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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
Namespace
Google \ Cloud \ AIPlatform \ V1Methods
__construct
Constructor.
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
↳ 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
↳ 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.
string
setName
Output only. Resource name of the TrainingPipeline.
var
string
$this
getDisplayName
Required. The user-defined name of this TrainingPipeline.
string
setDisplayName
Required. The user-defined name of this TrainingPipeline.
var
string
$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.
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.
$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.
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.
var
string
$this
getTrainingTaskInputs
Required. The training task's parameter(s), as specified in the training_task_definition
's inputs
.
hasTrainingTaskInputs
clearTrainingTaskInputs
setTrainingTaskInputs
Required. The training task's parameter(s), as specified in the training_task_definition
's inputs
.
$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.
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.
$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.
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.
$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.
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.
var
string
$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
.
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
.
var
string
$this
getState
Output only. The detailed state of the pipeline.
int
setState
Output only. The detailed state of the pipeline.
var
int
$this
getError
Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED
or PIPELINE_STATE_CANCELLED
.
hasError
clearError
setError
Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED
or PIPELINE_STATE_CANCELLED
.
$this
getCreateTime
Output only. Time when the TrainingPipeline was created.
hasCreateTime
clearCreateTime
setCreateTime
Output only. Time when the TrainingPipeline was created.
$this
getStartTime
Output only. Time when the TrainingPipeline for the first time entered the PIPELINE_STATE_RUNNING
state.
hasStartTime
clearStartTime
setStartTime
Output only. Time when the TrainingPipeline for the first time entered the PIPELINE_STATE_RUNNING
state.
$this
getEndTime
Output only. Time when the TrainingPipeline entered any of the following
states: PIPELINE_STATE_SUCCEEDED
, PIPELINE_STATE_FAILED
, PIPELINE_STATE_CANCELLED
.
hasEndTime
clearEndTime
setEndTime
Output only. Time when the TrainingPipeline entered any of the following
states: PIPELINE_STATE_SUCCEEDED
, PIPELINE_STATE_FAILED
, PIPELINE_STATE_CANCELLED
.
$this
getUpdateTime
Output only. Time when the TrainingPipeline was most recently updated.
hasUpdateTime
clearUpdateTime
setUpdateTime
Output only. Time when the TrainingPipeline was most recently updated.
$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.
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.
$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.
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.
$this
