataOrBuilderin interfaceTrainingPipelineOrBuilder
-
hasModelToUpload
public boolean hasModelToUpload()Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;- Specified by:
hasModelToUploadin interfaceTrainingPipelineOrBuilder- Returns:
- Whether the modelToUpload field is set.
-
getModelToUpload
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;- Specified by:
getModelToUploadin interfaceTrainingPipelineOrBuilder- Returns:
- The modelToUpload.
-
setModelToUpload
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7; -
setModelToUpload
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7; -
mergeModelToUpload
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7; -
clearModelToUpload
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7; -
getModelToUploadBuilder
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7; -
getModelToUploadOrBuilder
Describes the Model that may be uploaded (via [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel]) by this TrainingPipeline. The TrainingPipeline's [training_task_definition][google.cloud.aiplatform.v1.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.v1.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.v1.Model.name] is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;- Specified by:
getModelToUploadOrBuilderin interfaceTrainingPipelineOrBuilder
-
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];- Specified by:
getModelIdin interfaceTrainingPipelineOrBuilder- Returns:
- The modelId.
-
getModelIdBytes
public 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];- Specified by:
getModelIdBytesin interfaceTrainingPipelineOrBuilder- Returns:
- The bytes for modelId.
-
setModelId
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];- Parameters:
value- The modelId to set.- Returns:
- This builder for chaining.
-
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:
- This builder for chaining.
-
setModelIdBytes
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];- Parameters:
value- The bytes for modelId to set.- Returns:
- This builder for chaining.
-
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];- Specified by:
getParentModelin interfaceTrainingPipelineOrBuilder- Returns:
- The parentModel.
-
getParentModelBytes
public 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];- Specified by:
getParentModelBytesin interfaceTrainingPipelineOrBuilder- Returns:
- The bytes for parentModel.
-
setParentModel
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];- Parameters:
value- The parentModel to set.- Returns:
- This builder for chaining.
-
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:
- This builder for chaining.
-
setParentModelBytes
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];- Parameters:
value- The bytes for parentModel to set.- Returns:
- This builder for chaining.
-
getStateValue
public int getStateValue()Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getStateValuein interfaceTrainingPipelineOrBuilder- Returns:
- The enum numeric value on the wire for state.
-
setStateValue
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The enum numeric value on the wire for state to set.- Returns:
- This builder for chaining.
-
getState
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getStatein interfaceTrainingPipelineOrBuilder- Returns:
- The state.
-
setState
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The state to set.- Returns:
- This builder for chaining.
-
clearState
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];- Returns:
- This builder for chaining.
-
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];- Specified by:
hasErrorin interfaceTrainingPipelineOrBuilder- Returns:
- Whether the error field is set.
-
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];- Specified by:
getErrorin interfaceTrainingPipelineOrBuilder- Returns:
- The error.
-
setError
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]; -
setError
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]; -
mergeError
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]; -
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]; -
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]; -
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];- Specified by:
getErrorOrBuilderin interfaceTrainingPipelineOrBuilder
-
hasCreateTime
public boolean hasCreateTime()Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
hasCreateTimein interfaceTrainingPipelineOrBuilder- Returns:
- Whether the createTime field is set.
-
getCreateTime
public 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];- Specified by:
getCreateTimein interfaceTrainingPipelineOrBuilder- Returns:
- The createTime.
-
setCreateTime
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setCreateTime
public TrainingPipeline.Builder setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
mergeCreateTime
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
clearCreateTime
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getCreateTimeBuilder
public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getCreateTimeOrBuilder
public 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];- Specified by:
getCreateTimeOrBuilderin interfaceTrainingPipelineOrBuilder
-
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];- Specified by:
hasStartTimein interfaceTrainingPipelineOrBuilder- Returns:
- Whether the startTime field is set.
-
getStartTime
public 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];- Specified by:
getStartTimein interfaceTrainingPipelineOrBuilder- Returns:
- The startTime.
-
setStartTime
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]; -
setStartTime
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]; -
mergeStartTime
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]; -
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]; -
getStartTimeBuilder
public com.google.protobuf.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]; -
getStartTimeOrBuilder
public 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];- Specified by:
getStartTimeOrBuilderin interfaceTrainingPipelineOrBuilder
-
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];- Specified by:
hasEndTimein interfaceTrainingPipelineOrBuilder- Returns:
- Whether the endTime field is set.
-
getEndTime
public 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];- Specified by:
getEndTimein interfaceTrainingPipelineOrBuilder- Returns:
- The endTime.
-
setEndTime
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]; -
setEndTime
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]; -
mergeEndTime
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]; -
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]; -
getEndTimeBuilder
public com.google.protobuf.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]; -
getEndTimeOrBuilder
public 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];- Specified by:
getEndTimeOrBuilderin interfaceTrainingPipelineOrBuilder
-
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];- Specified by:
hasUpdateTimein interfaceTrainingPipelineOrBuilder- Returns:
- Whether the updateTime field is set.
-
getUpdateTime
public 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];- Specified by:
getUpdateTimein interfaceTrainingPipelineOrBuilder- Returns:
- The updateTime.
-
setUpdateTime
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setUpdateTime
public TrainingPipeline.Builder setUpdateTime(com.google.protobuf.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]; -
mergeUpdateTime
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
clearUpdateTime
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getUpdateTimeBuilder
public com.google.protobuf.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]; -
getUpdateTimeOrBuilder
public 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];- Specified by:
getUpdateTimeOrBuilderin interfaceTrainingPipelineOrBuilder
-
getLabelsCount
public int getLabelsCount()Description copied from interface:TrainingPipelineOrBuilderThe 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;- Specified by:
getLabelsCountin interfaceTrainingPipelineOrBuilder
-
containsLabels
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;- Specified by:
containsLabelsin interfaceTrainingPipelineOrBuilder
-
getLabels
Deprecated.UsegetLabelsMap()instead.- Specified by:
getLabelsin interfaceTrainingPipelineOrBuilder
-
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;- Specified by:
getLabelsMapin interfaceTrainingPipelineOrBuilder
-
getLabelsOrDefault
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;- Specified by:
getLabelsOrDefaultin interfaceTrainingPipelineOrBuilder
-
getLabelsOrThrow
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;- Specified by:
getLabelsOrThrowin interfaceTrainingPipelineOrBuilder
-
clearLabels
-
removeLabels
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; -
getMutableLabels
Deprecated.Use alternate mutation accessors instead. -
putLabels
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; -
putAllLabels
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
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][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;- Specified by:
hasEncryptionSpecin interfaceTrainingPipelineOrBuilder- Returns:
- Whether the encryptionSpec field is set.
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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.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;- Specified by:
getEncryptionSpecin interfaceTrainingPipelineOrBuilder- Returns:
- The encryptionSpec.
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setEncryptionSpec
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.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18; -
setEncryptionSpec
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.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18; -
mergeEncryptionSpec
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.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18; -
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][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18; -
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][google.cloud.aiplatform.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18; -
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.v1.TrainingPipeline.encryption_spec] is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;- Specified by:
getEncryptionSpecOrBuilderin interfaceTrainingPipelineOrBuilder
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