Training

static let text: Modality

static let image: Modality

static let video: Modality

static let audio: Modality

var description: String { get }

init?(name: String)

static let masked: Objective

static let contrastive: Objective

static let joint: Objective

var description: String { get }

init?(name: String)

static let ambient: Negatives

static let named: Negatives

var description: String { get }

init?(name: String)

static let derived: PairLossForm

static let balanced: PairLossForm

static let ranked: PairLossForm

static let sigmoid: PairLossForm

static let none: LateInteractionSide

static let query: LateInteractionSide

static let document: LateInteractionSide

static let queryAndDocument: LateInteractionSide

var patchSide: Int

var channels: Int

init(patchSide: Int = 0, channels: Int = 0)

var patchSide: Int

var tubeFrames: Int

var frameStride: Int

var channels: Int

init(patchSide: Int = 0, tubeFrames: Int = 0, frameStride: Int = 0, channels: Int = 0)

var chunkSamples: Int

var sampleRate: Int

init(chunkSamples: Int = 0, sampleRate: Int = 0)

var maxRowsPerDevice: Int

var maxSegmentsPerDevice: Int

var maxColumnsPerRow: Int

var maxBagsPerDevice: Int

var maxChoicesPerItem: Int

var image: ImageShape

var video: VideoShape

var audio: AudioShape

init(maxRowsPerDevice: Int = 0, maxSegmentsPerDevice: Int = 0, maxColumnsPerRow: Int = 0, maxBagsPerDevice: Int = 0, maxChoicesPerItem: Int = 0, image: ImageShape = ImageShape(), video: VideoShape = VideoShape(), audio: AudioShape = AudioShape())

var tokenMaskProbability: Float

var tokenMeanSpan: Float

var replaceFraction: Float

var randomFraction: Float

var imageMaskRatio: Float

var videoMaskRatio: Float

var audioMaskRatio: Float

var textWeight: Float

var imageWeight: Float

var videoWeight: Float

var audioWeight: Float

init()

var matryoshkaDimensions: [Int]

var temperatureGroups: Int

var inverseTemperature: Float

var bias: Float

var negatives: Negatives

var ambientRepulsionWeight: Float

var maxEdgesPerDevice: Int

var pairLoss: PairLossForm

init()

var weight: Float

var width: Int

var inverseTemperature: Float

var bias: Float

var maxQuerySpan: Int

var maxQueryTokensPerDevice: Int

var maxDocumentsPerDevice: Int

var maxDocumentTokensPerDevice: Int

var pairLoss: PairLossForm

init()

var learningRate: Float

var minLearningRate: Float

var warmupSteps: Int

var steps: Int

init(learningRate: Float = 0, minLearningRate: Float = 0, warmupSteps: Int = 0, steps: Int = 0)

var offsets: [Int]

var ids: [UInt32]

var weights: [Float]?

init(offsets: [Int], ids: [UInt32], weights: [Float]? = nil)

var attract: Edges?

var repel: Edges?

var ignore: Edges?

init(attract: Edges? = nil, repel: Edges? = nil, ignore: Edges? = nil)

var step: Int

var learningRate: Float

var loss: Float

var contrastiveLoss: Float

var maskedTextLoss: Float

var maskedImageLoss: Float

var maskedVideoLoss: Float

var maskedAudioLoss: Float

var lateInteractionLoss: Float

var choicesLoss: Float

var truncated: Int

var dropped: Int

let stats: TrainerStepStats

let embeddings: Rows?

static func initVram(
    executor: Executor,
    depth: Int,
    hidden: Int,
    batch: BatchShape,
    objective: Objective = .joint,
    masking: Masking = Masking(),
    contrastive: Contrastive = Contrastive(),
    lateInteraction: LateInteraction = LateInteraction(),
    choices: Choices = Choices(),
    schedule: Schedule,
    mesh: Mesh? = nil,
    resume: String = "",
    seed: UInt64 = 0,
    progress: Progress? = nil,
    progressSteps: Int = 0
) throws(UFormError) -> Trainer

func step(
    modalities: [Modality],
    contents: [[UInt8]],
    bags: [UInt32]? = nil,
    temperatureGroups: [UInt32]? = nil,
    sides: [LateInteractionSide]? = nil,
    relations: Relations = Relations(),
    choices: [[UInt8]]? = nil,
    choiceTargets: [[Float]]? = nil,
    arena: Arena? = nil,
    outputsScalar: Scalar = .f32
) throws(UFormError) -> TrainerStep

func step(
    modalities: [Modality],
    contents: (data: [UInt8], offsets: [Int]),
    bags: [UInt32]? = nil,
    temperatureGroups: [UInt32]? = nil,
    sides: [LateInteractionSide]? = nil,
    relations: Relations = Relations(),
    choices: (data: [UInt8], offsets: [Int])? = nil,
    choiceTargets: (data: [Float], offsets: [Int])? = nil,
    arena: Arena? = nil,
    outputsScalar: Scalar = .f32
) throws(UFormError) -> TrainerStep

Applies one optimizer step over tapes already packed as data and its count + 1 Apache Arrow offsets, lent to the library in place, without a copy, until the step returns.

func save(path: String, progress: Progress? = nil, progressSteps: Int = 0) throws(UFormError)