REST Resource: projects.locations.trainingPipelines

Resource: 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.

JSON representation

JSON representation
{ "name": string, "displayName": string, "inputDataConfig": { object (`InputDataConfig`) }, "trainingTaskDefinition": string, "trainingTaskInputs": value, "trainingTaskMetadata": value, "modelToUpload": { object (`Model`) }, "modelId": string, "parentModel": string, "state": enum (`PipelineState`), "error": { object (`Status`) }, "createTime": string, "startTime": string, "endTime": string, "updateTime": string, "labels": { string: string, ... }, "encryptionSpec": { object (`EncryptionSpec`) } }

{
  "name": string,
  "displayName": string,
  "inputDataConfig": {
    object (InputDataConfig)
  },
  "trainingTaskDefinition": string,
  "trainingTaskInputs": value,
  "trainingTaskMetadata": value,
  "modelToUpload": {
    object (Model)
  },
  "modelId": string,
  "parentModel": string,
  "state": enum (PipelineState),
  "error": {
    object (Status)
  },
  "createTime": string,
  "startTime": string,
  "endTime": string,
  "updateTime": string,
  "labels": {
    string: string,
    ...
  },
  "encryptionSpec": {
    object (EncryptionSpec)
  }
}

Fields
`name`	`string` Output only. Resource name of the TrainingPipeline.
`displayName`	`string` Required. The user-defined name of this TrainingPipeline.
`inputDataConfig`	`object (InputDataConfig)` Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's `trainingTaskDefinition` 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 `trainingTaskDefinition`, then it should be assumed that the TrainingPipeline does not depend on this configuration.
`trainingTaskDefinition`	`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.
`trainingTaskInputs`	`value (Value format)` Required. The training task's parameter(s), as specified in the `trainingTaskDefinition`'s `inputs`.
`trainingTaskMetadata`