{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE DuplicateRecordFields #-}
{-# LANGUAGE NamedFieldPuns #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE RecordWildCards #-}
{-# LANGUAGE StrictData #-}
{-# LANGUAGE NoImplicitPrelude #-}
{-# OPTIONS_GHC -fno-warn-unused-imports #-}
{-# OPTIONS_GHC -fno-warn-unused-matches #-}

-- Derived from AWS service descriptions, licensed under Apache 2.0.

-- |
-- Module      : Amazonka.SageMaker.Types.AutoMLJobConfig
-- Copyright   : (c) 2013-2023 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
module Amazonka.SageMaker.Types.AutoMLJobConfig where

import qualified Amazonka.Core as Core
import qualified Amazonka.Core.Lens.Internal as Lens
import qualified Amazonka.Data as Data
import qualified Amazonka.Prelude as Prelude
import Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig
import Amazonka.SageMaker.Types.AutoMLDataSplitConfig
import Amazonka.SageMaker.Types.AutoMLJobCompletionCriteria
import Amazonka.SageMaker.Types.AutoMLMode
import Amazonka.SageMaker.Types.AutoMLSecurityConfig

-- | A collection of settings used for an AutoML job.
--
-- /See:/ 'newAutoMLJobConfig' smart constructor.
data AutoMLJobConfig = AutoMLJobConfig'
  { -- | The configuration for generating a candidate for an AutoML job
    -- (optional).
    AutoMLJobConfig -> Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig :: Prelude.Maybe AutoMLCandidateGenerationConfig,
    -- | How long an AutoML job is allowed to run, or how many candidates a job
    -- is allowed to generate.
    AutoMLJobConfig -> Maybe AutoMLJobCompletionCriteria
completionCriteria :: Prelude.Maybe AutoMLJobCompletionCriteria,
    -- | The configuration for splitting the input training dataset.
    --
    -- Type: AutoMLDataSplitConfig
    AutoMLJobConfig -> Maybe AutoMLDataSplitConfig
dataSplitConfig :: Prelude.Maybe AutoMLDataSplitConfig,
    -- | The method that Autopilot uses to train the data. You can either specify
    -- the mode manually or let Autopilot choose for you based on the dataset
    -- size by selecting @AUTO@. In @AUTO@ mode, Autopilot chooses @ENSEMBLING@
    -- for datasets smaller than 100 MB, and @HYPERPARAMETER_TUNING@ for larger
    -- ones.
    --
    -- The @ENSEMBLING@ mode uses a multi-stack ensemble model to predict
    -- classification and regression tasks directly from your dataset. This
    -- machine learning mode combines several base models to produce an optimal
    -- predictive model. It then uses a stacking ensemble method to combine
    -- predictions from contributing members. A multi-stack ensemble model can
    -- provide better performance over a single model by combining the
    -- predictive capabilities of multiple models. See
    -- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
    -- for a list of algorithms supported by @ENSEMBLING@ mode.
    --
    -- The @HYPERPARAMETER_TUNING@ (HPO) mode uses the best hyperparameters to
    -- train the best version of a model. HPO will automatically select an
    -- algorithm for the type of problem you want to solve. Then HPO finds the
    -- best hyperparameters according to your objective metric. See
    -- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
    -- for a list of algorithms supported by @HYPERPARAMETER_TUNING@ mode.
    AutoMLJobConfig -> Maybe AutoMLMode
mode :: Prelude.Maybe AutoMLMode,
    -- | The security configuration for traffic encryption or Amazon VPC
    -- settings.
    AutoMLJobConfig -> Maybe AutoMLSecurityConfig
securityConfig :: Prelude.Maybe AutoMLSecurityConfig
  }
  deriving (AutoMLJobConfig -> AutoMLJobConfig -> Bool
forall a. (a -> a -> Bool) -> (a -> a -> Bool) -> Eq a
/= :: AutoMLJobConfig -> AutoMLJobConfig -> Bool
$c/= :: AutoMLJobConfig -> AutoMLJobConfig -> Bool
== :: AutoMLJobConfig -> AutoMLJobConfig -> Bool
$c== :: AutoMLJobConfig -> AutoMLJobConfig -> Bool
Prelude.Eq, ReadPrec [AutoMLJobConfig]
ReadPrec AutoMLJobConfig
Int -> ReadS AutoMLJobConfig
ReadS [AutoMLJobConfig]
forall a.
(Int -> ReadS a)
-> ReadS [a] -> ReadPrec a -> ReadPrec [a] -> Read a
readListPrec :: ReadPrec [AutoMLJobConfig]
$creadListPrec :: ReadPrec [AutoMLJobConfig]
readPrec :: ReadPrec AutoMLJobConfig
$creadPrec :: ReadPrec AutoMLJobConfig
readList :: ReadS [AutoMLJobConfig]
$creadList :: ReadS [AutoMLJobConfig]
readsPrec :: Int -> ReadS AutoMLJobConfig
$creadsPrec :: Int -> ReadS AutoMLJobConfig
Prelude.Read, Int -> AutoMLJobConfig -> ShowS
[AutoMLJobConfig] -> ShowS
AutoMLJobConfig -> String
forall a.
(Int -> a -> ShowS) -> (a -> String) -> ([a] -> ShowS) -> Show a
showList :: [AutoMLJobConfig] -> ShowS
$cshowList :: [AutoMLJobConfig] -> ShowS
show :: AutoMLJobConfig -> String
$cshow :: AutoMLJobConfig -> String
showsPrec :: Int -> AutoMLJobConfig -> ShowS
$cshowsPrec :: Int -> AutoMLJobConfig -> ShowS
Prelude.Show, forall x. Rep AutoMLJobConfig x -> AutoMLJobConfig
forall x. AutoMLJobConfig -> Rep AutoMLJobConfig x
forall a.
(forall x. a -> Rep a x) -> (forall x. Rep a x -> a) -> Generic a
$cto :: forall x. Rep AutoMLJobConfig x -> AutoMLJobConfig
$cfrom :: forall x. AutoMLJobConfig -> Rep AutoMLJobConfig x
Prelude.Generic)

-- |
-- Create a value of 'AutoMLJobConfig' with all optional fields omitted.
--
-- Use <https://hackage.haskell.org/package/generic-lens generic-lens> or <https://hackage.haskell.org/package/optics optics> to modify other optional fields.
--
-- The following record fields are available, with the corresponding lenses provided
-- for backwards compatibility:
--
-- 'candidateGenerationConfig', 'autoMLJobConfig_candidateGenerationConfig' - The configuration for generating a candidate for an AutoML job
-- (optional).
--
-- 'completionCriteria', 'autoMLJobConfig_completionCriteria' - How long an AutoML job is allowed to run, or how many candidates a job
-- is allowed to generate.
--
-- 'dataSplitConfig', 'autoMLJobConfig_dataSplitConfig' - The configuration for splitting the input training dataset.
--
-- Type: AutoMLDataSplitConfig
--
-- 'mode', 'autoMLJobConfig_mode' - The method that Autopilot uses to train the data. You can either specify
-- the mode manually or let Autopilot choose for you based on the dataset
-- size by selecting @AUTO@. In @AUTO@ mode, Autopilot chooses @ENSEMBLING@
-- for datasets smaller than 100 MB, and @HYPERPARAMETER_TUNING@ for larger
-- ones.
--
-- The @ENSEMBLING@ mode uses a multi-stack ensemble model to predict
-- classification and regression tasks directly from your dataset. This
-- machine learning mode combines several base models to produce an optimal
-- predictive model. It then uses a stacking ensemble method to combine
-- predictions from contributing members. A multi-stack ensemble model can
-- provide better performance over a single model by combining the
-- predictive capabilities of multiple models. See
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
-- for a list of algorithms supported by @ENSEMBLING@ mode.
--
-- The @HYPERPARAMETER_TUNING@ (HPO) mode uses the best hyperparameters to
-- train the best version of a model. HPO will automatically select an
-- algorithm for the type of problem you want to solve. Then HPO finds the
-- best hyperparameters according to your objective metric. See
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
-- for a list of algorithms supported by @HYPERPARAMETER_TUNING@ mode.
--
-- 'securityConfig', 'autoMLJobConfig_securityConfig' - The security configuration for traffic encryption or Amazon VPC
-- settings.
newAutoMLJobConfig ::
  AutoMLJobConfig
newAutoMLJobConfig :: AutoMLJobConfig
newAutoMLJobConfig =
  AutoMLJobConfig'
    { $sel:candidateGenerationConfig:AutoMLJobConfig' :: Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig =
        forall a. Maybe a
Prelude.Nothing,
      $sel:completionCriteria:AutoMLJobConfig' :: Maybe AutoMLJobCompletionCriteria
completionCriteria = forall a. Maybe a
Prelude.Nothing,
      $sel:dataSplitConfig:AutoMLJobConfig' :: Maybe AutoMLDataSplitConfig
dataSplitConfig = forall a. Maybe a
Prelude.Nothing,
      $sel:mode:AutoMLJobConfig' :: Maybe AutoMLMode
mode = forall a. Maybe a
Prelude.Nothing,
      $sel:securityConfig:AutoMLJobConfig' :: Maybe AutoMLSecurityConfig
securityConfig = forall a. Maybe a
Prelude.Nothing
    }

-- | The configuration for generating a candidate for an AutoML job
-- (optional).
autoMLJobConfig_candidateGenerationConfig :: Lens.Lens' AutoMLJobConfig (Prelude.Maybe AutoMLCandidateGenerationConfig)
autoMLJobConfig_candidateGenerationConfig :: Lens' AutoMLJobConfig (Maybe AutoMLCandidateGenerationConfig)
autoMLJobConfig_candidateGenerationConfig = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\AutoMLJobConfig' {Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig :: Maybe AutoMLCandidateGenerationConfig
$sel:candidateGenerationConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig} -> Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig) (\s :: AutoMLJobConfig
s@AutoMLJobConfig' {} Maybe AutoMLCandidateGenerationConfig
a -> AutoMLJobConfig
s {$sel:candidateGenerationConfig:AutoMLJobConfig' :: Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig = Maybe AutoMLCandidateGenerationConfig
a} :: AutoMLJobConfig)

-- | How long an AutoML job is allowed to run, or how many candidates a job
-- is allowed to generate.
autoMLJobConfig_completionCriteria :: Lens.Lens' AutoMLJobConfig (Prelude.Maybe AutoMLJobCompletionCriteria)
autoMLJobConfig_completionCriteria :: Lens' AutoMLJobConfig (Maybe AutoMLJobCompletionCriteria)
autoMLJobConfig_completionCriteria = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\AutoMLJobConfig' {Maybe AutoMLJobCompletionCriteria
completionCriteria :: Maybe AutoMLJobCompletionCriteria
$sel:completionCriteria:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLJobCompletionCriteria
completionCriteria} -> Maybe AutoMLJobCompletionCriteria
completionCriteria) (\s :: AutoMLJobConfig
s@AutoMLJobConfig' {} Maybe AutoMLJobCompletionCriteria
a -> AutoMLJobConfig
s {$sel:completionCriteria:AutoMLJobConfig' :: Maybe AutoMLJobCompletionCriteria
completionCriteria = Maybe AutoMLJobCompletionCriteria
a} :: AutoMLJobConfig)

-- | The configuration for splitting the input training dataset.
--
-- Type: AutoMLDataSplitConfig
autoMLJobConfig_dataSplitConfig :: Lens.Lens' AutoMLJobConfig (Prelude.Maybe AutoMLDataSplitConfig)
autoMLJobConfig_dataSplitConfig :: Lens' AutoMLJobConfig (Maybe AutoMLDataSplitConfig)
autoMLJobConfig_dataSplitConfig = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\AutoMLJobConfig' {Maybe AutoMLDataSplitConfig
dataSplitConfig :: Maybe AutoMLDataSplitConfig
$sel:dataSplitConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLDataSplitConfig
dataSplitConfig} -> Maybe AutoMLDataSplitConfig
dataSplitConfig) (\s :: AutoMLJobConfig
s@AutoMLJobConfig' {} Maybe AutoMLDataSplitConfig
a -> AutoMLJobConfig
s {$sel:dataSplitConfig:AutoMLJobConfig' :: Maybe AutoMLDataSplitConfig
dataSplitConfig = Maybe AutoMLDataSplitConfig
a} :: AutoMLJobConfig)

-- | The method that Autopilot uses to train the data. You can either specify
-- the mode manually or let Autopilot choose for you based on the dataset
-- size by selecting @AUTO@. In @AUTO@ mode, Autopilot chooses @ENSEMBLING@
-- for datasets smaller than 100 MB, and @HYPERPARAMETER_TUNING@ for larger
-- ones.
--
-- The @ENSEMBLING@ mode uses a multi-stack ensemble model to predict
-- classification and regression tasks directly from your dataset. This
-- machine learning mode combines several base models to produce an optimal
-- predictive model. It then uses a stacking ensemble method to combine
-- predictions from contributing members. A multi-stack ensemble model can
-- provide better performance over a single model by combining the
-- predictive capabilities of multiple models. See
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
-- for a list of algorithms supported by @ENSEMBLING@ mode.
--
-- The @HYPERPARAMETER_TUNING@ (HPO) mode uses the best hyperparameters to
-- train the best version of a model. HPO will automatically select an
-- algorithm for the type of problem you want to solve. Then HPO finds the
-- best hyperparameters according to your objective metric. See
-- <https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt Autopilot algorithm support>
-- for a list of algorithms supported by @HYPERPARAMETER_TUNING@ mode.
autoMLJobConfig_mode :: Lens.Lens' AutoMLJobConfig (Prelude.Maybe AutoMLMode)
autoMLJobConfig_mode :: Lens' AutoMLJobConfig (Maybe AutoMLMode)
autoMLJobConfig_mode = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\AutoMLJobConfig' {Maybe AutoMLMode
mode :: Maybe AutoMLMode
$sel:mode:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLMode
mode} -> Maybe AutoMLMode
mode) (\s :: AutoMLJobConfig
s@AutoMLJobConfig' {} Maybe AutoMLMode
a -> AutoMLJobConfig
s {$sel:mode:AutoMLJobConfig' :: Maybe AutoMLMode
mode = Maybe AutoMLMode
a} :: AutoMLJobConfig)

-- | The security configuration for traffic encryption or Amazon VPC
-- settings.
autoMLJobConfig_securityConfig :: Lens.Lens' AutoMLJobConfig (Prelude.Maybe AutoMLSecurityConfig)
autoMLJobConfig_securityConfig :: Lens' AutoMLJobConfig (Maybe AutoMLSecurityConfig)
autoMLJobConfig_securityConfig = forall s a b t. (s -> a) -> (s -> b -> t) -> Lens s t a b
Lens.lens (\AutoMLJobConfig' {Maybe AutoMLSecurityConfig
securityConfig :: Maybe AutoMLSecurityConfig
$sel:securityConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLSecurityConfig
securityConfig} -> Maybe AutoMLSecurityConfig
securityConfig) (\s :: AutoMLJobConfig
s@AutoMLJobConfig' {} Maybe AutoMLSecurityConfig
a -> AutoMLJobConfig
s {$sel:securityConfig:AutoMLJobConfig' :: Maybe AutoMLSecurityConfig
securityConfig = Maybe AutoMLSecurityConfig
a} :: AutoMLJobConfig)

instance Data.FromJSON AutoMLJobConfig where
  parseJSON :: Value -> Parser AutoMLJobConfig
parseJSON =
    forall a. String -> (Object -> Parser a) -> Value -> Parser a
Data.withObject
      String
"AutoMLJobConfig"
      ( \Object
x ->
          Maybe AutoMLCandidateGenerationConfig
-> Maybe AutoMLJobCompletionCriteria
-> Maybe AutoMLDataSplitConfig
-> Maybe AutoMLMode
-> Maybe AutoMLSecurityConfig
-> AutoMLJobConfig
AutoMLJobConfig'
            forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"CandidateGenerationConfig")
            forall (f :: * -> *) a b. Applicative f => f (a -> b) -> f a -> f b
Prelude.<*> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"CompletionCriteria")
            forall (f :: * -> *) a b. Applicative f => f (a -> b) -> f a -> f b
Prelude.<*> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"DataSplitConfig")
            forall (f :: * -> *) a b. Applicative f => f (a -> b) -> f a -> f b
Prelude.<*> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"Mode")
            forall (f :: * -> *) a b. Applicative f => f (a -> b) -> f a -> f b
Prelude.<*> (Object
x forall a. FromJSON a => Object -> Key -> Parser (Maybe a)
Data..:? Key
"SecurityConfig")
      )

instance Prelude.Hashable AutoMLJobConfig where
  hashWithSalt :: Int -> AutoMLJobConfig -> Int
hashWithSalt Int
_salt AutoMLJobConfig' {Maybe AutoMLCandidateGenerationConfig
Maybe AutoMLDataSplitConfig
Maybe AutoMLJobCompletionCriteria
Maybe AutoMLMode
Maybe AutoMLSecurityConfig
securityConfig :: Maybe AutoMLSecurityConfig
mode :: Maybe AutoMLMode
dataSplitConfig :: Maybe AutoMLDataSplitConfig
completionCriteria :: Maybe AutoMLJobCompletionCriteria
candidateGenerationConfig :: Maybe AutoMLCandidateGenerationConfig
$sel:securityConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLSecurityConfig
$sel:mode:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLMode
$sel:dataSplitConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLDataSplitConfig
$sel:completionCriteria:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLJobCompletionCriteria
$sel:candidateGenerationConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLCandidateGenerationConfig
..} =
    Int
_salt
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe AutoMLJobCompletionCriteria
completionCriteria
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe AutoMLDataSplitConfig
dataSplitConfig
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe AutoMLMode
mode
      forall a. Hashable a => Int -> a -> Int
`Prelude.hashWithSalt` Maybe AutoMLSecurityConfig
securityConfig

instance Prelude.NFData AutoMLJobConfig where
  rnf :: AutoMLJobConfig -> ()
rnf AutoMLJobConfig' {Maybe AutoMLCandidateGenerationConfig
Maybe AutoMLDataSplitConfig
Maybe AutoMLJobCompletionCriteria
Maybe AutoMLMode
Maybe AutoMLSecurityConfig
securityConfig :: Maybe AutoMLSecurityConfig
mode :: Maybe AutoMLMode
dataSplitConfig :: Maybe AutoMLDataSplitConfig
completionCriteria :: Maybe AutoMLJobCompletionCriteria
candidateGenerationConfig :: Maybe AutoMLCandidateGenerationConfig
$sel:securityConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLSecurityConfig
$sel:mode:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLMode
$sel:dataSplitConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLDataSplitConfig
$sel:completionCriteria:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLJobCompletionCriteria
$sel:candidateGenerationConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLCandidateGenerationConfig
..} =
    forall a. NFData a => a -> ()
Prelude.rnf Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig
      seq :: forall a b. a -> b -> b
`Prelude.seq` forall a. NFData a => a -> ()
Prelude.rnf Maybe AutoMLJobCompletionCriteria
completionCriteria
      seq :: forall a b. a -> b -> b
`Prelude.seq` forall a. NFData a => a -> ()
Prelude.rnf Maybe AutoMLDataSplitConfig
dataSplitConfig
      seq :: forall a b. a -> b -> b
`Prelude.seq` forall a. NFData a => a -> ()
Prelude.rnf Maybe AutoMLMode
mode
      seq :: forall a b. a -> b -> b
`Prelude.seq` forall a. NFData a => a -> ()
Prelude.rnf Maybe AutoMLSecurityConfig
securityConfig

instance Data.ToJSON AutoMLJobConfig where
  toJSON :: AutoMLJobConfig -> Value
toJSON AutoMLJobConfig' {Maybe AutoMLCandidateGenerationConfig
Maybe AutoMLDataSplitConfig
Maybe AutoMLJobCompletionCriteria
Maybe AutoMLMode
Maybe AutoMLSecurityConfig
securityConfig :: Maybe AutoMLSecurityConfig
mode :: Maybe AutoMLMode
dataSplitConfig :: Maybe AutoMLDataSplitConfig
completionCriteria :: Maybe AutoMLJobCompletionCriteria
candidateGenerationConfig :: Maybe AutoMLCandidateGenerationConfig
$sel:securityConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLSecurityConfig
$sel:mode:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLMode
$sel:dataSplitConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLDataSplitConfig
$sel:completionCriteria:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLJobCompletionCriteria
$sel:candidateGenerationConfig:AutoMLJobConfig' :: AutoMLJobConfig -> Maybe AutoMLCandidateGenerationConfig
..} =
    [Pair] -> Value
Data.object
      ( forall a. [Maybe a] -> [a]
Prelude.catMaybes
          [ (Key
"CandidateGenerationConfig" forall kv v. (KeyValue kv, ToJSON v) => Key -> v -> kv
Data..=)
              forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> Maybe AutoMLCandidateGenerationConfig
candidateGenerationConfig,
            (Key
"CompletionCriteria" forall kv v. (KeyValue kv, ToJSON v) => Key -> v -> kv
Data..=)
              forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> Maybe AutoMLJobCompletionCriteria
completionCriteria,
            (Key
"DataSplitConfig" forall kv v. (KeyValue kv, ToJSON v) => Key -> v -> kv
Data..=)
              forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> Maybe AutoMLDataSplitConfig
dataSplitConfig,
            (Key
"Mode" forall kv v. (KeyValue kv, ToJSON v) => Key -> v -> kv
Data..=) forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> Maybe AutoMLMode
mode,
            (Key
"SecurityConfig" forall kv v. (KeyValue kv, ToJSON v) => Key -> v -> kv
Data..=)
              forall (f :: * -> *) a b. Functor f => (a -> b) -> f a -> f b
Prelude.<$> Maybe AutoMLSecurityConfig
securityConfig
          ]
      )