...
- import of ONNX models into Mxnet.
- export MXNet models to ONNX format.
ONNX-MXNET Import Module
We have two repositories for the import module:
- onnx-mxnet repository inside onnx https://github.com/onnx/onnx-mxnet (deprecated)
- A newly created and refactored module inside Mxnet -> contrib. https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/contrib/onnx/onnx2mx
MXNET-ONNX Export module
A new module has been added to MXNet repository to export MXNet models to ONNX model format. https://github.com/apache/incubator-mxnet/tree/master/python/mxnet/contrib/onnx/mx2onnx
Operator Coverage:
This table keeps track of the status of all ONNX operators supported by Mxnet.
ONNX backend test script reports the coverage on the operators and attributes.
Status meaning:
OK = currently we support the operator
OK, in review = PR is out
NOT OK, under development = Operator is missing on MXNet backend or direct 1:1 mapping doesn’t exist
NOT OK = Not supported right now
Operator | Test Coverage | Mxnet (Import) | Mxnet (Export) | ||||
---|---|---|---|---|---|---|---|
Abs | Yes | OK | OK | ||||
Acos | Yes | OK | OK | ||||
Add | Yes | OK | OK | ||||
And | Yes | OK | OK | ||||
ArgMax | Yes | OK | OK | ||||
ArgMin | Yes | OK | OK | ||||
Asin | Yes | OK | OK | ||||
Atan | Yes | OK | Ok | ||||
AveragePool | Yes | OK | OK | ||||
BatchNormalization | Yes | OK | OK | ||||
Cast | Yes | OK | OK | ||||
Ceil | Yes | OK | OK | ||||
Clip | Yes | OK | OK | ||||
Concat | Yes | OK | OK | ||||
Constant | Yes | OK | |||||
Conv | Yes | OK | OK | ||||
ConvTranspose | Yes | OK | OK | ||||
Cos | Yes | OK | OK | ||||
Crop | OK | ||||||
DepthToSpace | Yes | OK | NOT OK, under development | ||||
Div | Yes | OK | OK | ||||
Dropout | Yes | OK | OK | ||||
Elu | Yes | OK | OK | ||||
Equal | Yes | OK | OK | ||||
Exp | Yes | OK | OK | ||||
Flatten | Yes | PARTIAL, only supports default axis=1 | OK | ||||
Floor | Yes | OK | OK | ||||
GRU | NOT OK , under development | ||||||
Gather | Yes | OK | |||||
Gemm | Yes | OK | OK | ||||
GlobalAveragePool | Yes | OK | OK | ||||
GlobalLpPool | Yes | OK | OK, In review | ||||
GlobalMaxPool | Yes | OK | OK | ||||
Greater | Yes | OK | OK | ||||
HardSigmoid | Yes | OK | OK | ||||
Hardmax | Yes | OK, In review | NOT OK | ||||
Identity | NOT OK | OK | |||||
If | |||||||
InstanceNormalization | Yes | OK | OK, In review | ||||
LRN | Yes | OK | OK | ||||
LSTM | NOT OK, under development | ||||||
LeakyRelu | Yes | OK | OK | ||||
Less | Yes | OK | OK | ||||
Log | Yes | OK | OK | ||||
LogSoftMax | Yes | OK | OK | ||||
Loop | |||||||
LpNormalization | Yes | OK, In review | |||||
LpPool | Yes | OK | |||||
LpPoolMatMul | Yes | OK, In review | MatMulOK | ||||
Max | Yes | OK | OK | ||||
MaxPool | Yes | OK | OK | ||||
MaxRoiPool | Yes | OK | OK, In review | ||||
Mean | Yes | OK | OK | ||||
Min | Yes | OK | OK | ||||
Mul | Yes | OK | OK | ||||
Multinomial | Yes | OK | OK | ||||
Neg | Yes | OK | OK | ||||
Not | Yes | OK | OK | ||||
Or | Yes | OK | OK | ||||
PRelu | Yes | OK | OK | ||||
Pad | Yes | OK | OK | ||||
Pow | Yes | Partial, only supports default axis=1 | OK | ||||
RNN | NOT OK, under development | ||||||
RandomNormal | Yes | OK | OK | ||||
RandomNormalLike | Yes | OK | OK | ||||
RandomUniform | Yes | OK | OK | ||||
RandomUniformLike | Yes | OK | OK | ||||
Reciprocal | Yes | OK | OK | ||||
ReduceL1 | Yes | OK | OK | ||||
ReduceL2 | Yes | OK | OK | ||||
ReduceLogSum | Yes | OK | NOT OK | ||||
ReduceLogSumExp | Yes | OK | NOT OK | ||||
ReduceMax | Yes | OK | OK | ||||
ReduceMean | Yes | OK | OK | ||||
ReduceMin | Yes | OK | OK | ||||
ReduceProd | Yes | OK | OK | ||||
ReduceSum | Yes | OK | OK | ||||
ReduceSumSquare | Yes | OK | NOT OK | ||||
Relu | Yes | OK | OK | ||||
Reshape | Yes | OK | OK | ||||
Selu | Yes | NOT OK, under development | OK | ||||
Shape | OK | OK | |||||
Sigmoid | Yes | OK | OK | ||||
Sin | Yes | OK | OK | ||||
Size | Yes | OK | OK | ||||
Slice | Yes | Partial, supports axis=1 | OK | ||||
Softmax | Yes | OK | OK | ||||
Softplus | Yes | OK | OK | ||||
Softsign | Yes | OK | OK | ||||
SpaceToDepth | Yes | OK | NOT OK, under development | ||||
Split | Yes | OK | OK | ||||
Sqrt | Yes | OK | OK | ||||
Squeeze | Yes | OK | OK | ||||
Sub | Yes | OK | OK | ||||
Sum | Yes | OK | OK | ||||
Tan | Yes | OK | OK | ||||
Tanh | Yes | OK | OK | ||||
Tile | Yes | NOT OK, under development | NOT OK, under development | ||||
TopK | Yes | OK, in review | OK, in review | ||||
Transpose | Yes | OK | OK | ||||
Unsqueeze | Yes | OK, In review | OK | ||||
Upsample | Yes | OK, in review | OK, in review | ||||
Xor | Yes | OK | OK | ||||
experimental ATen | NOT OK, under development | ||||||
experimental Affine | NOT OK, under development | ||||||
experimental ConstantFill | NOT OK, under development | experimental Crop | NOT OK, under development | ||||
experimental GRUUnit | NOT OK, under development | ||||||
experimental GivenTensorFill | NOT OK, under development | experimental If | NOT OK | ||||
experimental ImageScaler | Yes | OK, In review | |||||
experimental LoopLoopIndexexperimental LoopIndex | NOT OK | ||||||
experimental MeanVarianceNormalization | NOT OK, under development | ||||||
experimental ParametricSoftplus | NOT OK, under development | ||||||
experimental Scale | NOT OK, under development | ||||||
experimental ScaledTanh | NOT OK, under development | ||||||
experimental ThresholdedRelu | NOT OK, under development |
...
ONNX models coverage:
ONNX backend tests include below models. The table lists current status on Mxnet:
ONNX Models | Mxnet Support |
---|---|
bvlc_alexnet | OK |
densenet121 | OK |
inception_v1 | OK, In review |
inception_v2 | OK, In review |
resnet50 | OK |
shufflenet | OK, In review |
squeezenet | OK |
vgg16 | OK |
vgg19 | OK |
bvlc_googlenet | OK |
bvlc_caffenet | OK |
bvlc-rcnn-ilsvrc13 | OK |
...