nn

type Activation struct {
	Function  func(*mx.Symbol) *mx.Symbol
	BatchNorm bool
	Name      string
}

type Adam struct {
	Lr, Beta1, Beta2, Epsilon, Decay float64

	LrMap map[int]float64
}

type AvgPool struct {
	Kernel  mx.Dimension
	Stride  mx.Dimension
	Padding mx.Dimension
	Ceil    bool
	Name    string
	Round   int

	BatchNorm bool
}

type BatchNorm struct {
	Name           string
	Mom, Epsilon   float32
	UseGlobalStats bool
}

type Block interface {
	Combine(*mx.Symbol) *mx.Symbol
}

type BlockConcat struct {
	// contains filtered or unexported fields
}

type BlockConnect struct {
	// contains filtered or unexported fields
}

type BlockStack struct {
	// contains filtered or unexported fields
}

type Const struct {
	Value float32
}

type Convolution struct {
	Channels   int
	Kernel     mx.Dimension
	Stride     mx.Dimension
	Padding    mx.Dimension
	Activation func(*mx.Symbol) *mx.Symbol
	WeightInit mx.Inite // none by default
	BiasInit   mx.Inite // &nn.Const{0} by default
	NoBias     bool
	Groups     bool
	BatchNorm  bool
	Layout     string
	Name       string
	Round      int
	TurnOff    bool
	Output     bool
	Dropout    float32
}

type CrossEntropyLoss struct{ Num int }

type Dropout struct {
	Rate float32
}

type FeaturesMapper struct {
	// contains filtered or unexported fields
}

type Flatten struct{}

type FullyConnected struct {
	Size       int
	Activation func(*mx.Symbol) *mx.Symbol
	WeightInit mx.Inite // none by default
	BiasInit   mx.Inite // &nn.Const{0} by default
	NoBias     bool
	NoFlatten  bool
	BatchNorm  bool
	Name       string
	Output     bool
	Dropout    float32
}

type L0Loss struct{}

type L1Loss struct{ Num int }

type L2Loss struct{ Num int }

type Lambda struct {
	F func(*mx.Symbol) *mx.Symbol
}

type LcosLoss struct{ Num int }

type LossFunc func(*mx.Symbol) *mx.Symbol

type MaxPool struct {
	Kernel  mx.Dimension
	Stride  mx.Dimension
	Padding mx.Dimension
	Ceil    bool
	Name    string
	Round   int

	BatchNorm bool
}

type Model struct {
	Network   Block
	Optimizer OptimizerConf
	Loss      mx.Loss
	Input     mx.Dimension
	Seed      int
	BatchSize int
	Predicted string
	Context   mx.Context // CPU by default
}

type ModelMapFunction func(network *Network, features []string, predicts string) model.MemorizeMap

type Network struct {
	*mx.Graph

	BatchSize int
	// contains filtered or unexported fields
}

type Optimizer interface {
	Release()
	Update(params *mx.NDArray, grads *mx.NDArray)
}

type OptimizerConf interface {
	Init(epoch int) Optimizer
}

type Output struct {
	Name  string
	Round int
	Axis  int
	Begin int
	End   int
}

type ParamsReader struct {
	io.Closer
	// contains filtered or unexported fields
}

type PredictionModel struct {
	// contains filtered or unexported fields
}

type ResidualBlock struct {
	// contains filtered or unexported fields
}

type SGD struct {
	Lr, Mom, Decay float64

	LrMap map[int]float64
}

type Slice struct {
	Axis    int
	Begin   int
	End     int
	Name    string
	Output  bool
	TurnOff bool
}

type SoftmaxCrossEntropyLoss struct{}

type Uniform struct {
	Magnitude float32
}

type Xavier struct {
	Gaussian  bool
	Magnitude float32
	Factor    XavierFactor
}

type XavierFactor int