scala.googleapis.bigquery.MlStatistics.scala Maven / Gradle / Ivy

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googleapis-http4s-bigquery

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package googleapis.bigquery

import io.circe._
import io.circe.syntax._

final case class MlStatistics(
    /** Output only. Trials of a [hyperparameter tuning job](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id.
      */
    hparamTrials: Option[List[HparamTuningTrial]] = None,
    /** Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
      */
    maxIterations: Option[Long] = None,
    /** Output only. The type of the model that is being trained.
      */
    modelType: Option[MlStatisticsModelType] = None,
    /** Output only. Training type of the job.
      */
    trainingType: Option[MlStatisticsTrainingType] = None,
    /** Results for all completed iterations. Empty for [hyperparameter tuning jobs](https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview).
      */
    iterationResults: Option[List[IterationResult]] = None,
)
object MlStatistics {
  implicit val encoder: Encoder[MlStatistics] = Encoder.instance { x =>
    Json.obj(
      "hparamTrials" := x.hparamTrials,
      "maxIterations" := x.maxIterations,
      "modelType" := x.modelType,
      "trainingType" := x.trainingType,
      "iterationResults" := x.iterationResults,
    )
  }
  implicit val decoder: Decoder[MlStatistics] = Decoder.instance { c =>
    for {
      v0 <- c.get[Option[List[HparamTuningTrial]]]("hparamTrials")
      v1 <- c.get[Option[Long]]("maxIterations")
      v2 <- c.get[Option[MlStatisticsModelType]]("modelType")
      v3 <- c.get[Option[MlStatisticsTrainingType]]("trainingType")
      v4 <- c.get[Option[List[IterationResult]]]("iterationResults")
    } yield MlStatistics(v0, v1, v2, v3, v4)
  }
}