mx

package
v0.0.0-...-5f5c69f Latest Latest
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This package is not in the latest version of its module.

 Go to latest Published: Apr 28, 2020 License: Apache-2.0 Imports: 15 Imported by: 0

Documentation

Index

Constants

View Source 
const (
	DimRow    = 0
	DimColumn = 1
	DimDepth  = 2
	DimDepth3 = 3
)
View Source 
const (
	VersionMajor = 1
	VersionMinor = 5
	VersionPatch = 0
)
View Source 
const (
	OpVar_    capi.MxnetOp = -1
	OpInput_  capi.MxnetOp = -2
	OpScalar_ capi.MxnetOp = -4
	OpNogVar_ capi.MxnetOp = -5
	OpGroup_  capi.MxnetOp = -7
	OpRef_    capi.MxnetOp = -8
	OpOutput_ capi.MxnetOp = -9
	OpBound_  capi.MxnetOp = -10
	OpDepend_ capi.MxnetOp = -11
	OpLink_   capi.MxnetOp = -12
)
View Source 
const MaxDimensionCount = 4

do not change this constant code can assume exactly this value

View Source 
const Version fu.VersionType = VersionMajor*10000 + VersionMinor*100 + VersionPatch

Variables

This section is empty.

Functions

func AdamUpdate 

func AdamUpdate(params, grads, mean, variance *NDArray, lr, beta1, beta2, epsilon, wd float64)

func GpuCount 

func GpuCount() int

func LibVersion 

func LibVersion() fu.VersionType

func Nograd 

func Nograd(_hidden_nograd_)

func RandomSeed 

func RandomSeed(seed int)

func SgdMomUpdate 

func SgdMomUpdate(params, grads, mom *NDArray, lr, momentum, wd float64)

func SgdUpdate 

func SgdUpdate(params, grads *NDArray, lr, wd float64)

Types

type ActivationType 

type ActivationType int
const (
	ActivReLU ActivationType = iota
	ActivSoftReLU
	ActivSoftSign
	ActivSigmoid
	ActivTanh
)

type Context 

type Context int
const (
	NullContext Context = 0
	CPU         Context = 1
	GPU         Context = 2
	GPU0        Context = 2
	GPU1        Context = 1002
)

func Gpu 

func Gpu(no int) Context

func (Context) Array 

func (c Context) Array(tp Dtype, d Dimension, vals ...interface{}) *NDArray

func (Context) CopyAs 

func (c Context) CopyAs(a *NDArray, dtype Dtype) *NDArray

func (Context) DevNo 

func (c Context) DevNo() int

func (Context) DevType 

func (c Context) DevType() int

func (Context) IsGPU 

func (c Context) IsGPU() bool

func (Context) RandomSeed 

func (c Context) RandomSeed(seed int)

func (Context) String 

func (c Context) String() string

func (Context) Upgrade 

func (c Context) Upgrade() Context

type Dimension 

type Dimension struct {
	Shape [MaxDimensionCount]int `yaml:"shape,flow"`
	Len   int                    `yaml:"len"`
}

Array Dimension

func Dim 

func Dim(a ...int) Dimension

creates new dimension object

func DimensionFromString 

func DimensionFromString(s string) (Dimension, error)

func (Dimension) Empty 

func (dim Dimension) Empty() bool

func (Dimension) Good 

func (dim Dimension) Good() bool

check array dimension

func (Dimension) Like 

func (dim Dimension) Like(b Dimension) Dimension

func (Dimension) Push 

func (dim Dimension) Push(i int) Dimension

func (Dimension) SizeOf 

func (dim Dimension) SizeOf(dt Dtype) int

sizeof whole array data

func (Dimension) Skip 

func (dim Dimension) Skip(n int) Dimension

func (Dimension) Slice 

func (dim Dimension) Slice() []int

func (Dimension) String 

func (dim Dimension) String() string

represent array dimension as string

func (Dimension) Total 

func (dim Dimension) Total() int

total elements in the whole array

type Dtype 

type Dtype int
const (
	Float32 Dtype = 0
	Float64 Dtype = 1
	Float16 Dtype = 2
	Uint8   Dtype = 3
	Int32   Dtype = 4
	Int8    Dtype = 5
	Int64   Dtype = 6
)

func (Dtype) Size 

func (tp Dtype) Size() int

func (Dtype) String 

func (tp Dtype) String() string

type Graph 

type Graph struct {
	Ctx   Context
	Dtype Dtype

	Input  *NDArray // network input referencing to Params["_input"]
	Output *NDArray // referencing to Outputs["_output_output"]
	Loss   *NDArray // referencing to Outputs["_loss_loss"]
	Label  *NDArray // loss function label referencing to Params["_label"]

	Outputs  map[string]*NDArray  // referencing to executor outputs except loss
	Params   map[string]*NDArray  // network parameters
	Shapes   map[string]Dimension // predefined param shape
	Autograd map[string]bool      // if param can be trained
	Grads    map[string]*NDArray  // training gradients

	Exec         capi.ExecutorHandle
	Initializers map[string]Inite
	Initialized  bool
	// contains filtered or unexported fields
}

func Compose 

func Compose(
	ctx Context,
	sym *Symbol,
	loss Loss,
	input Dimension,
	dtype Dtype) *Graph

func (*Graph) Backward 

func (g *Graph) Backward()

func (*Graph) Forward 

func (g *Graph) Forward(train bool)

func (*Graph) GetShapes 

func (g *Graph) GetShapes(withLoss bool) map[string][]int

func (*Graph) Identity 

func (g *Graph) Identity() GraphIdentity

func (*Graph) InitParam 

func (g *Graph) InitParam(name string)

func (*Graph) Initialize 

func (g *Graph) Initialize(seed int, inite func(*NDArray, string))

func (*Graph) LogSummary 

func (g *Graph) LogSummary(withLoss bool)

func (*Graph) NextSymbolId 

func (g *Graph) NextSymbolId() int

func (*Graph) PrintSummary 

func (g *Graph) PrintSummary(withLoss bool)

func (*Graph) Release 

func (g *Graph) Release()

func (*Graph) Summary 

func (g *Graph) Summary(withLoss bool) Summary

func (*Graph) SummaryOut 

func (g *Graph) SummaryOut(withLoss bool, out func(string))

func (*Graph) ToJson 

func (g *Graph) ToJson(withLoss bool) []byte

type GraphIdentity 

type GraphIdentity [20]byte // SHA1

func (GraphIdentity) String 

func (identity GraphIdentity) String() string

type GraphJs 

type GraphJs struct {
	Nodes []struct {
		Op     string
		Name   string
		Attrs  map[string]string
		Inputs []interface{}
	}
}

type Inite 

type Inite interface {
	Inite(*NDArray)
}

type Loss 

type Loss interface {
	// out => loss
	Loss(*Symbol) *Symbol
}

type NDArray 

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

func Array 

func Array(tp Dtype, d Dimension) *NDArray

func (*NDArray) Cast 

func (a *NDArray) Cast(dt Dtype) *NDArray

func (*NDArray) Context 

func (a *NDArray) Context() Context

func (*NDArray) CopyValuesTo 

func (a *NDArray) CopyValuesTo(dst interface{})

func (*NDArray) Depth 

func (a *NDArray) Depth() int

func (*NDArray) Dim 

func (a *NDArray) Dim() Dimension

func (*NDArray) Dtype 

func (a *NDArray) Dtype() Dtype

func (*NDArray) Fill 

func (a *NDArray) Fill(value float32) *NDArray

func (*NDArray) Len 

func (a *NDArray) Len(d int) int

func (*NDArray) NewLikeThis 

func (a *NDArray) NewLikeThis() *NDArray

func (*NDArray) Normal 

func (a *NDArray) Normal(mean float32, scale float32) *NDArray

func (*NDArray) Ones 

func (a *NDArray) Ones() *NDArray

func (*NDArray) Raw 

func (a *NDArray) Raw() []byte

func (*NDArray) ReCopyValuesTo 

func (a *NDArray) ReCopyValuesTo(dst interface{})

func (*NDArray) Release 

func (a *NDArray) Release()

func (*NDArray) Reshape 

func (a *NDArray) Reshape(dim Dimension) *NDArray

func (*NDArray) SetValues 

func (a *NDArray) SetValues(vals ...interface{})

func (*NDArray) Size 

func (a *NDArray) Size() int

func (*NDArray) String 

func (a *NDArray) String() string

func (*NDArray) Uniform 

func (a *NDArray) Uniform(low float32, high float32) *NDArray

func (*NDArray) Values 

func (a *NDArray) Values(dtype Dtype) interface{}

func (*NDArray) ValuesF32 

func (a *NDArray) ValuesF32() []float32

func (*NDArray) Xavier 

func (a *NDArray) Xavier(gaussian bool, factor int, magnitude float32) *NDArray

func (*NDArray) Zeros 

func (a *NDArray) Zeros() *NDArray

type Param 

type Param struct {
	Data     *NDArray
	Grad     *NDArray
	Shape    Dimension
	Autograd bool
}

type Summary 

type Summary []SummaryRow

func (Summary) Print 

func (sry Summary) Print(out func(string))

type SummaryRow 

type SummaryRow struct {
	No        int         `yaml:"no"`
	Name      string      `yaml:"name"`
	Operation string      `yaml:"op"`
	Params    int         `yaml:"params"`
	Dim       Dimension   `yaml:"dimension"`
	Args      []SummryArg `yaml:"args"`
}

type SummryArg 

type SummryArg struct {
	No   int    `yaml:"no""`
	Name string `yaml:"name"`
}

type Symbol 

type Symbol struct {
	Op     capi.MxnetOp             `yaml:"op"`
	Value  string                   `yaml:"value"`
	Name   string                   `yaml:"name"`
	Args   []*Symbol                `yaml:"args"`
	Init   Inite                    `yaml:"-"`
	Attr   map[capi.MxnetKey]string `yaml:"attr"`
	Dim    Dimension                `yaml:"dim"`
	Output bool                     `yaml:"output"`
}

func Abs 

func Abs(a *Symbol) *Symbol

func Activation 

func Activation(a *Symbol, actType ActivationType) *Symbol

func Add 

func Add(lv interface{}, rv interface{}) *Symbol

func And 

func And(a *Symbol, b *Symbol) *Symbol

func BatchNorm 

func BatchNorm(a, gamma, beta, rmean, rvar *Symbol, mom, eps float32, useGlobalStats bool, axis ...int) *Symbol

func BcastAdd 

func BcastAdd(a, b *Symbol) *Symbol

func BcastDiv 

func BcastDiv(a, b *Symbol) *Symbol

func BcastMul 

func BcastMul(a, b *Symbol) *Symbol

func BcastSub 

func BcastSub(a, b *Symbol) *Symbol

func BlockGrad 

func BlockGrad(s *Symbol) *Symbol

func Bound 

func Bound(a ...*Symbol) *Symbol

func Channel 

func Channel(a *Symbol, ch int) *Symbol

func Concat 

func Concat(a ...*Symbol) *Symbol

func Conv 

func Conv(a, weight, bias *Symbol, channels int, kernel, stride, padding Dimension, groups bool, layout string) *Symbol

func Cosh 

func Cosh(a *Symbol) *Symbol

func Depend 

func Depend(a ...*Symbol) *Symbol

func Div 

func Div(lv interface{}, rv interface{}) *Symbol

func Dot 

func Dot(lv interface{}, rv interface{}) *Symbol

func Dropout 

func Dropout(a *Symbol, rate float32) *Symbol

func EQ 

func EQ(a *Symbol, rv interface{}) *Symbol

func Exp 

func Exp(a *Symbol) *Symbol

func Flatten 

func Flatten(a *Symbol) *Symbol

func FullyConnected 

func FullyConnected(a, weight, bias *Symbol, size int, flatten bool) *Symbol

func GE 

func GE(a *Symbol, rv interface{}) *Symbol

func GenericOp1 

func GenericOp1(op, opScalar capi.MxnetOp, l *Symbol, rv interface{}) *Symbol

func GenericOp2 

func GenericOp2(op, opScalar, opScalarR capi.MxnetOp, lv interface{}, rv interface{}) *Symbol

func Greater 

func Greater(a *Symbol, rv interface{}) *Symbol

func Group 

func Group(a ...*Symbol) *Symbol

func HardSigmoid 

func HardSigmoid(a *Symbol) *Symbol

func Input 

func Input(..._hidden_input_) *Symbol

func LE 

func LE(a *Symbol, rv interface{}) *Symbol

func Lesser 

func Lesser(a *Symbol, rv interface{}) *Symbol
func Link(name string) *Symbol

func Log 

func Log(a *Symbol) *Symbol

func LogCosh 

func LogCosh(a *Symbol) *Symbol

func LogSoftmax 

func LogSoftmax(a *Symbol, axis ...int) *Symbol

func MakeLoss 

func MakeLoss(s *Symbol) *Symbol

func Mean 

func Mean(a *Symbol, axis ...int) *Symbol

func MeanKd 

func MeanKd(a *Symbol, axis ...int) *Symbol

func MeanXl 

func MeanXl(a *Symbol, axis ...int) *Symbol

func Minus 

func Minus(a *Symbol) *Symbol

func Mul 

func Mul(lv interface{}, rv interface{}) *Symbol

func NE 

func NE(a *Symbol, rv interface{}) *Symbol

func Normal 

func Normal(loc, scale float32, dim ...int) *Symbol

func Not 

func Not(a *Symbol) *Symbol

func Ones 

func Ones(dim ...int) *Symbol

func OnesLike 

func OnesLike(a *Symbol) *Symbol

func Or 

func Or(a *Symbol, b *Symbol) *Symbol

func Output 

func Output(a *Symbol, name string) *Symbol

func Pick 

func Pick(a *Symbol, label *Symbol) *Symbol

func Pool 

func Pool(a *Symbol, kernel, stride, padding Dimension, ceil bool, maxpool bool) *Symbol

func Pow 

func Pow(lv interface{}, rv interface{}) *Symbol

func ReLU 

func ReLU(a *Symbol) *Symbol

func Ref 

func Ref(name string, a ...*Symbol) *Symbol

func Reshape 

func Reshape(a *Symbol, dim ...int) *Symbol

func ReshapeLike 

func ReshapeLike(a, b *Symbol) *Symbol

func Sigmoid 

func Sigmoid(a *Symbol) *Symbol

func Sin 

func Sin(a *Symbol) *Symbol

func Slice 

func Slice(a *Symbol, axis, begin, end int) *Symbol

func Softmax 

func Softmax(a *Symbol, axis ...int) *Symbol

func SoftmaxActivation 

func SoftmaxActivation(a *Symbol, channel bool) *Symbol

func SoftmaxCrossEntropy 

func SoftmaxCrossEntropy(a, b *Symbol, axis ...int) *Symbol

func SoftmaxOutput 

func SoftmaxOutput(a *Symbol, l *Symbol, multiOutput bool) *Symbol

func Sqrt 

func Sqrt(a *Symbol) *Symbol

func Square 

func Square(a *Symbol) *Symbol

func Stack 

func Stack(a ...*Symbol) *Symbol

func Stack1 

func Stack1(a ...*Symbol) *Symbol

func Sub 

func Sub(lv interface{}, rv interface{}) *Symbol

func Sum 

func Sum(a *Symbol, axis ...int) *Symbol

func Sum1 

func Sum1(a *Symbol) *Symbol

func SumNan 

func SumNan(a *Symbol, axis ...int) *Symbol

func SumXl 

func SumXl(a *Symbol, axis ...int) *Symbol

func SwapAxes 

func SwapAxes(a *Symbol, x, y int) *Symbol

func SymbolCast 

func SymbolCast(i interface{}) (*Symbol, error)

func Tanh 

func Tanh(a *Symbol) *Symbol

func Transpose 

func Transpose(a *Symbol, axis ...int) *Symbol

func Value 

func Value(name string, a ...float32) *Symbol

func Var 

func Var(name string, opt ...interface{}) *Symbol

func Xor 

func Xor(a *Symbol, b *Symbol) *Symbol

func Zeros 

func Zeros(dim ...int) *Symbol

func ZerosLike 

func ZerosLike(a *Symbol) *Symbol

func (*Symbol) SetName 

func (s *Symbol) SetName(name string) *Symbol

func (*Symbol) SetOutput 

func (s *Symbol) SetOutput(on bool) *Symbol

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