Conv2D

public var filter: Tensor<Scalar>

public var bias: Tensor<Scalar>

@noDerivative
public let activation: Activation

@noDerivative
public let strides: (Int, Int)

@noDerivative
public let padding: Padding

@noDerivative
public let dilations: (Int, Int)

public typealias Activation = @differentiable (Tensor<Scalar>) -> Tensor<Scalar>

public init(
  filter: Tensor<Scalar>,
  bias: Tensor<Scalar>? = nil,
  activation: @escaping Activation = identity,
  strides: (Int, Int) = (1, 1),
  padding: Padding = .valid,
  dilations: (Int, Int) = (1, 1)
)

@differentiable
public func forward(_ input: Tensor<Scalar>) -> Tensor<Scalar>

public init(
  filterShape: (Int, Int, Int, Int),
  strides: (Int, Int) = (1, 1),
  padding: Padding = .valid,
  dilations: (Int, Int) = (1, 1),
  activation: @escaping Activation = identity,
  useBias: Bool = true,
  filterInitializer: ParameterInitializer<Scalar> = glorotUniform(),
  biasInitializer: ParameterInitializer<Scalar> = zeros()
)