Function-Level Support Status

ONNX Support Status

Note

In this document, the numbers in the header of all tables represent the version of onnx opset.

Import

• ✓: onnx specification defined, and supported.

• X: onnx specification defined, but not support yet.

• Empty: Not defined (Support status follows latest).

Total: 93/155

ONNX Operator	1	2	3	4	5	6	7	8	9	10	11	NNabla Func	Description
Abs	✓					✓	✓					Abs
Acos							✓					ACos
Acosh									✓			ACosh
Add	✓					✓	✓					Add2, Reshape
And	✓						✓					LogicalAnd, Reshape
ArgMax	✓						✓			X	✓	Max
ArgMin	✓						✓			X	✓	Min
Asin							✓					ASin
Asinh									✓			ASinh
Atan							✓					ATan
Atanh									✓			ATanh
AveragePool	✓						✓			X	X	AveragePooling, Pad	Not all features are verified. Those features can be verified by ONNXRuntime when opset > 6. Some feature is not supported by Nnabla such as Pad’s edge mode. if opset >= 10, the ceil_mode is not supported.
BatchNormalization	X					X	X		✓			BatchNormalization
BitShift											X		Not yet implemented.
Cast	✓					✓	✓		X			Abs, Log
Ceil	✓					✓	✓					Ceil
Clip	✓					✓	✓				✓	Identity, MaximumScalar, MinimumScalar
Compress									X		X		Not yet implemented.
Concat	✓			✓			✓				X	Concatenate
ConcatFromSequence											X		Not yet implemented.
Constant	✓						✓		X		X	Identity
ConstantOfShape									✓			Constant
Conv	✓						✓				X	Convolution
ConvInteger										X			Not yet implemented.
ConvTranspose	✓						✓				X	Deconvolution, Pad
Cos							✓					Cos
Cosh									✓			Cosh
CumSum											X		Not yet implemented.
DepthToSpace	✓						✓				✓	Reshape, Transpose
DequantizeLinear										X			Not yet implemented.
Det											X		Not yet implemented.
Div	✓					✓	✓					Div2, Reshape
Dropout	✓					✓	✓			X		Identity
DynamicQuantizeLinear											X		Not yet implemented.
Elu	✓					✓	✓					ELU
Equal	✓						✓				X	Equal, Reshape
Erf									X				Not yet implemented.
Exp	✓					✓	✓					Exp
Expand								✓	✓			Broadcast, Reshape
EyeLike									X				Not yet implemented.
Flatten	✓						✓		✓		✓	Reshape
Floor	✓					✓	✓					Floor
GRU	X		X				X						Not yet implemented.
Gather	✓						✓				✓	Concatenate, Slice
GatherElements											X		Not yet implemented.
GatherND											X		Not yet implemented.
Gemm	✓					✓	✓		✓		✓	Add2, BatchMatmul, MulScalar, Reshape
GlobalAveragePool	✓						✓					GlobalAveragePooling
GlobalLpPool	X	X											Not yet implemented.
GlobalMaxPool	X												Not yet implemented.
Greater	✓						✓		✓			Greater, Reshape
HardSigmoid	✓					✓	✓					AddScalar, HardSigmoid, MaximumScalar, MinimumScalar, MulScalar
Hardmax	✓						✓				✓	Max, OneHot, Reshape
Identity	✓						✓					Identity
If	X												Not yet implemented.
InstanceNormalization	✓					✓	✓					BatchNormalization, Concatenate, Reshape, Split
IsInf										✓		IsInf
IsNaN									✓			IsNaN
LRN	✓						✓					AddScalar, Div2, MulScalar, PowScalar, SumPooling, Transpose
LSTM	X						X						Not yet implemented.
LeakyRelu	✓					✓	✓					LeakyReLU
Less	✓						✓		✓			Less, Reshape
Log	✓					✓	✓					Log
LogSoftmax	✓						✓				✓	Add2, Exp, Log, Max, Reshape, Sub2, Sum
Loop	X										X		Not yet implemented.
LpNormalization	X												Not yet implemented.
LpPool	X	X									X		Not yet implemented.
MatMul	✓						✓		✓			BatchMatmul, Reshape
MatMulInteger										X			Not yet implemented.
Max	✓					✓	✓	✓	✓			Maximum2
MaxPool	✓						✓	X		X	X	MaxPooling, Pad	Not all features are verified. Those features can be verified by ONNXRuntime. if opset >= 10, the ceil_mode is not supported, dilations is not equal to 1 is not supported.
MaxRoiPool	X												Not yet implemented.
MaxUnpool									X		X		Not yet implemented.
Mean	✓					✓	✓	✓	✓			Broadcast, Mean, Stack
MeanVarianceNormalization									X				Not yet implemented.
Min	✓					✓	✓	✓	✓			Minimum2
Mod										X			Not yet implemented.
Mul	✓					✓	✓					Mul2, Reshape
Multinomial							X						Not yet implemented.
Neg	✓					✓	✓					MulScalar
NonMaxSuppression										X	X		Not yet implemented.
NonZero									X				Not yet implemented.
Not	✓						✓					LogicalNot
OneHot									X		X		Not yet implemented.
Or	✓						✓					LogicalOr, Reshape
PRelu	✓					✓	✓		X			PReLU
Pad	✓	✓					✓				✓	Pad	Onnx required to support “edge” mode, while nnabla does not support it.
Pow	✓						✓					Pow2, Reshape
QLinearConv										X			Not yet implemented.
QLinearMatMul										X			Not yet implemented.
QuantizeLinear										X			Not yet implemented.
RNN	X						X						Not yet implemented.
RandomNormal	X												Not yet implemented.
RandomNormalLike	X												Not yet implemented.
RandomUniform	X												Not yet implemented.
RandomUniformLike	X												Not yet implemented.
Range											X		Not yet implemented.
Reciprocal	✓					✓	✓					RDivScalar
ReduceL1	X										X		Not yet implemented.
ReduceL2	X										X		Not yet implemented.
ReduceLogSum	X										X		Not yet implemented.
ReduceLogSumExp	X										X		Not yet implemented.
ReduceMax	✓						✓				✓	Max
ReduceMean	✓						✓				✓	Mean
ReduceMin	✓						✓				✓	Min
ReduceProd	✓						✓				✓	Prod
ReduceSum	✓						✓				✓	Sum
ReduceSumSquare	✓						✓				✓	PowScalar, Sum
Relu	✓					✓	✓					ReLU
Reshape	✓				✓		✓					Reshape
Resize										X	X		Not yet implemented.
ReverseSequence										X			Not yet implemented.
RoiAlign										X			Not yet implemented.
Round											✓	Round
Scan								X	X		X		Not yet implemented.
Scatter									X		X		Not yet implemented.
ScatterElements											X		Not yet implemented.
ScatterND											X		Not yet implemented.
Selu	✓					✓	✓					SELU
SequenceAt											X		Not yet implemented.
SequenceConstruct											X		Not yet implemented.
SequenceErase											X		Not yet implemented.
SequenceInsert											X		Not yet implemented.
SequenceLength											X		Not yet implemented.
Shape	X												Not yet implemented.
Shrink									X				Not yet implemented.
Sigmoid	✓					✓	✓					Sigmoid
Sign									✓			Sign
Sin							✓					Sin
Sinh									✓			Sinh
Size	X												Not yet implemented.
Slice	✓						✓			✓	X	Slice
Softmax	✓						✓				✓	Div2, Exp, Max, Reshape, Sub2, Sum
Softplus	✓						✓					SoftPlus
Softsign	✓						✓					SoftSign
SpaceToDepth	✓						✓					Reshape, Transpose
Split	✓	✓					✓				✓	Split, Stack
SplitToSequence											X		Not yet implemented.
Sqrt	✓					✓	✓					PowScalar
Squeeze	✓						✓				✓	Reshape
StringNormalizer										X			Not yet implemented.
Sub	✓					✓	✓					Reshape, Sub2
Sum	✓					✓	✓	X	X			AddN
Tan							✓					Tan
Tanh	✓					✓	✓					Tanh
TfIdfVectorizer									X				Not yet implemented.
ThresholdedRelu										✓		Constant, GreaterScalar, Where
Tile	✓					✓	✓					Tile
TopK	X									X	X		Not yet implemented.
Transpose	✓						✓					Transpose
Unique											X		Not yet implemented.
Unsqueeze	✓						✓				✓	Reshape
Upsample	X						X		✓	X		Unpooling
Where									✓			Where
Xor	✓						✓					LogicalXor, Reshape

Export

• ✓: Support to export this opset.

• △: Partially support to export this opset (e.g. some cases cannot be supported, or not completely tested).

• X: Supported, but test failed.

• Empty: Not support corresponding opset version.

Total: 120/173

Neural Network Layer

Count 11/14

NNabla Function	7	9	10	11	ONNX Op	Description
Affine	✓	✓	✓	✓	Gemm, Reshape
RNN						Not yet implemented.
LSTM						Not yet implemented.
GRU						Not yet implemented.
Convolution	✓	✓	✓	✓	Conv, Reshape
DepthwiseConvolution	✓	✓	✓	✓	Conv, Reshape
Deconvolution	✓	✓	✓	✓	ConvTranspose, Reshape
DepthwiseDeconvolution	✓	✓	✓	✓	ConvTranspose, Reshape
MaxPooling	✓	✓	✓	✓	Constant, MaxPool, Pad, Reshape
AveragePooling	△	△	△	△	AveragePool, Constant, Pad, Reshape	Currently only supports the cases where both ignore_border and including_pad are True.
GlobalAveragePooling	✓	✓	✓	✓	GlobalAveragePool
SumPooling	✓	✓	✓	✓	AveragePool, Constant, Mul, Pad, Reshape
Unpooling	✓	✓	✓	✓	Resize
Embed	✓	✓	✓	✓	Gather

Neural Network Activation Functions

Count 21/21

NNabla Function	7	9	10	11	ONNX Op	Description
Sigmoid	✓	✓	✓	✓	Sigmoid
Swish	✓	✓	✓	✓	Mul, Sigmoid
Tanh	✓	✓	✓	✓	Tanh
ReLU	✓	✓	✓	✓	Relu
LeakyReLU	✓	✓	✓	✓	LeakyRelu
Softmax	✓	✓	✓	✓	Div, Exp, ReduceMax, ReduceSum, Sub
LogSoftmax	✓	✓	✓	✓	Exp, Log, ReduceMax, ReduceSum, Sub
ELU	✓	✓	✓	✓	Elu
SELU	✓	✓	✓	✓	Selu
CReLU	✓	✓	✓	✓	Concat, Neg, Relu
CELU	✓	✓	✓	✓	Concat, Elu, Neg
PReLU	✓	✓	✓	✓	PRelu, Reshape
GELU	✓	✓	✓	✓	Add, Constant, Div, Mul, Pow, Sqrt, Tanh
ReLU6	✓	✓	✓	✓	Constant, Min, Relu
HardSigmoid	✓	✓	✓	✓	HardSigmoid
HardTanh	✓	✓	✓	✓	Constant, Max, Min, Neg
LogSigmoid	✓	✓	✓	✓	Log, Sigmoid
SoftPlus	✓	✓	✓	✓	Softplus
SoftSign	✓	✓	✓	✓	Softsign
TanhShrink	✓	✓	✓	✓	Sub, Tanh
Sinc	X	X	X	✓	Constant, Div, Equal, Sin, Where

Normalization

Count 2/6

NNabla Function	7	9	10	11	ONNX Op	Description
FusedBatchNormalization	✓	✓	✓	✓	Add, BatchNormalization, Constant, Div, Mul, ReduceMean, ReduceSum, Relu, Reshape, Squeeze, Sub
BatchNormalization	✓	✓	✓	✓	BatchNormalization, Constant, Div, Mul, ReduceMean, ReduceSum, Reshape, Squeeze, Sub
SyncBatchNormalization						Not yet implemented.
MeanSubtraction						Not yet implemented.
ClipGradByValue						Not yet implemented.
ClipGradByNorm						Not yet implemented.

Reduction

Count 5/7

NNabla Function	7	9	10	11	ONNX Op	Description
Sum	✓	✓	✓	✓	ReduceSum
Mean	✓	✓	✓	✓	ReduceMean
Max	✓	✓	✓	✓	ReduceMax
Min	✓	✓	✓	✓	ReduceMin
Prod	✓	✓	✓	✓	ReduceProd
ReduceSum						Not yet implemented.
ReduceMean						Not yet implemented.

Arithmetic

Count 11/12

NNabla Function	7	9	10	11	ONNX Op	Description
Add2	✓	✓	✓	✓	Add
BcAdd2						Not yet implemented.
Sub2	✓	✓	✓	✓	Sub
Mul2	✓	✓	✓	✓	Mul
Div2	✓	✓	✓	✓	Div
Pow2	✓	✓	✓	✓	Pow
AddScalar	✓	✓	✓	✓	Add, Constant
MulScalar	✓	✓	✓	✓	Constant, Mul
PowScalar	✓	✓	✓	✓	Constant, Pow
RSubScalar	✓	✓	✓	✓	Constant, Sub
RDivScalar	✓	✓	✓	✓	Constant, Div
RPowScalar	✓	✓	✓	✓	Constant, Pow

Logical

Count 29/29

NNabla Function	7	9	10	11	ONNX Op	Description
Sign	X	✓	✓	✓	Sign
Minimum2	✓	✓	✓	✓	Add, Constant, Min
Maximum2	✓	✓	✓	✓	Add, Constant, Max
MinimumScalar	✓	✓	✓	✓	Add, Constant, Min
MaximumScalar	✓	✓	✓	✓	Add, Constant, Max
LogicalAnd	✓	✓	✓	✓	And
LogicalOr	✓	✓	✓	✓	Or
LogicalXor	✓	✓	✓	✓	Xor
Equal	X	X	X	✓	Equal
NotEqual	X	X	X	✓	Equal, Not
GreaterEqual	✓	✓	✓	✓	Less, Not
Greater	✓	✓	✓	✓	Greater
LessEqual	✓	✓	✓	✓	Greater, Not
Less	✓	✓	✓	✓	Less
LogicalAndScalar	✓	✓	✓	✓	And, Constant
LogicalOrScalar	✓	✓	✓	✓	Constant, Or
LogicalXorScalar	✓	✓	✓	✓	Constant, Xor
EqualScalar	X	X	X	✓	Constant, Equal
NotEqualScalar	X	X	X	✓	Constant, Equal, Not
GreaterEqualScalar	✓	✓	✓	✓	Constant, Less, Not
GreaterScalar	✓	✓	✓	✓	Constant, Greater
LessEqualScalar	✓	✓	✓	✓	Constant, Greater, Not
LessScalar	✓	✓	✓	✓	Constant, Less
LogicalNot	✓	✓	✓	✓	Not
IsNaN	X	✓	✓	✓	IsNaN
IsInf	X	X	✓	✓	IsInf
ResetNaN	X	✓	✓	✓	Constant, IsNaN, Where
ResetInf	X	X	✓	✓	Constant, IsInf, Where
Where	X	✓	✓	✓	Where

Math

Count 22/22

NNabla Function	7	9	10	11	ONNX Op	Description
Constant	✓	✓	✓	✓	Constant, Identity
Arange	✓	✓	✓	✓	Constant, Identity
Abs	✓	✓	✓	✓	Abs
Exp	✓	✓	✓	✓	Exp
Log	✓	✓	✓	✓	Log
Identity	✓	✓	✓	✓	Identity
BatchMatmul	✓	✓	✓	✓	MatMul, Transpose
Round	X	X	X	✓	Round
Ceil	✓	✓	✓	✓	Ceil
Floor	✓	✓	✓	✓	Floor
Sin	✓	✓	✓	✓	Sin
Cos	✓	✓	✓	✓	Cos
Tan	✓	✓	✓	✓	Tan
Sinh	X	✓	✓	✓	Sinh
Cosh	X	✓	✓	✓	Cosh
ASin	✓	✓	✓	✓	Asin
ACos	✓	✓	✓	✓	Acos
ATan	✓	✓	✓	✓	Atan
ATan2	✓	✓	✓	✓	Atan, Div
ASinh	X	✓	✓	✓	Asinh
ACosh	X	✓	✓	✓	Acosh
ATanh	X	✓	✓	✓	Atanh

Array Manipulation

Count 12/19

NNabla Function	7	9	10	11	ONNX Op	Description
Concatenate	✓	✓	✓	✓	Concat
Split	✓	✓	✓	✓	Split, Squeeze
Stack	✓	✓	✓	✓	Concat, Unsqueeze
Slice	△	△	✓	✓	Constant, Slice	ONNX slice cannot support step != 1 on opset < 10.
Pad	△	△	△	△	Constant, Pad	When the mode of the pad is reflect, if the size of the pad exceeds the input size, onnxruntime cannot handle it.
Transpose	✓	✓	✓	✓	Transpose
Broadcast	X	✓	✓	✓
BroadcastTo	✓	✓	✓	✓
Tile	✓	✓	✓	✓	Constant, Reshape, Tile
OneHot	X	✓	✓	✓	Flatten, Gather, Reshape
Flip	✓	✓	✓	✓	Gather, Identity, Transpose
Shift						Not yet implemented.
Sort						Not yet implemented.
Reshape	✓	✓	✓	✓	Constant, Reshape
MatrixDiag						Not yet implemented.
MatrixDiagPart						Not yet implemented.
Assign						Not yet implemented.
GatherNd						Not yet implemented.
ScatterNd						Not yet implemented.

Signal Processing

Count 1/3

NNabla Function	7	9	10	11	ONNX Op	Description
Interpolate	X	X	△	✓	Resize
FFT						Not yet implemented.
IFFT						Not yet implemented.

Stochasticity

Count 0/11

NNabla Function	7	9	10	11	ONNX Op	Description
Dropout	X	X	X	X	Dropout	The Dropout in nnabla has no test mode and contains random parameters, so the test result is not the same as onnx.
TopKData						Not yet implemented.
TopKGrad						Not yet implemented.
Rand						Not yet implemented.
Randint						Not yet implemented.
Randn						Not yet implemented.
RandomChoice						Not yet implemented.
RandomCrop						Not yet implemented.
RandomFlip						Not yet implemented.
RandomShift						Not yet implemented.
ImageAugmentation						Not yet implemented.

Loss Functions

Count 0/9

NNabla Function	7	9	10	11	ONNX Op	Description
SigmoidCrossEntropy						Not yet implemented.
BinaryCrossEntropy						Not yet implemented.
SoftmaxCrossEntropy						Not yet implemented.
CategoricalCrossEntropy						Not yet implemented.
SquaredError						Not yet implemented.
AbsoluteError						Not yet implemented.
HuberLoss						Not yet implemented.
EpsilonInsensitiveLoss						Not yet implemented.
KLMultinomial						Not yet implemented.

Quantization Neural Network Layers

Count 6/12

NNabla Function	7	9	10	11	ONNX Op	Description
BinarySigmoid	X	✓	✓	✓	Constant, Greater, Where
BinaryTanh	X	✓	✓	✓	Constant, Greater, Where
BinaryConnectAffine	✓	✓	✓	✓	Gemm, Reshape
BinaryConnectConvolution	✓	✓	✓	✓	Conv, Reshape
BinaryWeightAffine	✓	✓	✓	✓	Add, MatMul, Mul, Reshape
BinaryWeightConvolution	✓	✓	✓	✓	Add, Conv, Mul, Reshape
INQAffine						Not yet implemented.
INQConvolution						Not yet implemented.
FixedPointQuantize						Not yet implemented.
MinMaxQuantize						Not yet implemented.
Pow2Quantize						Not yet implemented.
Prune						Not yet implemented.

Validation

Count 0/3

NNabla Function	7	9	10	11	ONNX Op	Description
TopNError						Not yet implemented.
BinaryError						Not yet implemented.
ConfusionMatrix						Not yet implemented.

Unsupported, Special Use

Count 0/5

NNabla Function	7	9	10	11	ONNX Op	Description
VATNoise						Not yet implemented.
Unlink						Not yet implemented.
Sink						Not yet implemented.
NmsDetection2d						Not yet implemented.
MaxPoolingBackward						Not yet implemented.

Tensorflow Support Status

Import

• ✓: Supported

• △: Partially supported

• X: Supported, but test failed.

• Empty: Not support yet.

Total: 109/122

Tensorflow support status

Tensorflow Function	Status	NNabla Func	Description
Abs	✓	Abs
Acos	✓	ACos
Acosh	✓	ACosh
Add	✓	Add2
AddN	✓	AddN
All	✓	Greater, Min, Reshape
Any	✓	Greater, Reshape, Sum
ArgMax	✓	Max
ArgMin	✓	Min
Asin	✓	ASin
Asinh	✓	ASinh
Atan	✓	ATan
Atan2	✓	ATan, Add2, Div2, Mul2, Reshape, Sign, Sub2
Atanh	✓	ATanh
AvgPool	△	AveragePooling, Pad, Transpose
AvgPool3D	△	AveragePooling, Pad, Transpose
BatchMatMul	✓	BatchMatmul, Transpose
BatchNormalization	✓	Add2, Mul2, PowScalar, RDivScalar, Reshape, Sub2
BiasAdd	✓	Add2, Reshape
BroadcastTo	✓
Cast	X	NA	Not yet implemented.
Ceil	✓	Ceil
ClipByValue	✓	Maximum2, Minimum2, Reshape
Concat	✓	Concatenate
ConcatV2	✓	Concatenate
Const	✓	NA
Conv1D	△	Convolution, Pad, Reshape, Transpose
Conv1DTranspose	△	Deconvolution, Reshape, Transpose
Conv2D	△	Convolution, Pad, Transpose
Conv2DBackpropInput	△	Deconvolution, Transpose
Conv3D	△	Convolution, Pad, Transpose
Conv3DBackpropInput	△	Deconvolution, Pad, Transpose
Cos	✓	Cos
Cosh	✓	Cosh
Crelu	✓	Concatenate, MulScalar, ReLU
Cumsum	X		Not yet implemented.
DepthToSpace	✓	Reshape, Transpose
DepthwiseConv2d	△	Convolution, Pad, Reshape, Transpose
Div	✓	Div2
Elu	✓	ELU
Equal	✓	Equal
Erf	X		Not yet implemented.
Erfc	X		Not yet implemented.
Exp	✓	Exp
ExpandDims	✓	Reshape
Floor	✓	Floor
FloorDiv	✓	Div2, Floor
FloorMod	✓	Div2, Floor, Mul2, Sub2
GatherNd	X		Not yet implemented.
GatherV2	X	Concatenate, Slice	Not yet implemented.
Greater	✓	Greater
GreaterEqual	✓	Less, LogicalNot
Identity	✓	Identity
IsInf	✓	IsInf
IsNan	✓	IsNaN
LeakyRelu	✓	LeakyReLU
Less	✓	Less
LessEqual	✓	Greater, LogicalNot
Log	✓	Log
LogSigmoid	✓	MulScalar, SoftPlus
LogSoftmax	✓	Add2, Exp, Log, Max, Reshape, Sub2, Sum, Transpose
LogicalAnd	✓	LogicalAnd
LogicalNot	✓	LogicalNot
LogicalOr	✓	LogicalOr
LogicalXor	✓	LogicalAnd, LogicalNot, LogicalOr
Max	✓	Max
MaxPool	△	MaxPooling, Pad, Reshape, Transpose
MaxPool3D	△	MaxPooling, Pad, Transpose
MaxPoolWithArgmax	X		Not yet implemented.
Maximum	✓	Maximum2
Mean	✓	Mean
Min	✓	Min
Minimum	✓	Minimum2
Mul	✓	Mul2
Neg	✓	MulScalar
NotEqual	✓	Equal, LogicalNot
Pack	✓	Concatenate, Reshape
Pad	△	Pad
Pow	✓	Pow2
Prod	✓	Prod
RealDiv	✓	Div2
Reciprocal	✓	RDivScalar
Relu	✓	ReLU
Relu6	✓	MaximumScalar, MinimumScalar
Reshape	✓	Reshape
ReverseSequence	X		Not yet implemented.
ReverseV2	X		Not yet implemented.
Round	✓	Round
Rsqrt	✓	PowScalar, RDivScalar
Selu	✓	SELU
Shape	X		Not yet implemented.
Sigmoid	✓	Sigmoid
Sign	✓	Sign
Sin	✓	Sin
Sinh	✓	Sinh
Size	X		Not yet implemented.
Slice	✓	Slice
Softmax	✓	Div2, Exp, Max, Reshape, Sub2, Sum, Transpose
Softplus	✓	SoftPlus
Softsign	✓	SoftSign
SpaceToDepth	✓	Reshape, Transpose
Split	✓	Split, Stack
SplitV	✓	Split, Stack
Sqrt	✓	PowScalar
Square	✓	Mul2
SquaredDifference	✓	Mul2, Sub2
Squeeze	✓	Reshape
StopGradient	✓	Identity
StridedSlice	△	Slice
Sub	✓	Sub2
Sum	✓	Sum
Swish	✓	Mul2, Sigmoid
Tan	✓	Tan
Tanh	✓	Tanh
Tile	✓	Tile
TopKV2	X		Not yet implemented.
Transpose	✓	Transpose
TruncateDiv	✓	Div2
TruncateMod	X		Not yet implemented.
Unpack	✓	Reshape, Split, Stack
Where	△	Where
ZerosLike	✓	NA

Export

• ✓: Supported

• △: Partially supported

• X: Supported, but test failed.

• Empty: Not support yet.

Total: 120/173

Neural Network Layer

Count 11/14

NNabla Function	Status	Description
Affine	✓
RNN		Not yet implemented.
LSTM		Not yet implemented.
GRU		Not yet implemented.
Convolution	△	The cases dilations and strides larger than 1 are not supported by tensorflow.
DepthwiseConvolution	△	The cases dilations and strides larger than 1 are not supported by tensorflow.
Deconvolution	△	The cases dilations larger than 1 are not supported by tensorflow.
DepthwiseDeconvolution	△	The cases dilations larger than 1 are not supported by tensorflow.
MaxPooling	✓
AveragePooling	△	Currently only supports the cases both ignore_border and including_pad are True.
GlobalAveragePooling	✓
SumPooling	✓
Unpooling	△	The kernel only supports 2d.
Embed	✓

Neural Network Activation Functions

Count 21/21

NNabla Function	Status	Description
Sigmoid	✓
Swish	✓
Tanh	✓
ReLU	✓
LeakyReLU	✓
Softmax	✓
LogSoftmax	✓
ELU	✓
SELU	△
CReLU	✓
CELU	✓
PReLU	✓
GELU	✓
ReLU6	✓
HardSigmoid	✓
HardTanh	✓
LogSigmoid	✓
SoftPlus	✓
SoftSign	✓
TanhShrink	✓
Sinc	✓

Normalization

Count 2/6

NNabla Function	Status	Description
FusedBatchNormalization	✓
BatchNormalization	✓
SyncBatchNormalization		Not yet implemented.
MeanSubtraction		Not yet implemented.
ClipGradByValue		Not yet implemented.
ClipGradByNorm		Not yet implemented.

Reduction

Count 5/7

NNabla Function	Status	Description
Sum	✓
Mean	✓
Max	✓
Min	✓
Prod	✓
ReduceSum		Not yet implemented.
ReduceMean		Not yet implemented.

Arithmetic

Count 11/12

NNabla Function	Status	Description
Add2	✓
BcAdd2		Not yet implemented.
Sub2	✓
Mul2	✓
Div2	✓
Pow2	✓
AddScalar	✓
MulScalar	✓
PowScalar	✓
RSubScalar	✓
RDivScalar	✓
RPowScalar	✓

Logical

Count 29/29

NNabla Function	Status	Description
Sign	✓
Minimum2	✓
Maximum2	✓
MinimumScalar	✓
MaximumScalar	✓
LogicalAnd	✓
LogicalOr	✓
LogicalXor	✓
Equal	✓
NotEqual	✓
GreaterEqual	✓
Greater	✓
LessEqual	✓
Less	✓
LogicalAndScalar	✓
LogicalOrScalar	✓
LogicalXorScalar	✓
EqualScalar	✓
NotEqualScalar	✓
GreaterEqualScalar	✓
GreaterScalar	✓
LessEqualScalar	✓
LessScalar	✓
LogicalNot	✓
IsNaN	✓
IsInf	✓
ResetNaN	✓
ResetInf	✓
Where	✓

Math

Count 22/22

NNabla Function	Status	Description
Constant	✓
Arange	✓
Abs	✓
Exp	✓
Log	✓
Identity	✓
BatchMatmul	✓
Round	✓
Ceil	✓
Floor	✓
Sin	✓
Cos	✓
Tan	✓
Sinh	✓
Cosh	✓
ASin	✓
ACos	✓
ATan	✓
ATan2	✓
ASinh	✓
ACosh	✓
ATanh	✓

Array Manipulation

Count 12/19

NNabla Function	Status	Description
Concatenate	✓
Split	✓
Stack	✓
Slice	✓
Pad	△	When the mode of the pad is reflect, if the size of the pad exceeds the input size, tensorflow cannot handle it.
Transpose	✓
Broadcast	✓
BroadcastTo	✓
Tile	✓
OneHot	✓
Flip	✓
Shift		Not yet implemented.
Sort		Not yet implemented.
Reshape	✓
MatrixDiag		Not yet implemented.
MatrixDiagPart		Not yet implemented.
Assign		Not yet implemented.
GatherNd		Not yet implemented.
ScatterNd		Not yet implemented.

Signal Processing

Count 1/3

NNabla Function	Status	Description
Interpolate	△
FFT		Not yet implemented.
IFFT		Not yet implemented.

Stochasticity

Count 0/11

NNabla Function	Status	Description
Dropout	X	The Dropout in nnabla has no test mode and contains random parameters, so the test result is not the same as tensorflow.
TopKData		Not yet implemented.
TopKGrad		Not yet implemented.
Rand		Not yet implemented.
Randint		Not yet implemented.
Randn		Not yet implemented.
RandomChoice		Not yet implemented.
RandomCrop		Not yet implemented.
RandomFlip		Not yet implemented.
RandomShift		Not yet implemented.
ImageAugmentation		Not yet implemented.

Loss Functions

Count 0/9

NNabla Function	Status	Description
SigmoidCrossEntropy		Not yet implemented.
BinaryCrossEntropy		Not yet implemented.
SoftmaxCrossEntropy		Not yet implemented.
CategoricalCrossEntropy		Not yet implemented.
SquaredError		Not yet implemented.
AbsoluteError		Not yet implemented.
HuberLoss		Not yet implemented.
EpsilonInsensitiveLoss		Not yet implemented.
KLMultinomial		Not yet implemented.

Quantization Neural Network Layers

Count 6/12

NNabla Function	Status	Description
BinarySigmoid	✓
BinaryTanh	✓
BinaryConnectAffine	✓
BinaryConnectConvolution	△	The cases dilations and strides larger than 1 are not supported by tensorflow.
BinaryWeightAffine	✓
BinaryWeightConvolution	△	The cases dilations and strides larger than 1 are not supported by tensorflow.
INQAffine		Not yet implemented.
INQConvolution		Not yet implemented.
FixedPointQuantize		Not yet implemented.
MinMaxQuantize		Not yet implemented.
Pow2Quantize		Not yet implemented.
Prune		Not yet implemented.

Validation

Count 0/3

NNabla Function	Status	Description
TopNError		Not yet implemented.
BinaryError		Not yet implemented.
ConfusionMatrix		Not yet implemented.

Unsupported, Special Use

Count 0/5

NNabla Function	Status	Description
VATNoise		Not yet implemented.
Unlink		Not yet implemented.
Sink		Not yet implemented.
NmsDetection2d		Not yet implemented.
MaxPoolingBackward		Not yet implemented.

Tensorflow Lite Support Status

Export

• ✓: Supported

• △: Partially supported

• X: Supported, but test failed.

• Empty: Not support yet.

Total: 98/173

Neural Network Layer

Count 8/14

NNabla Function	Status
Affine	✓
RNN
LSTM
GRU
Convolution	△
DepthwiseConvolution	△
Deconvolution	△
DepthwiseDeconvolution	△
MaxPooling	X
AveragePooling	X
GlobalAveragePooling	✓
SumPooling	X
Unpooling	△
Embed	✓

Neural Network Activation Functions

Count 20/21

NNabla Function	Status
Sigmoid	✓
Swish	✓
Tanh	✓
ReLU	✓
LeakyReLU	✓
Softmax	✓
LogSoftmax	✓
ELU	✓
SELU	△
CReLU	✓
CELU	✓
PReLU	✓
GELU	✓
ReLU6	✓
HardSigmoid	✓
HardTanh	✓
LogSigmoid	✓
SoftPlus	✓
SoftSign	✓
TanhShrink	✓
Sinc	X

Normalization

Count 0/6

NNabla Function	Status
FusedBatchNormalization	X
BatchNormalization	X
SyncBatchNormalization
MeanSubtraction
ClipGradByValue
ClipGradByNorm

Reduction

Count 5/7

NNabla Function	Status
Sum	✓
Mean	✓
Max	✓
Min	✓
Prod	✓
ReduceSum
ReduceMean

Arithmetic

Count 11/12

NNabla Function	Status
Add2	✓
BcAdd2
Sub2	✓
Mul2	✓
Div2	✓
Pow2	✓
AddScalar	✓
MulScalar	✓
PowScalar	✓
RSubScalar	✓
RDivScalar	✓
RPowScalar	✓

Logical

Count 25/29

NNabla Function	Status
Sign	✓
Minimum2	✓
Maximum2	✓
MinimumScalar	✓
MaximumScalar	✓
LogicalAnd	✓
LogicalOr	✓
LogicalXor	✓
Equal	✓
NotEqual	✓
GreaterEqual	✓
Greater	✓
LessEqual	✓
Less	✓
LogicalAndScalar	✓
LogicalOrScalar	✓
LogicalXorScalar	✓
EqualScalar	✓
NotEqualScalar	✓
GreaterEqualScalar	✓
GreaterScalar	✓
LessEqualScalar	✓
LessScalar	✓
LogicalNot	✓
IsNaN	✓
IsInf	X
ResetNaN	X
ResetInf	X
Where	X

Math

Count 14/22

NNabla Function	Status
Constant	✓
Arange	✓
Abs	✓
Exp	✓
Log	✓
Identity	✓
BatchMatmul	✓
Round	X
Ceil	✓
Floor	✓
Sin	✓
Cos	✓
Tan	✓
Sinh	✓
Cosh	✓
ASin	X
ACos	X
ATan	X
ATan2	X
ASinh	X
ACosh	X
ATanh	X

Array Manipulation

Count 11/19

NNabla Function	Status
Concatenate	✓
Split	✓
Stack	✓
Slice	△
Pad	X
Transpose	✓
Broadcast	✓
BroadcastTo	✓
Tile	✓
OneHot	✓
Flip	✓
Shift
Sort
Reshape	✓
MatrixDiag
MatrixDiagPart
Assign
GatherNd
ScatterNd

Signal Processing

Count 0/3

NNabla Function	Status
Interpolate	X
FFT
IFFT

Stochasticity

Count 0/11

NNabla Function	Status
Dropout	X
TopKData
TopKGrad
Rand
Randint
Randn
RandomChoice
RandomCrop
RandomFlip
RandomShift
ImageAugmentation

Loss Functions

Count 0/9

NNabla Function	Status
SigmoidCrossEntropy
BinaryCrossEntropy
SoftmaxCrossEntropy
CategoricalCrossEntropy
SquaredError
AbsoluteError
HuberLoss
EpsilonInsensitiveLoss
KLMultinomial

Quantization Neural Network Layers

Count 4/12

NNabla Function	Status
BinarySigmoid	X
BinaryTanh	X
BinaryConnectAffine	✓
BinaryConnectConvolution	△
BinaryWeightAffine	✓
BinaryWeightConvolution	△
INQAffine
INQConvolution
FixedPointQuantize
MinMaxQuantize
Pow2Quantize
Prune

Validation

Count 0/3

NNabla Function	Status
TopNError
BinaryError
ConfusionMatrix

Unsupported, Special Use

Count 0/5

NNabla Function	Status
VATNoise
Unlink
Sink
NmsDetection2d
MaxPoolingBackward

NNabla C Runtime Support Status

NNabla version: None

• ✓: Supported

• △: Partially supported

• X: Supported, but test failed or no test data.

• Empty: Not support yet.

Export

Total: 56/173

Neural Network Layer

Count 8/14

NNabla Function	Status	Description
Affine	✓
RNN
LSTM
GRU
Convolution	✓
DepthwiseConvolution	✓
Deconvolution	✓
DepthwiseDeconvolution
MaxPooling	✓
AveragePooling	✓
GlobalAveragePooling
SumPooling	✓
Unpooling	✓
Embed

Neural Network Activation Functions

Count 11/21

NNabla Function	Status	Description
Sigmoid	✓
Swish	✓
Tanh	✓
ReLU	✓
LeakyReLU	✓
Softmax	✓
LogSoftmax
ELU	✓
SELU	✓
CReLU	✓
CELU	✓
PReLU	✓
GELU
ReLU6
HardSigmoid
HardTanh
LogSigmoid
SoftPlus
SoftSign
TanhShrink
Sinc

Normalization

Count 1/6

NNabla Function	Status	Description
FusedBatchNormalization
BatchNormalization	✓
SyncBatchNormalization
MeanSubtraction	X
ClipGradByValue
ClipGradByNorm

Reduction

Count 1/7

NNabla Function	Status	Description
Sum	✓
Mean
Max
Min
Prod
ReduceSum
ReduceMean

Arithmetic

Count 11/12

NNabla Function	Status	Description
Add2	✓
BcAdd2
Sub2	✓
Mul2	✓
Div2	✓
Pow2	✓
AddScalar	✓
MulScalar	✓
PowScalar	✓
RSubScalar	✓
RDivScalar	✓
RPowScalar	✓

Logical

Count 5/29

NNabla Function	Status	Description
Sign	✓
Minimum2	✓
Maximum2	✓
MinimumScalar	✓
MaximumScalar	✓
LogicalAnd
LogicalOr
LogicalXor
Equal
NotEqual
GreaterEqual
Greater
LessEqual
Less
LogicalAndScalar
LogicalOrScalar
LogicalXorScalar
EqualScalar
NotEqualScalar
GreaterEqualScalar
GreaterScalar
LessEqualScalar
LessScalar
LogicalNot
IsNaN
IsInf
ResetNaN
ResetInf
Where

Math

Count 6/22

NNabla Function	Status	Description
Constant
Arange
Abs	✓
Exp	✓
Log	✓
Identity	✓
BatchMatmul	△
Round	✓
Ceil
Floor
Sin
Cos
Tan
Sinh
Cosh
ASin
ACos
ATan
ATan2
ASinh
ACosh
ATanh

Array Manipulation

Count 7/19

NNabla Function	Status	Description
Concatenate	✓
Split	✓
Stack	✓
Slice	✓
Pad
Transpose	✓
Broadcast
BroadcastTo
Tile
OneHot
Flip	✓
Shift	X
Sort
Reshape	✓
MatrixDiag	X
MatrixDiagPart	X
Assign
GatherNd
ScatterNd

Signal Processing

Count 0/3

NNabla Function	Status	Description
Interpolate
FFT
IFFT

Stochasticity

Count 0/11

NNabla Function	Status	Description
Dropout	X
TopKData
TopKGrad
Rand
Randint
Randn
RandomChoice
RandomCrop
RandomFlip
RandomShift
ImageAugmentation

Loss Functions

Count 0/9

NNabla Function	Status	Description
SigmoidCrossEntropy
BinaryCrossEntropy
SoftmaxCrossEntropy
CategoricalCrossEntropy
SquaredError
AbsoluteError
HuberLoss
EpsilonInsensitiveLoss
KLMultinomial

Quantization Neural Network Layers

Count 6/12

NNabla Function	Status	Description
BinarySigmoid	✓
BinaryTanh	✓
BinaryConnectAffine	✓
BinaryConnectConvolution	✓
BinaryWeightAffine	✓
BinaryWeightConvolution	✓
INQAffine
INQConvolution
FixedPointQuantize
MinMaxQuantize
Pow2Quantize
Prune

Validation

Count 0/3

NNabla Function	Status	Description
TopNError
BinaryError
ConfusionMatrix

Unsupported, Special Use

Count 0/5

NNabla Function	Status	Description
VATNoise
Unlink
Sink
NmsDetection2d
MaxPoolingBackward