Google Cloud Ai Platform V1 Client - Class TrainingPipeline (1.13.1)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class TrainingPipeline.

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.

Generated from protobuf message google.cloud.aiplatform.v1.TrainingPipeline

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name Description
data array

Optional. Data for populating the Message object.
↳ name string

Output only. Resource name of the TrainingPipeline.
↳ display_name string

Required. The user-defined name of this TrainingPipeline.
↳ input_data_config InputDataConfig

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.
↳ training_task_definition string

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.
↳ training_task_inputs Google\Protobuf\Value

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.
↳ training_task_metadata Google\Protobuf\Value

Output only. The metadata information as specified in the training_task_definition's metadata. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains metadata object.
↳ model_to_upload Model

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.
↳ model_id string

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.
↳ parent_model string

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.
↳ state int

Output only. The detailed state of the pipeline.
↳ error Google\Rpc\Status

Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED.
↳ create_time Google\Protobuf\Timestamp

Output only. Time when the TrainingPipeline was created.
↳ start_time Google\Protobuf\Timestamp

Output only. Time when the TrainingPipeline for the first time entered the PIPELINE_STATE_RUNNING state.
↳ end_time Google\Protobuf\Timestamp

Output only. Time when the TrainingPipeline entered any of the following states: PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED, PIPELINE_STATE_CANCELLED.
↳ update_time Google\Protobuf\Timestamp

Output only. Time when the TrainingPipeline was most recently updated.
↳ labels array|Google\Protobuf\Internal\MapField

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.
↳ encryption_spec EncryptionSpec

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.

getName

Output only. Resource name of the TrainingPipeline.

Returns
Type Description
string

setName

Output only. Resource name of the TrainingPipeline.

Parameter
Name Description
var string
Returns
Type Description
$this

getDisplayName

Required. The user-defined name of this TrainingPipeline.

Returns
Type Description
string

setDisplayName

Required. The user-defined name of this TrainingPipeline.

Parameter
Name Description
var string
Returns
Type Description
$this

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.

Returns
Type Description
InputDataConfig|null

hasInputDataConfig

clearInputDataConfig

setInputDataConfig

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.

Parameter
Name Description
var InputDataConfig
Returns
Type Description
$this

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.

Returns
Type Description
string

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.

Parameter
Name Description
var string
Returns
Type Description
$this

getTrainingTaskInputs

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.

Returns
Type Description
Google\Protobuf\Value|null

hasTrainingTaskInputs

clearTrainingTaskInputs

setTrainingTaskInputs

Required. The training task's parameter(s), as specified in the training_task_definition's inputs.

Parameter
Name Description
var Google\Protobuf\Value
Returns
Type Description
$this

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.

Returns
Type Description
Google\Protobuf\Value|null

hasTrainingTaskMetadata

clearTrainingTaskMetadata

setTrainingTaskMetadata

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.

Parameter
Name Description
var Google\Protobuf\Value
Returns
Type Description
$this

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.

Returns
Type Description
Model|null

hasModelToUpload

clearModelToUpload

setModelToUpload

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.

Parameter
Name Description
var Model
Returns
Type Description
$this

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.

Returns
Type Description
string

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.

Parameter
Name Description
var string
Returns
Type Description
$this

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.

Returns
Type Description
string

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.

Parameter
Name Description
var string
Returns
Type Description
$this

getState

Output only. The detailed state of the pipeline.

Returns
Type Description
int

setState

Output only. The detailed state of the pipeline.

Parameter
Name Description
var int
Returns
Type Description
$this

getError

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

Returns
Type Description
Google\Rpc\Status|null

hasError

clearError

setError

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

Parameter
Name Description
var Google\Rpc\Status
Returns
Type Description
$this

getCreateTime

Output only. Time when the TrainingPipeline was created.

Returns
Type Description
Google\Protobuf\Timestamp|null

hasCreateTime

clearCreateTime

setCreateTime

Output only. Time when the TrainingPipeline was created.

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getStartTime

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

Returns
Type Description
Google\Protobuf\Timestamp|null

hasStartTime

clearStartTime

setStartTime

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

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getEndTime

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

Returns
Type Description
Google\Protobuf\Timestamp|null

hasEndTime

clearEndTime

setEndTime

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

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getUpdateTime

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

Returns
Type Description
Google\Protobuf\Timestamp|null

hasUpdateTime

clearUpdateTime

setUpdateTime

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

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getLabels

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.

Returns
Type Description
Google\Protobuf\Internal\MapField

setLabels

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.

Parameter
Name Description
var array|Google\Protobuf\Internal\MapField
Returns
Type Description
$this

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.

Returns
Type Description
EncryptionSpec|null

hasEncryptionSpec

clearEncryptionSpec

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 is not set separately.

Parameter
Name Description
var EncryptionSpec
Returns
Type Description
$this