FunctionLevel 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 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
andstrides
larger than 1 are not supported by tensorflow.DepthwiseConvolution
△
The cases
dilations
andstrides
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
andstrides
larger than 1 are not supported by tensorflow.BinaryWeightAffine
✓
BinaryWeightConvolution
△
The cases
dilations
andstrides
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