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func EucDistance ¶

func EucDistance(x, y *G.Node) (retVal *G.Node)

EucDistance is the Euclidean distance between two matrix, typically used for calculating the distance between two embedding. Case1: x, y shapes are same, no broadcast. output shape will be x.shape[:-1] Case2: x, y shapes are different, broadcast will be applied on the smaller dim. output shape will be something like x.shape[:-1] but with a broadcast dim

func FillTensorRows ¶ added in v0.3.0

func FillTensorRows(batchSize int, inputs tensor.Tensor) (x tensor.Tensor, err error)

FillTensorRows fills the batch samples with the zero data to make sample size fit the batch size it sames tensor.Concat is not optimized for large dataset. we should avoid using FillTensorRows while input data is large.

func InitForwardOnlyVm ¶

func InitForwardOnlyVm(uProfileDim, uBehaviorSize, uBehaviorDim, iFeatureDim, cFeatureDim int,
	batchSize int,
	m Model,
) (err error)

func PRelu ¶

func PRelu(x, slop *G.Node) (retVal *G.Node)

PRelu is the slop learnable LeakyRelu activation function slop should be a scalar

func Predict ¶

func Predict(m Model, numExamples, batchSize int, si *rcmd.SampleInfo, inputs tensor.Tensor) (y []float32, err error)

func Train ¶

func Train(uProfileDim, uBehaviorSize, uBehaviorDim, iFeatureDim, cFeatureDim int,
	numExamples, batchSize, epochs, earlyStop int,
	si *rcmd.SampleInfo,
	inputs, targets tensor.Tensor,

	m Model,
) (err error)