{-# 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.Channel
-- 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.Channel 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.CompressionType
import Amazonka.SageMaker.Types.DataSource
import Amazonka.SageMaker.Types.RecordWrapper
import Amazonka.SageMaker.Types.ShuffleConfig
import Amazonka.SageMaker.Types.TrainingInputMode

-- | A channel is a named input source that training algorithms can consume.
--
-- /See:/ 'newChannel' smart constructor.
data Channel = Channel'
  { -- | If training data is compressed, the compression type. The default value
    -- is @None@. @CompressionType@ is used only in Pipe input mode. In File
    -- mode, leave this field unset or set it to None.
    compressionType :: Prelude.Maybe CompressionType,
    -- | The MIME type of the data.
    contentType :: Prelude.Maybe Prelude.Text,
    -- | (Optional) The input mode to use for the data channel in a training job.
    -- If you don\'t set a value for @InputMode@, SageMaker uses the value set
    -- for @TrainingInputMode@. Use this parameter to override the
    -- @TrainingInputMode@ setting in a AlgorithmSpecification request when you
    -- have a channel that needs a different input mode from the training
    -- job\'s general setting. To download the data from Amazon Simple Storage
    -- Service (Amazon S3) to the provisioned ML storage volume, and mount the
    -- directory to a Docker volume, use @File@ input mode. To stream data
    -- directly from Amazon S3 to the container, choose @Pipe@ input mode.
    --
    -- To use a model for incremental training, choose @File@ input model.
    inputMode :: Prelude.Maybe TrainingInputMode,
    -- | Specify RecordIO as the value when input data is in raw format but the
    -- training algorithm requires the RecordIO format. In this case, SageMaker
    -- wraps each individual S3 object in a RecordIO record. If the input data
    -- is already in RecordIO format, you don\'t need to set this attribute.
    -- For more information, see
    -- <https://mxnet.apache.org/api/architecture/note_data_loading#data-format Create a Dataset Using RecordIO>.
    --
    -- In File mode, leave this field unset or set it to None.
    recordWrapperType :: Prelude.Maybe RecordWrapper,
    -- | A configuration for a shuffle option for input data in a channel. If you
    -- use @S3Prefix@ for @S3DataType@, this shuffles the results of the S3 key
    -- prefix matches. If you use @ManifestFile@, the order of the S3 object
    -- references in the @ManifestFile@ is shuffled. If you use
    -- @AugmentedManifestFile@, the order of the JSON lines in the
    -- @AugmentedManifestFile@ is shuffled. The shuffling order is determined
    -- using the @Seed@ value.
    --
    -- For Pipe input mode, shuffling is done at the start of every epoch. With
    -- large datasets this ensures that the order of the training data is
    -- different for each epoch, it helps reduce bias and possible overfitting.
    -- In a multi-node training job when ShuffleConfig is combined with
    -- @S3DataDistributionType@ of @ShardedByS3Key@, the data is shuffled
    -- across nodes so that the content sent to a particular node on the first
    -- epoch might be sent to a different node on the second epoch.
    shuffleConfig :: Prelude.Maybe ShuffleConfig,
    -- | The name of the channel.
    channelName :: Prelude.Text,
    -- | The location of the channel data.
    dataSource :: DataSource
  }
  deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic)

-- |
-- Create a value of 'Channel' 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:
--
-- 'compressionType', 'channel_compressionType' - If training data is compressed, the compression type. The default value
-- is @None@. @CompressionType@ is used only in Pipe input mode. In File
-- mode, leave this field unset or set it to None.
--
-- 'contentType', 'channel_contentType' - The MIME type of the data.
--
-- 'inputMode', 'channel_inputMode' - (Optional) The input mode to use for the data channel in a training job.
-- If you don\'t set a value for @InputMode@, SageMaker uses the value set
-- for @TrainingInputMode@. Use this parameter to override the
-- @TrainingInputMode@ setting in a AlgorithmSpecification request when you
-- have a channel that needs a different input mode from the training
-- job\'s general setting. To download the data from Amazon Simple Storage
-- Service (Amazon S3) to the provisioned ML storage volume, and mount the
-- directory to a Docker volume, use @File@ input mode. To stream data
-- directly from Amazon S3 to the container, choose @Pipe@ input mode.
--
-- To use a model for incremental training, choose @File@ input model.
--
-- 'recordWrapperType', 'channel_recordWrapperType' - Specify RecordIO as the value when input data is in raw format but the
-- training algorithm requires the RecordIO format. In this case, SageMaker
-- wraps each individual S3 object in a RecordIO record. If the input data
-- is already in RecordIO format, you don\'t need to set this attribute.
-- For more information, see
-- <https://mxnet.apache.org/api/architecture/note_data_loading#data-format Create a Dataset Using RecordIO>.
--
-- In File mode, leave this field unset or set it to None.
--
-- 'shuffleConfig', 'channel_shuffleConfig' - A configuration for a shuffle option for input data in a channel. If you
-- use @S3Prefix@ for @S3DataType@, this shuffles the results of the S3 key
-- prefix matches. If you use @ManifestFile@, the order of the S3 object
-- references in the @ManifestFile@ is shuffled. If you use
-- @AugmentedManifestFile@, the order of the JSON lines in the
-- @AugmentedManifestFile@ is shuffled. The shuffling order is determined
-- using the @Seed@ value.
--
-- For Pipe input mode, shuffling is done at the start of every epoch. With
-- large datasets this ensures that the order of the training data is
-- different for each epoch, it helps reduce bias and possible overfitting.
-- In a multi-node training job when ShuffleConfig is combined with
-- @S3DataDistributionType@ of @ShardedByS3Key@, the data is shuffled
-- across nodes so that the content sent to a particular node on the first
-- epoch might be sent to a different node on the second epoch.
--
-- 'channelName', 'channel_channelName' - The name of the channel.
--
-- 'dataSource', 'channel_dataSource' - The location of the channel data.
newChannel ::
  -- | 'channelName'
  Prelude.Text ->
  -- | 'dataSource'
  DataSource ->
  Channel
newChannel pChannelName_ pDataSource_ =
  Channel'
    { compressionType = Prelude.Nothing,
      contentType = Prelude.Nothing,
      inputMode = Prelude.Nothing,
      recordWrapperType = Prelude.Nothing,
      shuffleConfig = Prelude.Nothing,
      channelName = pChannelName_,
      dataSource = pDataSource_
    }

-- | If training data is compressed, the compression type. The default value
-- is @None@. @CompressionType@ is used only in Pipe input mode. In File
-- mode, leave this field unset or set it to None.
channel_compressionType :: Lens.Lens' Channel (Prelude.Maybe CompressionType)
channel_compressionType = Lens.lens (\Channel' {compressionType} -> compressionType) (\s@Channel' {} a -> s {compressionType = a} :: Channel)

-- | The MIME type of the data.
channel_contentType :: Lens.Lens' Channel (Prelude.Maybe Prelude.Text)
channel_contentType = Lens.lens (\Channel' {contentType} -> contentType) (\s@Channel' {} a -> s {contentType = a} :: Channel)

-- | (Optional) The input mode to use for the data channel in a training job.
-- If you don\'t set a value for @InputMode@, SageMaker uses the value set
-- for @TrainingInputMode@. Use this parameter to override the
-- @TrainingInputMode@ setting in a AlgorithmSpecification request when you
-- have a channel that needs a different input mode from the training
-- job\'s general setting. To download the data from Amazon Simple Storage
-- Service (Amazon S3) to the provisioned ML storage volume, and mount the
-- directory to a Docker volume, use @File@ input mode. To stream data
-- directly from Amazon S3 to the container, choose @Pipe@ input mode.
--
-- To use a model for incremental training, choose @File@ input model.
channel_inputMode :: Lens.Lens' Channel (Prelude.Maybe TrainingInputMode)
channel_inputMode = Lens.lens (\Channel' {inputMode} -> inputMode) (\s@Channel' {} a -> s {inputMode = a} :: Channel)

-- | Specify RecordIO as the value when input data is in raw format but the
-- training algorithm requires the RecordIO format. In this case, SageMaker
-- wraps each individual S3 object in a RecordIO record. If the input data
-- is already in RecordIO format, you don\'t need to set this attribute.
-- For more information, see
-- <https://mxnet.apache.org/api/architecture/note_data_loading#data-format Create a Dataset Using RecordIO>.
--
-- In File mode, leave this field unset or set it to None.
channel_recordWrapperType :: Lens.Lens' Channel (Prelude.Maybe RecordWrapper)
channel_recordWrapperType = Lens.lens (\Channel' {recordWrapperType} -> recordWrapperType) (\s@Channel' {} a -> s {recordWrapperType = a} :: Channel)

-- | A configuration for a shuffle option for input data in a channel. If you
-- use @S3Prefix@ for @S3DataType@, this shuffles the results of the S3 key
-- prefix matches. If you use @ManifestFile@, the order of the S3 object
-- references in the @ManifestFile@ is shuffled. If you use
-- @AugmentedManifestFile@, the order of the JSON lines in the
-- @AugmentedManifestFile@ is shuffled. The shuffling order is determined
-- using the @Seed@ value.
--
-- For Pipe input mode, shuffling is done at the start of every epoch. With
-- large datasets this ensures that the order of the training data is
-- different for each epoch, it helps reduce bias and possible overfitting.
-- In a multi-node training job when ShuffleConfig is combined with
-- @S3DataDistributionType@ of @ShardedByS3Key@, the data is shuffled
-- across nodes so that the content sent to a particular node on the first
-- epoch might be sent to a different node on the second epoch.
channel_shuffleConfig :: Lens.Lens' Channel (Prelude.Maybe ShuffleConfig)
channel_shuffleConfig = Lens.lens (\Channel' {shuffleConfig} -> shuffleConfig) (\s@Channel' {} a -> s {shuffleConfig = a} :: Channel)

-- | The name of the channel.
channel_channelName :: Lens.Lens' Channel Prelude.Text
channel_channelName = Lens.lens (\Channel' {channelName} -> channelName) (\s@Channel' {} a -> s {channelName = a} :: Channel)

-- | The location of the channel data.
channel_dataSource :: Lens.Lens' Channel DataSource
channel_dataSource = Lens.lens (\Channel' {dataSource} -> dataSource) (\s@Channel' {} a -> s {dataSource = a} :: Channel)

instance Data.FromJSON Channel where
  parseJSON =
    Data.withObject
      "Channel"
      ( \x ->
          Channel'
            Prelude.<$> (x Data..:? "CompressionType")
            Prelude.<*> (x Data..:? "ContentType")
            Prelude.<*> (x Data..:? "InputMode")
            Prelude.<*> (x Data..:? "RecordWrapperType")
            Prelude.<*> (x Data..:? "ShuffleConfig")
            Prelude.<*> (x Data..: "ChannelName")
            Prelude.<*> (x Data..: "DataSource")
      )

instance Prelude.Hashable Channel where
  hashWithSalt _salt Channel' {..} =
    _salt
      `Prelude.hashWithSalt` compressionType
      `Prelude.hashWithSalt` contentType
      `Prelude.hashWithSalt` inputMode
      `Prelude.hashWithSalt` recordWrapperType
      `Prelude.hashWithSalt` shuffleConfig
      `Prelude.hashWithSalt` channelName
      `Prelude.hashWithSalt` dataSource

instance Prelude.NFData Channel where
  rnf Channel' {..} =
    Prelude.rnf compressionType
      `Prelude.seq` Prelude.rnf contentType
      `Prelude.seq` Prelude.rnf inputMode
      `Prelude.seq` Prelude.rnf recordWrapperType
      `Prelude.seq` Prelude.rnf shuffleConfig
      `Prelude.seq` Prelude.rnf channelName
      `Prelude.seq` Prelude.rnf dataSource

instance Data.ToJSON Channel where
  toJSON Channel' {..} =
    Data.object
      ( Prelude.catMaybes
          [ ("CompressionType" Data..=)
              Prelude.<$> compressionType,
            ("ContentType" Data..=) Prelude.<$> contentType,
            ("InputMode" Data..=) Prelude.<$> inputMode,
            ("RecordWrapperType" Data..=)
              Prelude.<$> recordWrapperType,
            ("ShuffleConfig" Data..=) Prelude.<$> shuffleConfig,
            Prelude.Just ("ChannelName" Data..= channelName),
            Prelude.Just ("DataSource" Data..= dataSource)
          ]
      )