Class ReferenceCPUOps

Reference CPU implementation of IOps

Inheritance

Object

ReferenceCPUOps

PixelShaderOps

ReferenceComputeOps

UnsafeArrayCPUOps

Namespace: Unity.Barracuda

Syntax

public class ReferenceCPUOps : object, IOps, IOpsStatistics

Constructors

ReferenceCPUOps(ITensorAllocator)

Create ReferenceCPUOps

Declaration

public ReferenceCPUOps(ITensorAllocator allocator = null)

Parameters

Type	Name	Description
ITensorAllocator	allocator	allocator

Methods

Abs(Tensor)

Abs

Declaration

public virtual Tensor Abs(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Abs(Tensor)

Acos(Tensor)

Acos

Declaration

public virtual Tensor Acos(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Acos(Tensor)

Acosh(Tensor)

Acosh

Declaration

public virtual Tensor Acosh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Acosh(Tensor)

Add(Tensor[])

Add tensors together

Declaration

public virtual Tensor Add(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Add(Tensor[])

ArgMax(Tensor, Int32)

ArgMax

Declaration

public virtual Tensor ArgMax(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ArgMax(Tensor, Int32)

ArgMin(Tensor, Int32)

ArgMax

Declaration

public virtual Tensor ArgMin(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ArgMin(Tensor, Int32)

Asin(Tensor)

Asin

Declaration

public virtual Tensor Asin(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Asin(Tensor)

Asinh(Tensor)

Asinh

Declaration

public virtual Tensor Asinh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Asinh(Tensor)

Atan(Tensor)

Atan

Declaration

public virtual Tensor Atan(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Atan(Tensor)

Atanh(Tensor)

Atanh

Declaration

public virtual Tensor Atanh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Atanh(Tensor)

AvgPool2D(Tensor, Int32[], Int32[], Int32[])

2D average pooling

Declaration

public virtual Tensor AvgPool2D(Tensor X, int[] pool, int[] stride, int[] pad)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pool	pooling
Int32[]	stride	stride
Int32[]	pad	padding

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.AvgPool2D(Tensor, Int32[], Int32[], Int32[])

Bernoulli(Single)

Bernoulli distribution

Declaration

protected float Bernoulli(float p)

Parameters

Type	Name	Description
Single	p	p

Returns

Type	Description
Single	random value

Border2D(Tensor, Int32[], Single)

2D border padding

Declaration

public virtual Tensor Border2D(Tensor X, int[] pad, float value)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pad	padding
Single	value

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Border2D(Tensor, Int32[], Single)

Border3D(Tensor, Int32[], Single)

3D border padding

Declaration

public virtual Tensor Border3D(Tensor X, int[] pad, float value)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pad	padding
Single	value

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Border3D(Tensor, Int32[], Single)

Ceil(Tensor)

Ceil

Declaration

public virtual Tensor Ceil(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Ceil(Tensor)

Clip(Tensor, Single, Single)

Clip

Declaration

public virtual Tensor Clip(Tensor X, float min, float max)

Parameters

Type	Name	Description
Tensor	X
Single	min	min value
Single	max	max value

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Clip(Tensor, Single, Single)

Concat(Tensor[], Int32)

Concatenate tensors across axis

Declaration

public virtual Tensor Concat(Tensor[] tensors, int axis)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Concat(Tensor[], Int32)

ConstantOfShape(TensorShape, DataType, Single)

Creates a constant of shape input

Declaration

public virtual Tensor ConstantOfShape(TensorShape X, DataType type, float value = 0F)

Parameters

Type	Name	Description
TensorShape	X	input shape
DataType	type	Tensor DataType
Single	value	value

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ConstantOfShape(TensorShape, DataType, Single)

Conv2D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

2D convolution

Declaration

public virtual Tensor Conv2D(Tensor X, Tensor K, Tensor B, int[] stride, int[] pad, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	K
Tensor	B
Int32[]	stride	stride
Int32[]	pad	padding
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Conv2D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

Conv2DTrans(Tensor, Tensor, Tensor, Int32[], Int32[], Int32[], Layer.FusedActivation)

Transpose 2D convolution

Declaration

public virtual Tensor Conv2DTrans(Tensor X, Tensor K, Tensor B, int[] stride, int[] pad, int[] outputAdjustment, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	K
Tensor	B
Int32[]	stride	stride
Int32[]	pad	padding
Int32[]	outputAdjustment	output adjustments
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Conv2DTrans(Tensor, Tensor, Tensor, Int32[], Int32[], Int32[], Layer.FusedActivation)

Conv3D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

3D convolution

Declaration

public virtual Tensor Conv3D(Tensor X, Tensor K, Tensor B, int[] stride, int[] pad, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	K
Tensor	B
Int32[]	stride	stride
Int32[]	pad	padding
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Conv3D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

Copy(Tensor)

Copy

Declaration

public virtual Tensor Copy(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Copy(Tensor)

CopyAndReshape(Tensor, TensorShape)

Copy and reshape Tensor

Declaration

protected virtual Tensor CopyAndReshape(Tensor X, TensorShape shape)

Parameters

Type	Name	Description
Tensor	X	input
TensorShape	shape	shape

Returns

Type	Description
Tensor	output Tensor

Cos(Tensor)

Cos

Declaration

public virtual Tensor Cos(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Cos(Tensor)

Cosh(Tensor)

Cosh

Declaration

public virtual Tensor Cosh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Cosh(Tensor)

Dense(Tensor, Tensor, Tensor, Layer.FusedActivation)

Dense layer (matrix multiplication) o = x ⨯ w + b

Declaration

public virtual Tensor Dense(Tensor X, Tensor W, Tensor B, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	W
Tensor	B
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Dense(Tensor, Tensor, Tensor, Layer.FusedActivation)

Dense3(Tensor, Tensor, Tensor)

rank3 Dense layer (matrix multiplication) o = x ⨯ w + b O: N,,W,C / X: N,,W,C / W:N,,,C / B:N,,,_

Declaration

public virtual Tensor Dense3(Tensor X, Tensor W, Tensor B)

Parameters

Type	Name	Description
Tensor	X
Tensor	W
Tensor	B

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Dense3(Tensor, Tensor, Tensor)

DepthToSpace(Tensor, Int32[], Layer.DepthToSpaceMode)

Depth to space

Declaration

public virtual Tensor DepthToSpace(Tensor X, int[] blocksize, Layer.DepthToSpaceMode mode)

Parameters

Type	Name	Description
Tensor	X
Int32[]	blocksize
Layer.DepthToSpaceMode	mode	mode

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.DepthToSpace(Tensor, Int32[], Layer.DepthToSpaceMode)

DepthwiseConv2D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

Depthwise 2D convolution

Declaration

public virtual Tensor DepthwiseConv2D(Tensor X, Tensor K, Tensor B, int[] stride, int[] pad, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	K
Tensor	B
Int32[]	stride	stride
Int32[]	pad	padding
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.DepthwiseConv2D(Tensor, Tensor, Tensor, Int32[], Int32[], Layer.FusedActivation)

Div(Tensor[])

Divide tensors o = tensors[0] / tensors[1] / ... / tensors[N-1]

Declaration

public virtual Tensor Div(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Div(Tensor[])

Dropout(Tensor, Single)

Dropout

Declaration

public virtual Tensor Dropout(Tensor X, float alpha)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Dropout(Tensor, Single)

Elu(Tensor, Single)

ELU

Declaration

public virtual Tensor Elu(Tensor X, float alpha)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Elu(Tensor, Single)

Equal(Tensor, Tensor)

Equal

Declaration

public virtual Tensor Equal(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a == b

Implements

IOps.Equal(Tensor, Tensor)

Erf(Tensor)

Erf

Declaration

public virtual Tensor Erf(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Erf(Tensor)

Exp(Tensor)

Exponent e^x

Declaration

public virtual Tensor Exp(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Exp(Tensor)

Expand(Tensor, TensorShape)

Expand

Declaration

public virtual Tensor Expand(Tensor X, TensorShape newShape)

Parameters

Type	Name	Description
Tensor	X
TensorShape	newShape

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Expand(Tensor, TensorShape)

Flatten(Tensor)

Flatten

Declaration

public virtual Tensor Flatten(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Flatten(Tensor)

Floor(Tensor)

Floor

Declaration

public virtual Tensor Floor(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Floor(Tensor)

Gather(Tensor[], Int32)

Gather

Declaration

public virtual Tensor Gather(Tensor[] tensors, int axis)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Gather(Tensor[], Int32)

Gaussian(Single, Single)

Gaussian distribution

Declaration

protected float Gaussian(float mean, float stdDev)

Parameters

Type	Name	Description
Single	mean	mean
Single	stdDev	standard deviation

Returns

Type	Description
Single	random value

GetModelExecutionsReporter()

Get model executions reporter

Declaration

public IModelExecutionsReporter GetModelExecutionsReporter()

Returns

Type	Description
IModelExecutionsReporter	model executions reporter

Implements

IOps.GetModelExecutionsReporter()

GlobalAvgPool2D(Tensor)

2D global average pooling

Declaration

public virtual Tensor GlobalAvgPool2D(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.GlobalAvgPool2D(Tensor)

GlobalAvgVariancePool2D(Tensor)

2D global average variance pooling

Declaration

public virtual Tensor GlobalAvgVariancePool2D(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.GlobalAvgVariancePool2D(Tensor)

GlobalMaxPool2D(Tensor)

2D global max pooling

Declaration

public virtual Tensor GlobalMaxPool2D(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.GlobalMaxPool2D(Tensor)

Greater(Tensor, Tensor)

Greater

Declaration

public virtual Tensor Greater(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a > b

Implements

IOps.Greater(Tensor, Tensor)

GreaterEqual(Tensor, Tensor)

Greater or equal

Declaration

public virtual Tensor GreaterEqual(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a >= b

Implements

IOps.GreaterEqual(Tensor, Tensor)

HardSigmoid(Tensor, Single, Single)

HardSigmoid

Declaration

public virtual Tensor HardSigmoid(Tensor X, float alpha, float beta)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha
Single	beta

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.HardSigmoid(Tensor, Single, Single)

IsFusedActivationSupported(Layer.FusedActivation)

Check if fusedActivation is supported in-place

Declaration

protected virtual bool IsFusedActivationSupported(Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Boolean	true if supported in-place

LeakyRelu(Tensor, Single)

Leaky ReLU

Declaration

public virtual Tensor LeakyRelu(Tensor X, float alpha)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.LeakyRelu(Tensor, Single)

Less(Tensor, Tensor)

Less

Declaration

public virtual Tensor Less(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a < b

Implements

IOps.Less(Tensor, Tensor)

LessEqual(Tensor, Tensor)

Less or equal

Declaration

public virtual Tensor LessEqual(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a < b

Implements

IOps.LessEqual(Tensor, Tensor)

Log(Tensor)

Log

Declaration

public virtual Tensor Log(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Log(Tensor)

LogicalAnd(Tensor, Tensor)

And

Declaration

public virtual Tensor LogicalAnd(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a && b

Implements

IOps.LogicalAnd(Tensor, Tensor)

LogicalNot(Tensor)

Not

Declaration

public virtual Tensor LogicalNot(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	Tensor with !x values

Implements

IOps.LogicalNot(Tensor)

LogicalOr(Tensor, Tensor)

Or

Declaration

public virtual Tensor LogicalOr(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a || b

Implements

IOps.LogicalOr(Tensor, Tensor)

LogicalXor(Tensor, Tensor)

Xor

Declaration

public virtual Tensor LogicalXor(Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with true where a xor b

Implements

IOps.LogicalXor(Tensor, Tensor)

LogSoftmax(Tensor, Int32)

LogSoftmax

Declaration

public virtual Tensor LogSoftmax(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.LogSoftmax(Tensor, Int32)

LRN(Tensor, Single, Single, Single, Int32)

LRN (Local Response Normalization)

Declaration

public virtual Tensor LRN(Tensor X, float alpha, float beta, float bias, int size)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha
Single	beta	beta
Single	bias	bias
Int32	size	size

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.LRN(Tensor, Single, Single, Single, Int32)

LSTM(Tensor, Tensor[], Tensor[], Tensor[], Tensor[], Tensor, Tensor)

LSTM

Declaration

public virtual Tensor[] LSTM(Tensor X, Tensor[] W, Tensor[] R, Tensor[] Wb, Tensor[] Rb, Tensor hidden, Tensor cell)

Parameters

Type	Name	Description
Tensor	X	The input sequences packed into one 3-D tensor.
Tensor[]	W	W parameter weight matrix for input, output, forget, and cell gates - W[iofc]
Tensor[]	R	R recurrence weight matrix for input, output, forget, and cell gates - R[iofc]
Tensor[]	Wb	W bias vectors for input, output, forget, and cell gates - Wb[iofc]
Tensor[]	Rb	R bias vectors for input, output, forget, and cell gates - Rb[iofc]
Tensor	hidden	Initial value of the hidden
Tensor	cell	Initial value of the cell

Returns

Type	Description
Tensor[]	[Y (concatenated intermediate values of the hidden), Y_h (final hidden), Y_c (final cell)]

Implements

IOps.LSTM(Tensor, Tensor[], Tensor[], Tensor[], Tensor[], Tensor, Tensor)

MatMul(Tensor, Boolean, Tensor, Boolean)

Simple 2D matrix multiplication O = X ⨯ Y

Declaration

public virtual Tensor MatMul(Tensor X, bool xTranspose, Tensor Y, bool yTranspose)

Parameters

Type	Name	Description
Tensor	X	left Tensor
Boolean	xTranspose	X transposed data flag
Tensor	Y	right Tensor
Boolean	yTranspose	Y transposed data flag

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.MatMul(Tensor, Boolean, Tensor, Boolean)

MatMul(Tensor, Int32, Tensor, Int32)

Multidimensional Matrix multiplication o = x ⨯ y

Declaration

public virtual Tensor MatMul(Tensor X, int rankX, Tensor Y, int rankY)

Parameters

Type	Name	Description
Tensor	X
Int32	rankX	rank of x
Tensor	Y
Int32	rankY	rank of y

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.MatMul(Tensor, Int32, Tensor, Int32)

Max(Tensor[])

Max

Declaration

public virtual Tensor Max(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Max(Tensor[])

MaxPool2D(Tensor, Int32[], Int32[], Int32[])

2D max pooling

Declaration

public virtual Tensor MaxPool2D(Tensor X, int[] pool, int[] stride, int[] pad)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pool	pooling
Int32[]	stride	stride
Int32[]	pad	padding

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.MaxPool2D(Tensor, Int32[], Int32[], Int32[])

Mean(Tensor[])

Mean

Declaration

public virtual Tensor Mean(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Mean(Tensor[])

Min(Tensor[])

Min

Declaration

public virtual Tensor Min(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Min(Tensor[])

Mul(Tensor[])

Multiply tensors together

Declaration

public virtual Tensor Mul(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Mul(Tensor[])

Multinomial(Tensor, Int32, Int32)

Multinomial random distribution

Declaration

public virtual Tensor Multinomial(Tensor X, int count, int seed)

Parameters

Type	Name	Description
Tensor	X
Int32	count	count
Int32	seed	seed

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Multinomial(Tensor, Int32, Int32)

Neg(Tensor)

Neg

Declaration

public virtual Tensor Neg(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Neg(Tensor)

NewOutputTensor(DataType, TensorShape, String)

Allocate new Tensor via allocator using AllocScope.LayerOutput scope

Declaration

protected Tensor NewOutputTensor(DataType type, TensorShape s, string name = "")

Parameters

Type	Name	Description
DataType	type	data type
TensorShape	s	shape of the tensor to be created
String	name	tensor name

Returns

Type	Description
Tensor	new Tensor

NewTempTensor(DataType, TensorShape, String)

Allocate new Tensor via allocator using AllocScope.InternalToLayer scope

Declaration

protected Tensor NewTempTensor(DataType type, TensorShape s, string name = "")

Parameters

Type	Name	Description
DataType	type	data type
TensorShape	s	shape of the tensor to be created
String	name	tensor name

Returns

Type	Description
Tensor	new Tensor

NewTensor(DataType, TensorShape, AllocScope, String)

Allocate new Tensor via allocator

Declaration

protected Tensor NewTensor(DataType dataType, TensorShape s, AllocScope scope, string name = "")

Parameters

Type	Name	Description
DataType	dataType	data type
TensorShape	s	shape
AllocScope	scope	tensor lifetime scope
String	name	name

Returns

Type	Description
Tensor	new Tensor

NewTensorForFusedActivation(DataType, TensorShape, Layer.FusedActivation)

Allocate new Tensor via allocator tensor lifetime will be OutputLayer if activation is supported in place, InternalToLayer otherwise.

Declaration

protected Tensor NewTensorForFusedActivation(DataType dataType, TensorShape shape, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
DataType	dataType	data type
TensorShape	shape	shape of the tensor to be created
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	new Tensor

NewTensorLike(Tensor, AllocScope)

Allocate new Tensor similar to specified Tensor t

Declaration

protected Tensor NewTensorLike(Tensor t, AllocScope scope)

Parameters

Type	Name	Description
Tensor	t	Tensor
AllocScope	scope	tensor lifetime scope

Returns

Type	Description
Tensor	new Tensor

NewTensorLike(Tensor[], AllocScope, Boolean)

Allocate new Tensor corresponding to max shape of specified tensors

Declaration

protected Tensor NewTensorLike(Tensor[] tensors, AllocScope scope, bool validateType = true)

Parameters

Type	Name	Description
Tensor[]	tensors	tensors
AllocScope	scope	tensor lifetime scope
Boolean	validateType	should this method validate that all tensors are the same type

Returns

Type	Description
Tensor	new Tensor

NonMaxSuppression(Tensor[], Int32, Single, Single, Int32)

Non max suppression tensors[0] - boxes, tensors[1] - scores

Declaration

public Tensor NonMaxSuppression(Tensor[] tensors, int maxOutputBoxesPerClass, float iouThreshold, float scoreThreshold, int centerPointBox)

Parameters

Type	Name	Description
Tensor[]	tensors
Int32	maxOutputBoxesPerClass	max output boxes per class
Single	iouThreshold	IOU (Intersection Over Union) threshold
Single	scoreThreshold	score threshold
Int32	centerPointBox	center point box

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.NonMaxSuppression(Tensor[], Int32, Single, Single, Int32)

NonZero(Tensor)

Indices for non zero values

Declaration

public Tensor NonZero(Tensor X)

Parameters

Type	Name	Description
Tensor	X	input

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.NonZero(Tensor)

Normalization(Tensor, Tensor, Tensor, Int32, Int32, Single, Layer.FusedActivation)

Normalization

Declaration

public virtual Tensor Normalization(Tensor X, Tensor S, Tensor B, int pool, int axis, float epsilon, Layer.FusedActivation fusedActivation)

Parameters

Type	Name	Description
Tensor	X
Tensor	S
Tensor	B
Int32	pool	pooling
Int32	axis	axis
Single	epsilon	threshold
Layer.FusedActivation	fusedActivation	fused activation type

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Normalization(Tensor, Tensor, Tensor, Int32, Int32, Single, Layer.FusedActivation)

OneHot(Tensor, Int32, Single, Single, Int32)

One hot

Declaration

public virtual Tensor OneHot(Tensor X, int depth, float onValue, float offValue, int inputRank = null)

Parameters

Type	Name	Description
Tensor	X
Int32	depth	output depth
Single	onValue	on value
Single	offValue	off value
Int32	inputRank	input rank helper

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.OneHot(Tensor, Int32, Single, Single, Int32)

Pad2DEdge(Tensor, Int32[])

Edge padding

Declaration

public virtual Tensor Pad2DEdge(Tensor X, int[] pad)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pad	padding

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Pad2DEdge(Tensor, Int32[])

Pad2DReflect(Tensor, Int32[])

Reflection padding

Declaration

public virtual Tensor Pad2DReflect(Tensor X, int[] pad)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pad	padding

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Pad2DReflect(Tensor, Int32[])

Pad2DSymmetric(Tensor, Int32[])

Symmetric padding

Declaration

public virtual Tensor Pad2DSymmetric(Tensor X, int[] pad)

Parameters

Type	Name	Description
Tensor	X
Int32[]	pad	padding

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Pad2DSymmetric(Tensor, Int32[])

PostLayerCleanup()

Called after every layer execution. It allows IOps to run cleanup operations such as clearing temporary buffers only used in the scope of the last layer executed.

Declaration

public virtual void PostLayerCleanup()

Implements

IOps.PostLayerCleanup()

Pow(Tensor, Single)

Power

Declaration

public virtual Tensor Pow(Tensor X, float alpha)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Pow(Tensor, Single)

Pow(Tensor[])

Raise tensors to the power o =tensors[0] ^ tensors[1] ^ ... ^ tensors[N-1]

Declaration

public virtual Tensor Pow(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Pow(Tensor[])

PRelu(Tensor, Tensor)

PReLU

Declaration

public virtual Tensor PRelu(Tensor X, Tensor S)

Parameters

Type	Name	Description
Tensor	X
Tensor	S

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.PRelu(Tensor, Tensor)

Prepare(Tensor)

Prepares tensor for use

Declaration

public virtual Tensor Prepare(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	Tensor

Implements

IOps.Prepare(Tensor)

PrepareNoAlloc(Tensor)

Prepares tensor for use without uploading internal data to device

Declaration

public virtual Tensor PrepareNoAlloc(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	Tensor

Implements

IOps.PrepareNoAlloc(Tensor)

RandomNormal(TensorShape, Single, Single, Int32)

Normal random distribution

Declaration

public virtual Tensor RandomNormal(TensorShape s, float mean, float scale, int seed)

Parameters

Type	Name	Description
TensorShape	s	shape
Single	mean	mean
Single	scale	scale
Int32	seed	seed

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.RandomNormal(TensorShape, Single, Single, Int32)

RandomUniform(TensorShape, Single, Single, Int32)

Uniform random distribution

Declaration

public virtual Tensor RandomUniform(TensorShape s, float mean, float scale, int seed)

Parameters

Type	Name	Description
TensorShape	s	shape
Single	mean	mean
Single	scale	scale
Int32	seed	seed

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.RandomUniform(TensorShape, Single, Single, Int32)

Reciprocal(Tensor)

Reciprocal (1/x)

Declaration

public virtual Tensor Reciprocal(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Reciprocal(Tensor)

ReduceMax(Tensor, Int32)

Reduce with max

Declaration

public virtual Tensor ReduceMax(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ReduceMax(Tensor, Int32)

ReduceMean(Tensor, Int32)

Reduce with mean

Declaration

public virtual Tensor ReduceMean(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ReduceMean(Tensor, Int32)

ReduceMin(Tensor, Int32)

Reduce with min

Declaration

public virtual Tensor ReduceMin(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ReduceMin(Tensor, Int32)

ReduceProd(Tensor, Int32)

Reduce with product

Declaration

public virtual Tensor ReduceProd(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ReduceProd(Tensor, Int32)

ReduceSum(Tensor, Int32)

Reduce with sum

Declaration

public virtual Tensor ReduceSum(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ReduceSum(Tensor, Int32)

Relu(Tensor)

ReLU

Declaration

public virtual Tensor Relu(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Relu(Tensor)

Relu6(Tensor)

ReLU capped to 6

Declaration

public virtual Tensor Relu6(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Relu6(Tensor)

Resample2D(Tensor, Int32[], Boolean)

Resample 2D

Declaration

public virtual Tensor Resample2D(Tensor X, int[] size, bool bilinear)

Parameters

Type	Name	Description
Tensor	X
Int32[]	size	size
Boolean	bilinear	bilinear flag

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Resample2D(Tensor, Int32[], Boolean)

ResetAllocator(Boolean)

Reset internal allocator

Declaration

public virtual void ResetAllocator(bool keepCachedMemory = true)

Parameters

Type	Name	Description
Boolean	keepCachedMemory	keep cached memory flag

Implements

IOps.ResetAllocator(Boolean)

Reshape(Tensor, TensorShape)

Reshape

Declaration

public virtual Tensor Reshape(Tensor X, TensorShape newShape)

Parameters

Type	Name	Description
Tensor	X
TensorShape	newShape

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Reshape(Tensor, TensorShape)

RoiAlign(Tensor, Tensor, Tensor, Int32, Int32, Int32, Single)

RoiAlign

Declaration

public virtual Tensor RoiAlign(Tensor X, Tensor Rois, Tensor Indices, int outputHeight, int outputWidth, int samplingRatio, float spatialScale)

Parameters

Type	Name	Description
Tensor	X
Tensor	Rois
Tensor	Indices
Int32	outputHeight	outputHeight
Int32	outputWidth	outputWidth
Int32	samplingRatio	samplingRatio
Single	spatialScale	spatialScale

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.RoiAlign(Tensor, Tensor, Tensor, Int32, Int32, Int32, Single)

Round(Tensor)

Round to nearest integer. In case of halfs, round to nearest even integer

Declaration

public virtual Tensor Round(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Round(Tensor)

ScaleBias(Tensor, Tensor, Tensor)

Scale bias o = s * x + b, element wise

Declaration

public virtual Tensor ScaleBias(Tensor X, Tensor S, Tensor B)

Parameters

Type	Name	Description
Tensor	X
Tensor	S
Tensor	B

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.ScaleBias(Tensor, Tensor, Tensor)

ScatterND(Tensor, Tensor, Tensor, Layer.ScatterNDReductionMode)

Declaration

public virtual Tensor ScatterND(Tensor X, Tensor indices, Tensor updates, Layer.ScatterNDReductionMode reduction)

Parameters

Type	Name	Description
Tensor	X
Tensor	indices
Tensor	updates
Layer.ScatterNDReductionMode	reduction

Returns

Type	Description
Tensor

Implements

IOps.ScatterND(Tensor, Tensor, Tensor, Layer.ScatterNDReductionMode)

Selu(Tensor, Single, Single)

SELU

Declaration

public virtual Tensor Selu(Tensor X, float alpha, float gamma)

Parameters

Type	Name	Description
Tensor	X
Single	alpha	alpha
Single	gamma	gamma

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Selu(Tensor, Single, Single)

SetModelExecutionsReporter(IModelExecutionsReporter)

Set model executions reporter model executions reporter

Declaration

public void SetModelExecutionsReporter(IModelExecutionsReporter executionsReporter)

Parameters

Type	Name	Description
IModelExecutionsReporter	executionsReporter

Implements

IOps.SetModelExecutionsReporter(IModelExecutionsReporter)

Shape(Tensor, Int32)

Shape of the input

Declaration

public Tensor Shape(Tensor X, int axis = null)

Parameters

Type	Name	Description
Tensor	X	input
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Shape(Tensor, Int32)

Sigmoid(Tensor)

Sigmoid

Declaration

public virtual Tensor Sigmoid(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Sigmoid(Tensor)

Sign(Tensor)

Sign

Declaration

public virtual Tensor Sign(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	Tensor with 1 if x > 0 -1 if < 0 and 0 if == 0 values

Implements

IOps.Sign(Tensor)

Sin(Tensor)

Sin

Declaration

public virtual Tensor Sin(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Sin(Tensor)

Sinh(Tensor)

Sinh

Declaration

public virtual Tensor Sinh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Sinh(Tensor)

Softmax(Tensor, Int32)

Softmax

Declaration

public virtual Tensor Softmax(Tensor X, int axis)

Parameters

Type	Name	Description
Tensor	X
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Softmax(Tensor, Int32)

Softplus(Tensor)

Softplus

Declaration

public virtual Tensor Softplus(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Softplus(Tensor)

SpaceToDepth(Tensor, Int32[])

Space to depth

Declaration

public virtual Tensor SpaceToDepth(Tensor X, int[] blocksize)

Parameters

Type	Name	Description
Tensor	X
Int32[]	blocksize

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.SpaceToDepth(Tensor, Int32[])

Sqrt(Tensor)

Sqrt

Declaration

public virtual Tensor Sqrt(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Sqrt(Tensor)

StridedSlice(Tensor, Int32[], Int32[], Int32[])

Strided slice

Declaration

public virtual Tensor StridedSlice(Tensor X, int[] starts4Dor8D, int[] ends4Dor8D, int[] strides4Dor8D)

Parameters

Type	Name	Description
Tensor	X
Int32[]	starts4Dor8D
Int32[]	ends4Dor8D
Int32[]	strides4Dor8D	stride

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.StridedSlice(Tensor, Int32[], Int32[], Int32[])

Sub(Tensor[])

Subtract tensors o = tensors[0] - tensors[1] - ... - tensors[N-1]

Declaration

public virtual Tensor Sub(Tensor[] tensors)

Parameters

Type	Name	Description
Tensor[]	tensors	input tensors

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Sub(Tensor[])

Swish(Tensor)

Swish

Declaration

public virtual Tensor Swish(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Swish(Tensor)

Tan(Tensor)

Tan

Declaration

public virtual Tensor Tan(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Tan(Tensor)

Tanh(Tensor)

Tanh

Declaration

public virtual Tensor Tanh(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Tanh(Tensor)

Tile(Tensor, Int32[])

Tile

Declaration

public virtual Tensor Tile(Tensor X, int[] repeats)

Parameters

Type	Name	Description
Tensor	X
Int32[]	repeats	repetition counts

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Tile(Tensor, Int32[])

TopKIndices(Tensor, Int32, Int32, Boolean, Boolean)

Top K indices

Declaration

public virtual Tensor TopKIndices(Tensor X, int k, int axis, bool largest, bool sorted)

Parameters

Type	Name	Description
Tensor	X
Int32	k	k
Int32	axis	axis
Boolean	largest	largest flag
Boolean	sorted	sorted flag

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.TopKIndices(Tensor, Int32, Int32, Boolean, Boolean)

TopKValues(Tensor, Tensor, Int32)

Top K values

Declaration

public virtual Tensor TopKValues(Tensor X, Tensor I, int axis)

Parameters

Type	Name	Description
Tensor	X	input
Tensor	I	indices
Int32	axis	axis

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.TopKValues(Tensor, Tensor, Int32)

Transpose(Tensor)

Transpose matrix

Declaration

public virtual Tensor Transpose(Tensor X)

Parameters

Type	Name	Description
Tensor	X

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Transpose(Tensor)

Transpose(Tensor, Int32[])

Transpose according to permutations

Declaration

public virtual Tensor Transpose(Tensor X, int[] permutations)

Parameters

Type	Name	Description
Tensor	X
Int32[]	permutations	new axis order

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Transpose(Tensor, Int32[])

Upsample2D(Tensor, Int32[], Boolean)

Upsample 2D

Declaration

public virtual Tensor Upsample2D(Tensor X, int[] scale, bool bilinear)

Parameters

Type	Name	Description
Tensor	X
Int32[]	scale	scale
Boolean	bilinear	bilinear flag

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Upsample2D(Tensor, Int32[], Boolean)

Upsample3D(Tensor, Int32[], Boolean)

Upsample 3D

Declaration

public virtual Tensor Upsample3D(Tensor X, int[] scale, bool trilinear)

Parameters

Type	Name	Description
Tensor	X
Int32[]	scale	scale
Boolean	trilinear	trilinear flag

Returns

Type	Description
Tensor	output Tensor

Implements

IOps.Upsample3D(Tensor, Int32[], Boolean)

Where(Tensor, Tensor, Tensor)

Where

Declaration

public virtual Tensor Where(Tensor C, Tensor A, Tensor B)

Parameters

Type	Name	Description
Tensor	C
Tensor	A
Tensor	B

Returns

Type	Description
Tensor	Tensor with values c ? a : b

Implements

IOps.Where(Tensor, Tensor, Tensor)