Sequential
A sequential layer that concatenates the computations of two other layers.
With function builders, a sequential layer can be used to express sequential models in a type safe way.
Example:
let model = Sequential {
Dense<Float, CPU>(inputSize: 32, outputSize: 64)
Relu<Float, CPU>()
Dense<Float, CPU>(inputSize: 64, outputSize: 10)
Softmax<Float, CPU>()
}
model will have a type Sequential<Sequential<Dense<Float, CPU>, Relu<Float, CPU>>, Sequential<Dense<Float, CPU>, Softmax<Float, CPU>>>.
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First transform
Declaration
Swift
public var first: First -
Second transform
Declaration
Swift
public var second: Second -
Tag for debugging purposes
Declaration
Swift
public var tag: String? -
Declaration
Swift
public var parameters: [Tensor<First.Parameter, First.Device>] { get } -
A sequential layer that concatenates the computations of two other layers.
Declaration
Swift
public init(first: First, second: Second)Parameters
firstFirst transform
secondSecond transform
-
Declaration
Swift
public var parameterPaths: [WritableKeyPath<`Self`, Tensor<First.Parameter, First.Device>>] { get } -
Declaration
Swift
public func callAsFunction(_ inputs: First.Inputs) -> Second.Outputs -
Creates a sequential layer with the sequence of transforms, that is specified in the provided layer builder builder closure.
Example:
Sequential { Dense<Float, CPU>(inputSize: 32, outputSize: 64) Relu<Float, CPU>() Dense<Float, CPU>(inputSize: 64, outputSize: 10) Softmax<Float, CPU>() }Declaration
Swift
init(@LayerBuilder _ build: () -> `Self`)Parameters
buildBuild block (function builder)
View on GitHub
Sequential Structure Reference