UntypedSeries Structure Reference


                    
                    
                    Element

Declaration

Swift

public typealias Element


                    
                    
                    makeIterator()

Declaration

Swift

public func makeIterator() -> DataSeriesIterator<UntypedSeries>


                    
                    
                    prefetch(_:streamContext:)

Declaration

Swift

public func prefetch(_ i: Int, streamContext: StreamContext?)


                    
                    
                    next(_:)

Declaration

Swift

public func next(_ streamContext: StreamContext?) -> AnyObject?


                    
                    
                    underestmiatedCount

Declaration

Swift

public var underestmiatedCount: Int { get }


                    
                    
                    count

Declaration

Swift

public let count: Int


                    
                    
                    combine(size:repeating:)

Combine tensors into one tensor. This is useful for GPU batching.

Declaration

Swift

public func combine(size: Int, repeating: Int? = nil) -> DataFrame

Parameters

`size`	How many tensors to group together.
`repeating`	How many new columns to be created.

Return Value

A new dataframe with combined tensors.


                    
                    
                    toLoadImage()

Load images into tensors. It is expected to be called from a column with file paths.

Declaration

Swift

public func toLoadImage() -> DataFrame.UntypedSeries


                    
                    
                    toOneHot(_:count:onval:offval:)

Create one-hot tensors. It is expected to be called from a column with Int.

Declaration

Swift

public func toOneHot<Element: TensorNumeric>(
  _ dataType: Element.Type, count: Int, onval: Float = 1, offval: Float = 0
) -> DataFrame.UntypedSeries


                    
                    
                    toGPU(_:)

Copy tensor to GPU. It is expected to be called from a column of tensors.

Declaration

Swift

public func toGPU(_ ordinal: Int = 0) -> DataFrame.UntypedSeries


                    
                    
                    toOneSquared(maxLength:variableLength:)

Declaration

Swift

public func toOneSquared(maxLength: Int, variableLength: Bool = true) -> DataFrame.UntypedSeries


                    
                    
                    toTruncate(_:)

Declaration

Swift

public func toTruncate(_ other: DataFrame.UntypedSeries) -> DataFrame.UntypedSeries


                    
                    
                    toTruncate(_:)

Declaration

Swift

public func toTruncate<Element: AnyTensor>(_ other: DataFrame.TypedSeries<Element>)
  -> DataFrame.UntypedSeries


                    
                    
                    toImageJitter(_:size:resize:contrast:saturation:brightness:lighting:aspectRatio:symmetric:seed:centerCrop:offset:normalize:)

Apply some jitter to loaded images.

Declaration

Swift

public func toImageJitter<Element: TensorNumeric>(
  _ ofType: Element.Type, size: ImageJitter.Size, resize: ImageJitter.Resize, contrast: Float = 0,
  saturation: Float = 0, brightness: Float = 0, lighting: Float = 0, aspectRatio: Float = 0,
  symmetric: Bool = false, seed: Int = 0, centerCrop: Bool = false,
  offset: ImageJitter.Offset = ImageJitter.Offset(x: 0, y: 0),
  normalize: ImageJitter.Normalize = ImageJitter.Normalize(mean: [])
) -> DataFrame.UntypedSeries


                    
                    
                    sample(size:repeating:sampler:)

Sample existing column to create a new dataframe.

Declaration

Swift

public func sample<T, U>(size: Int, repeating: Int? = nil, sampler: @escaping ([T]) -> U)
  -> DataFrame

Parameters

`size`	How many rows to be sampled together.
`repeating`	Will we repeat the sampling to create more columns?
`sampler`	The sampling function, for example, averaging, max, first, last etc.

Return Value

A new dataframe.


                    
                    
                    from(_:)

Declaration

Swift

public static func from(_ scalar: Any) -> DataFrame.UntypedSeries


                    
                    
                    from(_:)

Create a new column from a sequence of objects.

Declaration

Swift

public static func from<S>(_ sequence: S) -> DataFrame.UntypedSeries where S : Sequence


                    
                    
                    map(_:)

Create a new column by applying some transformations on an existing column.

Declaration

Swift

public func map<T, U>(_ mapper: @escaping (T) -> U) -> DataFrame.UntypedSeries