public final class TrainingPipeline extends GeneratedMessageV3 implements TrainingPipelineOrBuilder
The TrainingPipeline orchestrates tasks associated with training a Model. It
always executes the training task, and optionally may also
export data from Vertex AI's Dataset which becomes the training input,
upload the Model to Vertex AI, and evaluate the
Model.
Protobuf type google.cloud.aiplatform.v1.TrainingPipeline
Static Fields
public static final int CREATE_TIME_FIELD_NUMBER
Field Value
public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
public static final int ENCRYPTION_SPEC_FIELD_NUMBER
Field Value
public static final int END_TIME_FIELD_NUMBER
Field Value
public static final int ERROR_FIELD_NUMBER
Field Value
public static final int INPUT_DATA_CONFIG_FIELD_NUMBER
Field Value
public static final int LABELS_FIELD_NUMBER
Field Value
public static final int MODEL_TO_UPLOAD_FIELD_NUMBER
Field Value
public static final int NAME_FIELD_NUMBER
Field Value
public static final int START_TIME_FIELD_NUMBER
Field Value
public static final int STATE_FIELD_NUMBER
Field Value
public static final int TRAINING_TASK_DEFINITION_FIELD_NUMBER
Field Value
public static final int TRAINING_TASK_INPUTS_FIELD_NUMBER
Field Value
public static final int TRAINING_TASK_METADATA_FIELD_NUMBER
Field Value
public static final int UPDATE_TIME_FIELD_NUMBER
Field Value
Static Methods
public static TrainingPipeline getDefaultInstance()
Returns
public static final Descriptors.Descriptor getDescriptor()
Returns
public static TrainingPipeline.Builder newBuilder()
Returns
public static TrainingPipeline.Builder newBuilder(TrainingPipeline prototype)
Parameter
Returns
public static TrainingPipeline parseDelimitedFrom(InputStream input)
Parameter
Returns
Exceptions
public static TrainingPipeline parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static TrainingPipeline parseFrom(byte[] data)
Parameter
| Name | Description |
| data | byte[]
|
Returns
Exceptions
public static TrainingPipeline parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static TrainingPipeline parseFrom(ByteString data)
Parameter
Returns
Exceptions
public static TrainingPipeline parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static TrainingPipeline parseFrom(CodedInputStream input)
Parameter
Returns
Exceptions
public static TrainingPipeline parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static TrainingPipeline parseFrom(InputStream input)
Parameter
Returns
Exceptions
public static TrainingPipeline parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
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Exceptions
public static TrainingPipeline parseFrom(ByteBuffer data)
Parameter
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Exceptions
public static TrainingPipeline parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Returns
Exceptions
public static Parser<TrainingPipeline> parser()
Returns
Methods
public boolean containsLabels(String key)
The labels with user-defined metadata to organize TrainingPipelines.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
public boolean equals(Object obj)
Parameter
Returns
Overrides
public Timestamp getCreateTime()
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TimestampOrBuilder getCreateTimeOrBuilder()
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TrainingPipeline getDefaultInstanceForType()
Returns
public String getDisplayName()
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| String | The displayName.
|
public ByteString getDisplayNameBytes()
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| ByteString | The bytes for displayName.
|
public EncryptionSpec getEncryptionSpec()
Customer-managed encryption key spec for a TrainingPipeline. If set, this
TrainingPipeline will be secured by this key.
Note: Model trained by this TrainingPipeline is also secured by this key if
model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
Customer-managed encryption key spec for a TrainingPipeline. If set, this
TrainingPipeline will be secured by this key.
Note: Model trained by this TrainingPipeline is also secured by this key if
model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
public Timestamp getEndTime()
Output only. Time when the TrainingPipeline entered any of the following states:
PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED,
PIPELINE_STATE_CANCELLED.
.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TimestampOrBuilder getEndTimeOrBuilder()
Output only. Time when the TrainingPipeline entered any of the following states:
PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED,
PIPELINE_STATE_CANCELLED.
.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
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];
| Type | Description |
| com.google.rpc.Status | The error.
|
public StatusOrBuilder getErrorOrBuilder()
Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED or
PIPELINE_STATE_CANCELLED.
.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| com.google.rpc.StatusOrBuilder | |
public InputDataConfig getInputDataConfig()
Specifies Vertex AI owned input data that may be used for training the
Model. The TrainingPipeline's training_task_definition should make
clear whether this config is used and if there are any special requirements
on how it should be filled. If nothing about this config is mentioned in
the training_task_definition, then it should be assumed that the
TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
public InputDataConfigOrBuilder getInputDataConfigOrBuilder()
Specifies Vertex AI owned input data that may be used for training the
Model. The TrainingPipeline's training_task_definition should make
clear whether this config is used and if there are any special requirements
on how it should be filled. If nothing about this config is mentioned in
the training_task_definition, then it should be assumed that the
TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
public Map<String,String> getLabels()
Returns
public int getLabelsCount()
The labels with user-defined metadata to organize TrainingPipelines.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
public Map<String,String> getLabelsMap()
The labels with user-defined metadata to organize TrainingPipelines.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
public String getLabelsOrDefault(String key, String defaultValue)
The labels with user-defined metadata to organize TrainingPipelines.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
public String getLabelsOrThrow(String key)
The labels with user-defined metadata to organize TrainingPipelines.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
public Model getModelToUpload()
Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
| Type | Description |
| Model | The modelToUpload.
|
public ModelOrBuilder getModelToUploadOrBuilder()
Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| String | The name.
|
public ByteString getNameBytes()
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Parser<TrainingPipeline> getParserForType()
Returns
Overrides
public int getSerializedSize()
Returns
Overrides
public Timestamp getStartTime()
Output only. Time when the TrainingPipeline for the first time entered the
PIPELINE_STATE_RUNNING state.
.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TimestampOrBuilder getStartTimeOrBuilder()
Output only. Time when the TrainingPipeline for the first time entered the
PIPELINE_STATE_RUNNING state.
.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
public PipelineState getState()
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
public int getStateValue()
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| int | The enum numeric value on the wire for state.
|
public String getTrainingTaskDefinition()
Required. A Google Cloud Storage path to the YAML file that defines the training task
which is responsible for producing the model artifact, and may also include
additional auxiliary work.
The definition files that can be used here are found in
gs://google-cloud-aiplatform/schema/trainingjob/definition/.
Note: The URI given on output will be immutable and probably different,
including the URI scheme, than the one given on input. The output URI will
point to a location where the user only has a read access.
string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| String | The trainingTaskDefinition.
|
public ByteString getTrainingTaskDefinitionBytes()
Required. A Google Cloud Storage path to the YAML file that defines the training task
which is responsible for producing the model artifact, and may also include
additional auxiliary work.
The definition files that can be used here are found in
gs://google-cloud-aiplatform/schema/trainingjob/definition/.
Note: The URI given on output will be immutable and probably different,
including the URI scheme, than the one given on input. The output URI will
point to a location where the user only has a read access.
string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| ByteString | The bytes for trainingTaskDefinition.
|
public Value getTrainingTaskInputs()
Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| Value | The trainingTaskInputs.
|
public ValueOrBuilder getTrainingTaskInputsOrBuilder()
Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
public Value getTrainingTaskMetadata()
Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Value | The trainingTaskMetadata.
|
public ValueOrBuilder getTrainingTaskMetadataOrBuilder()
Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
public final UnknownFieldSet getUnknownFields()
Returns
Overrides
public Timestamp getUpdateTime()
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public TimestampOrBuilder getUpdateTimeOrBuilder()
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public boolean hasCreateTime()
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the createTime field is set.
|
public boolean hasEncryptionSpec()
Customer-managed encryption key spec for a TrainingPipeline. If set, this
TrainingPipeline will be secured by this key.
Note: Model trained by this TrainingPipeline is also secured by this key if
model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
| Type | Description |
| boolean | Whether the encryptionSpec field is set.
|
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];
| Type | Description |
| boolean | Whether the endTime field is set.
|
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];
| Type | Description |
| boolean | Whether the error field is set.
|
public boolean hasInputDataConfig()
Specifies Vertex AI owned input data that may be used for training the
Model. The TrainingPipeline's training_task_definition should make
clear whether this config is used and if there are any special requirements
on how it should be filled. If nothing about this config is mentioned in
the training_task_definition, then it should be assumed that the
TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
| Type | Description |
| boolean | Whether the inputDataConfig field is set.
|
public boolean hasModelToUpload()
Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
| Type | Description |
| boolean | Whether the modelToUpload field is set.
|
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];
| Type | Description |
| boolean | Whether the startTime field is set.
|
public boolean hasTrainingTaskInputs()
Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| boolean | Whether the trainingTaskInputs field is set.
|
public boolean hasTrainingTaskMetadata()
Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the trainingTaskMetadata field is set.
|
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];
| Type | Description |
| boolean | Whether the updateTime field is set.
|
Returns
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Overrides
protected MapField internalGetMapField(int number)
Parameter
Returns
Overrides
public final boolean isInitialized()
Returns
Overrides
public TrainingPipeline.Builder newBuilderForType()
Returns
protected TrainingPipeline.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Returns
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Returns
Overrides
public TrainingPipeline.Builder toBuilder()
Returns
public void writeTo(CodedOutputStream output)
Parameter
Overrides
Exceptions
