Google Cloud Ai Platform V1 Client - Class TrainingPipeline (0.11.1)

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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

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	Google\Cloud\AIPlatform\V1\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	Google\Cloud\AIPlatform\V1\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	Google\Cloud\AIPlatform\V1\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
Google\Cloud\AIPlatform\V1\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	Google\Cloud\AIPlatform\V1\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
Google\Cloud\AIPlatform\V1\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	Google\Cloud\AIPlatform\V1\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
Google\Cloud\AIPlatform\V1\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	Google\Cloud\AIPlatform\V1\EncryptionSpec

Returns
Type	Description
$this