GetEvaluation.hs

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

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

-- |
-- Module      : Amazonka.MachineLearning.GetEvaluation
-- Copyright   : (c) 2013-2023 Brendan Hay
-- License     : Mozilla Public License, v. 2.0.
-- Maintainer  : Brendan Hay
-- Stability   : auto-generated
-- Portability : non-portable (GHC extensions)
--
-- Returns an @Evaluation@ that includes metadata as well as the current
-- status of the @Evaluation@.
module Amazonka.MachineLearning.GetEvaluation
  ( -- * Creating a Request
    GetEvaluation (..),
    newGetEvaluation,

    -- * Request Lenses
    getEvaluation_evaluationId,

    -- * Destructuring the Response
    GetEvaluationResponse (..),
    newGetEvaluationResponse,

    -- * Response Lenses
    getEvaluationResponse_computeTime,
    getEvaluationResponse_createdAt,
    getEvaluationResponse_createdByIamUser,
    getEvaluationResponse_evaluationDataSourceId,
    getEvaluationResponse_evaluationId,
    getEvaluationResponse_finishedAt,
    getEvaluationResponse_inputDataLocationS3,
    getEvaluationResponse_lastUpdatedAt,
    getEvaluationResponse_logUri,
    getEvaluationResponse_mLModelId,
    getEvaluationResponse_message,
    getEvaluationResponse_name,
    getEvaluationResponse_performanceMetrics,
    getEvaluationResponse_startedAt,
    getEvaluationResponse_status,
    getEvaluationResponse_httpStatus,
  )
where

import qualified Amazonka.Core as Core
import qualified Amazonka.Core.Lens.Internal as Lens
import qualified Amazonka.Data as Data
import Amazonka.MachineLearning.Types
import qualified Amazonka.Prelude as Prelude
import qualified Amazonka.Request as Request
import qualified Amazonka.Response as Response

-- | /See:/ 'newGetEvaluation' smart constructor.
data GetEvaluation = GetEvaluation'
  { -- | The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@
    -- is recorded and cataloged. The ID provides the means to access the
    -- information.
    evaluationId :: Prelude.Text
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'GetEvaluation' 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:
--
-- 'evaluationId', 'getEvaluation_evaluationId' - The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@
-- is recorded and cataloged. The ID provides the means to access the
-- information.
newGetEvaluation ::
  -- | 'evaluationId'
  Prelude.Text ->
  GetEvaluation
newGetEvaluation pEvaluationId_ =
  GetEvaluation' {evaluationId = pEvaluationId_}

-- | The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@
-- is recorded and cataloged. The ID provides the means to access the
-- information.
getEvaluation_evaluationId :: Lens.Lens' GetEvaluation Prelude.Text
getEvaluation_evaluationId = Lens.lens (\GetEvaluation' {evaluationId} -> evaluationId) (\s@GetEvaluation' {} a -> s {evaluationId = a} :: GetEvaluation)

instance Core.AWSRequest GetEvaluation where
  type
    AWSResponse GetEvaluation =
      GetEvaluationResponse
  request overrides =
    Request.postJSON (overrides defaultService)
  response =
    Response.receiveJSON
      ( \s h x ->
          GetEvaluationResponse'
            Prelude.<$> (x Data..?> "ComputeTime")
            Prelude.<*> (x Data..?> "CreatedAt")
            Prelude.<*> (x Data..?> "CreatedByIamUser")
            Prelude.<*> (x Data..?> "EvaluationDataSourceId")
            Prelude.<*> (x Data..?> "EvaluationId")
            Prelude.<*> (x Data..?> "FinishedAt")
            Prelude.<*> (x Data..?> "InputDataLocationS3")
            Prelude.<*> (x Data..?> "LastUpdatedAt")
            Prelude.<*> (x Data..?> "LogUri")
            Prelude.<*> (x Data..?> "MLModelId")
            Prelude.<*> (x Data..?> "Message")
            Prelude.<*> (x Data..?> "Name")
            Prelude.<*> (x Data..?> "PerformanceMetrics")
            Prelude.<*> (x Data..?> "StartedAt")
            Prelude.<*> (x Data..?> "Status")
            Prelude.<*> (Prelude.pure (Prelude.fromEnum s))
      )

instance Prelude.Hashable GetEvaluation where
  hashWithSalt _salt GetEvaluation' {..} =
    _salt `Prelude.hashWithSalt` evaluationId

instance Prelude.NFData GetEvaluation where
  rnf GetEvaluation' {..} = Prelude.rnf evaluationId

instance Data.ToHeaders GetEvaluation where
  toHeaders =
    Prelude.const
      ( Prelude.mconcat
          [ "X-Amz-Target"
              Data.=# ( "AmazonML_20141212.GetEvaluation" ::
                          Prelude.ByteString
                      ),
            "Content-Type"
              Data.=# ( "application/x-amz-json-1.1" ::
                          Prelude.ByteString
                      )
          ]
      )

instance Data.ToJSON GetEvaluation where
  toJSON GetEvaluation' {..} =
    Data.object
      ( Prelude.catMaybes
          [Prelude.Just ("EvaluationId" Data..= evaluationId)]
      )

instance Data.ToPath GetEvaluation where
  toPath = Prelude.const "/"

instance Data.ToQuery GetEvaluation where
  toQuery = Prelude.const Prelude.mempty

-- | Represents the output of a @GetEvaluation@ operation and describes an
-- @Evaluation@.
--
-- /See:/ 'newGetEvaluationResponse' smart constructor.
data GetEvaluationResponse = GetEvaluationResponse'
  { -- | The approximate CPU time in milliseconds that Amazon Machine Learning
    -- spent processing the @Evaluation@, normalized and scaled on computation
    -- resources. @ComputeTime@ is only available if the @Evaluation@ is in the
    -- @COMPLETED@ state.
    computeTime :: Prelude.Maybe Prelude.Integer,
    -- | The time that the @Evaluation@ was created. The time is expressed in
    -- epoch time.
    createdAt :: Prelude.Maybe Data.POSIX,
    -- | The AWS user account that invoked the evaluation. The account type can
    -- be either an AWS root account or an AWS Identity and Access Management
    -- (IAM) user account.
    createdByIamUser :: Prelude.Maybe Prelude.Text,
    -- | The @DataSource@ used for this evaluation.
    evaluationDataSourceId :: Prelude.Maybe Prelude.Text,
    -- | The evaluation ID which is same as the @EvaluationId@ in the request.
    evaluationId :: Prelude.Maybe Prelude.Text,
    -- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as
    -- @COMPLETED@ or @FAILED@. @FinishedAt@ is only available when the
    -- @Evaluation@ is in the @COMPLETED@ or @FAILED@ state.
    finishedAt :: Prelude.Maybe Data.POSIX,
    -- | The location of the data file or directory in Amazon Simple Storage
    -- Service (Amazon S3).
    inputDataLocationS3 :: Prelude.Maybe Prelude.Text,
    -- | The time of the most recent edit to the @Evaluation@. The time is
    -- expressed in epoch time.
    lastUpdatedAt :: Prelude.Maybe Data.POSIX,
    -- | A link to the file that contains logs of the @CreateEvaluation@
    -- operation.
    logUri :: Prelude.Maybe Prelude.Text,
    -- | The ID of the @MLModel@ that was the focus of the evaluation.
    mLModelId :: Prelude.Maybe Prelude.Text,
    -- | A description of the most recent details about evaluating the @MLModel@.
    message :: Prelude.Maybe Prelude.Text,
    -- | A user-supplied name or description of the @Evaluation@.
    name :: Prelude.Maybe Prelude.Text,
    -- | Measurements of how well the @MLModel@ performed using observations
    -- referenced by the @DataSource@. One of the following metric is returned
    -- based on the type of the @MLModel@:
    --
    -- -   BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC)
    --     technique to measure performance.
    --
    -- -   RegressionRMSE: A regression @MLModel@ uses the Root Mean Square
    --     Error (RMSE) technique to measure performance. RMSE measures the
    --     difference between predicted and actual values for a single
    --     variable.
    --
    -- -   MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score
    --     technique to measure performance.
    --
    -- For more information about performance metrics, please see the
    -- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.
    performanceMetrics :: Prelude.Maybe PerformanceMetrics,
    -- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as
    -- @INPROGRESS@. @StartedAt@ isn\'t available if the @Evaluation@ is in the
    -- @PENDING@ state.
    startedAt :: Prelude.Maybe Data.POSIX,
    -- | The status of the evaluation. This element can have one of the following
    -- values:
    --
    -- -   @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request
    --     to evaluate an @MLModel@.
    --
    -- -   @INPROGRESS@ - The evaluation is underway.
    --
    -- -   @FAILED@ - The request to evaluate an @MLModel@ did not run to
    --     completion. It is not usable.
    --
    -- -   @COMPLETED@ - The evaluation process completed successfully.
    --
    -- -   @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable.
    status :: Prelude.Maybe EntityStatus,
    -- | The response's http status code.
    httpStatus :: Prelude.Int
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'GetEvaluationResponse' 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:
--
-- 'computeTime', 'getEvaluationResponse_computeTime' - The approximate CPU time in milliseconds that Amazon Machine Learning
-- spent processing the @Evaluation@, normalized and scaled on computation
-- resources. @ComputeTime@ is only available if the @Evaluation@ is in the
-- @COMPLETED@ state.
--
-- 'createdAt', 'getEvaluationResponse_createdAt' - The time that the @Evaluation@ was created. The time is expressed in
-- epoch time.
--
-- 'createdByIamUser', 'getEvaluationResponse_createdByIamUser' - The AWS user account that invoked the evaluation. The account type can
-- be either an AWS root account or an AWS Identity and Access Management
-- (IAM) user account.
--
-- 'evaluationDataSourceId', 'getEvaluationResponse_evaluationDataSourceId' - The @DataSource@ used for this evaluation.
--
-- 'evaluationId', 'getEvaluationResponse_evaluationId' - The evaluation ID which is same as the @EvaluationId@ in the request.
--
-- 'finishedAt', 'getEvaluationResponse_finishedAt' - The epoch time when Amazon Machine Learning marked the @Evaluation@ as
-- @COMPLETED@ or @FAILED@. @FinishedAt@ is only available when the
-- @Evaluation@ is in the @COMPLETED@ or @FAILED@ state.
--
-- 'inputDataLocationS3', 'getEvaluationResponse_inputDataLocationS3' - The location of the data file or directory in Amazon Simple Storage
-- Service (Amazon S3).
--
-- 'lastUpdatedAt', 'getEvaluationResponse_lastUpdatedAt' - The time of the most recent edit to the @Evaluation@. The time is
-- expressed in epoch time.
--
-- 'logUri', 'getEvaluationResponse_logUri' - A link to the file that contains logs of the @CreateEvaluation@
-- operation.
--
-- 'mLModelId', 'getEvaluationResponse_mLModelId' - The ID of the @MLModel@ that was the focus of the evaluation.
--
-- 'message', 'getEvaluationResponse_message' - A description of the most recent details about evaluating the @MLModel@.
--
-- 'name', 'getEvaluationResponse_name' - A user-supplied name or description of the @Evaluation@.
--
-- 'performanceMetrics', 'getEvaluationResponse_performanceMetrics' - Measurements of how well the @MLModel@ performed using observations
-- referenced by the @DataSource@. One of the following metric is returned
-- based on the type of the @MLModel@:
--
-- -   BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC)
--     technique to measure performance.
--
-- -   RegressionRMSE: A regression @MLModel@ uses the Root Mean Square
--     Error (RMSE) technique to measure performance. RMSE measures the
--     difference between predicted and actual values for a single
--     variable.
--
-- -   MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score
--     technique to measure performance.
--
-- For more information about performance metrics, please see the
-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.
--
-- 'startedAt', 'getEvaluationResponse_startedAt' - The epoch time when Amazon Machine Learning marked the @Evaluation@ as
-- @INPROGRESS@. @StartedAt@ isn\'t available if the @Evaluation@ is in the
-- @PENDING@ state.
--
-- 'status', 'getEvaluationResponse_status' - The status of the evaluation. This element can have one of the following
-- values:
--
-- -   @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request
--     to evaluate an @MLModel@.
--
-- -   @INPROGRESS@ - The evaluation is underway.
--
-- -   @FAILED@ - The request to evaluate an @MLModel@ did not run to
--     completion. It is not usable.
--
-- -   @COMPLETED@ - The evaluation process completed successfully.
--
-- -   @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable.
--
-- 'httpStatus', 'getEvaluationResponse_httpStatus' - The response's http status code.
newGetEvaluationResponse ::
  -- | 'httpStatus'
  Prelude.Int ->
  GetEvaluationResponse
newGetEvaluationResponse pHttpStatus_ =
  GetEvaluationResponse'
    { computeTime =
        Prelude.Nothing,
      createdAt = Prelude.Nothing,
      createdByIamUser = Prelude.Nothing,
      evaluationDataSourceId = Prelude.Nothing,
      evaluationId = Prelude.Nothing,
      finishedAt = Prelude.Nothing,
      inputDataLocationS3 = Prelude.Nothing,
      lastUpdatedAt = Prelude.Nothing,
      logUri = Prelude.Nothing,
      mLModelId = Prelude.Nothing,
      message = Prelude.Nothing,
      name = Prelude.Nothing,
      performanceMetrics = Prelude.Nothing,
      startedAt = Prelude.Nothing,
      status = Prelude.Nothing,
      httpStatus = pHttpStatus_
    }

-- | The approximate CPU time in milliseconds that Amazon Machine Learning
-- spent processing the @Evaluation@, normalized and scaled on computation
-- resources. @ComputeTime@ is only available if the @Evaluation@ is in the
-- @COMPLETED@ state.
getEvaluationResponse_computeTime :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Integer)
getEvaluationResponse_computeTime = Lens.lens (\GetEvaluationResponse' {computeTime} -> computeTime) (\s@GetEvaluationResponse' {} a -> s {computeTime = a} :: GetEvaluationResponse)

-- | The time that the @Evaluation@ was created. The time is expressed in
-- epoch time.
getEvaluationResponse_createdAt :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.UTCTime)
getEvaluationResponse_createdAt = Lens.lens (\GetEvaluationResponse' {createdAt} -> createdAt) (\s@GetEvaluationResponse' {} a -> s {createdAt = a} :: GetEvaluationResponse) Prelude.. Lens.mapping Data._Time

-- | The AWS user account that invoked the evaluation. The account type can
-- be either an AWS root account or an AWS Identity and Access Management
-- (IAM) user account.
getEvaluationResponse_createdByIamUser :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_createdByIamUser = Lens.lens (\GetEvaluationResponse' {createdByIamUser} -> createdByIamUser) (\s@GetEvaluationResponse' {} a -> s {createdByIamUser = a} :: GetEvaluationResponse)

-- | The @DataSource@ used for this evaluation.
getEvaluationResponse_evaluationDataSourceId :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_evaluationDataSourceId = Lens.lens (\GetEvaluationResponse' {evaluationDataSourceId} -> evaluationDataSourceId) (\s@GetEvaluationResponse' {} a -> s {evaluationDataSourceId = a} :: GetEvaluationResponse)

-- | The evaluation ID which is same as the @EvaluationId@ in the request.
getEvaluationResponse_evaluationId :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_evaluationId = Lens.lens (\GetEvaluationResponse' {evaluationId} -> evaluationId) (\s@GetEvaluationResponse' {} a -> s {evaluationId = a} :: GetEvaluationResponse)

-- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as
-- @COMPLETED@ or @FAILED@. @FinishedAt@ is only available when the
-- @Evaluation@ is in the @COMPLETED@ or @FAILED@ state.
getEvaluationResponse_finishedAt :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.UTCTime)
getEvaluationResponse_finishedAt = Lens.lens (\GetEvaluationResponse' {finishedAt} -> finishedAt) (\s@GetEvaluationResponse' {} a -> s {finishedAt = a} :: GetEvaluationResponse) Prelude.. Lens.mapping Data._Time

-- | The location of the data file or directory in Amazon Simple Storage
-- Service (Amazon S3).
getEvaluationResponse_inputDataLocationS3 :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_inputDataLocationS3 = Lens.lens (\GetEvaluationResponse' {inputDataLocationS3} -> inputDataLocationS3) (\s@GetEvaluationResponse' {} a -> s {inputDataLocationS3 = a} :: GetEvaluationResponse)

-- | The time of the most recent edit to the @Evaluation@. The time is
-- expressed in epoch time.
getEvaluationResponse_lastUpdatedAt :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.UTCTime)
getEvaluationResponse_lastUpdatedAt = Lens.lens (\GetEvaluationResponse' {lastUpdatedAt} -> lastUpdatedAt) (\s@GetEvaluationResponse' {} a -> s {lastUpdatedAt = a} :: GetEvaluationResponse) Prelude.. Lens.mapping Data._Time

-- | A link to the file that contains logs of the @CreateEvaluation@
-- operation.
getEvaluationResponse_logUri :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_logUri = Lens.lens (\GetEvaluationResponse' {logUri} -> logUri) (\s@GetEvaluationResponse' {} a -> s {logUri = a} :: GetEvaluationResponse)

-- | The ID of the @MLModel@ that was the focus of the evaluation.
getEvaluationResponse_mLModelId :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_mLModelId = Lens.lens (\GetEvaluationResponse' {mLModelId} -> mLModelId) (\s@GetEvaluationResponse' {} a -> s {mLModelId = a} :: GetEvaluationResponse)

-- | A description of the most recent details about evaluating the @MLModel@.
getEvaluationResponse_message :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_message = Lens.lens (\GetEvaluationResponse' {message} -> message) (\s@GetEvaluationResponse' {} a -> s {message = a} :: GetEvaluationResponse)

-- | A user-supplied name or description of the @Evaluation@.
getEvaluationResponse_name :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.Text)
getEvaluationResponse_name = Lens.lens (\GetEvaluationResponse' {name} -> name) (\s@GetEvaluationResponse' {} a -> s {name = a} :: GetEvaluationResponse)

-- | Measurements of how well the @MLModel@ performed using observations
-- referenced by the @DataSource@. One of the following metric is returned
-- based on the type of the @MLModel@:
--
-- -   BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC)
--     technique to measure performance.
--
-- -   RegressionRMSE: A regression @MLModel@ uses the Root Mean Square
--     Error (RMSE) technique to measure performance. RMSE measures the
--     difference between predicted and actual values for a single
--     variable.
--
-- -   MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score
--     technique to measure performance.
--
-- For more information about performance metrics, please see the
-- <https://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.
getEvaluationResponse_performanceMetrics :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe PerformanceMetrics)
getEvaluationResponse_performanceMetrics = Lens.lens (\GetEvaluationResponse' {performanceMetrics} -> performanceMetrics) (\s@GetEvaluationResponse' {} a -> s {performanceMetrics = a} :: GetEvaluationResponse)

-- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as
-- @INPROGRESS@. @StartedAt@ isn\'t available if the @Evaluation@ is in the
-- @PENDING@ state.
getEvaluationResponse_startedAt :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe Prelude.UTCTime)
getEvaluationResponse_startedAt = Lens.lens (\GetEvaluationResponse' {startedAt} -> startedAt) (\s@GetEvaluationResponse' {} a -> s {startedAt = a} :: GetEvaluationResponse) Prelude.. Lens.mapping Data._Time

-- | The status of the evaluation. This element can have one of the following
-- values:
--
-- -   @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request
--     to evaluate an @MLModel@.
--
-- -   @INPROGRESS@ - The evaluation is underway.
--
-- -   @FAILED@ - The request to evaluate an @MLModel@ did not run to
--     completion. It is not usable.
--
-- -   @COMPLETED@ - The evaluation process completed successfully.
--
-- -   @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable.
getEvaluationResponse_status :: Lens.Lens' GetEvaluationResponse (Prelude.Maybe EntityStatus)
getEvaluationResponse_status = Lens.lens (\GetEvaluationResponse' {status} -> status) (\s@GetEvaluationResponse' {} a -> s {status = a} :: GetEvaluationResponse)

-- | The response's http status code.
getEvaluationResponse_httpStatus :: Lens.Lens' GetEvaluationResponse Prelude.Int
getEvaluationResponse_httpStatus = Lens.lens (\GetEvaluationResponse' {httpStatus} -> httpStatus) (\s@GetEvaluationResponse' {} a -> s {httpStatus = a} :: GetEvaluationResponse)

instance Prelude.NFData GetEvaluationResponse where
  rnf GetEvaluationResponse' {..} =
    Prelude.rnf computeTime
      `Prelude.seq` Prelude.rnf createdAt
      `Prelude.seq` Prelude.rnf createdByIamUser
      `Prelude.seq` Prelude.rnf evaluationDataSourceId
      `Prelude.seq` Prelude.rnf evaluationId
      `Prelude.seq` Prelude.rnf finishedAt
      `Prelude.seq` Prelude.rnf inputDataLocationS3
      `Prelude.seq` Prelude.rnf lastUpdatedAt
      `Prelude.seq` Prelude.rnf logUri
      `Prelude.seq` Prelude.rnf mLModelId
      `Prelude.seq` Prelude.rnf message
      `Prelude.seq` Prelude.rnf name
      `Prelude.seq` Prelude.rnf performanceMetrics
      `Prelude.seq` Prelude.rnf startedAt
      `Prelude.seq` Prelude.rnf status
      `Prelude.seq` Prelude.rnf httpStatus