Google Cloud Ai Platform V1 Client - Class TrainingPipeline (0.20.0)

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`	`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

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

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

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

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.

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`