| # Tracking why operators are not covered |
| [ONNX backend test script](https://github.com/onnx/onnx-caffe2/blob/master/tests/onnx_backend_test.py) |
| reports the coverage on the operators and attributes. But we have various of reasons for the missing test coverage on operators. |
| This doc keeps tracking why operators are not covered by the testcases. |
| |
| - 💚 The ONNX operator can map to a Caffe2 operator. |
| - 💛 The solution is not perfect/finished, for example, the operator can map to a combination of Caffe2 operators. |
| - 💔 Hard to find a solution with existing Caffe2 operators. |
| |
| | Operator | Test Coverage | PyTorch | Caffe2 | |
| |---|:--:|:---:|:---:| |
| |Abs|Yes|OK|💚OK| |
| |Acos|Yes|OK|💚OK| |
| |Add|Yes|OK|💚OK| |
| |And|Yes|Support int tensor, but no bool tensor|💚OK| |
| |ArgMax|||💚OK| |
| |ArgMin|||💚OK| |
| |Asin|||💚OK| |
| |Atan|||💚OK| |
| |AveragePool||OK|💚OK| |
| |BatchNormalization||OK|💚OK| |
| |Cast|Yes||💔Need extension| |
| |Ceil|Yes||💚OK| |
| |Clip|Yes|OK|💚OK| |
| |Concat|Yes|OK|💚OK| |
| |Constant|Yes|OK|💛Special handling| |
| |Conv|Yes|OK|💚OK| |
| |ConvTranspose|Yes||💚OK, under enhancement| |
| |Cos|Yes|OK|💚OK| |
| |DepthToSpace|Yes||💔No op| |
| |Div|Yes|OK|💚OK| |
| |Dropout|Yes|OK|💚OK| |
| |Elu|Yes|OK|💚OK| |
| |Equal|Yes|OK|💚OK| |
| |Exp|Yes|OK|💚OK| |
| |Flatten|Yes|OK|💚OK| |
| |Floor|Yes||💚OK| |
| |GRU|||💚| |
| |Gather|Yes|OK|💛C2 only support axis=0 or 1, under development| |
| |Gemm|Yes|OK|💛C2 use FC or MatMul + Add| |
| |GlobalAveragePool|Yes|No direct mapping|💚OK| |
| |GlobalLpPool|||💔No mapping yet| |
| |GlobalMaxPool|||💚OK| |
| |Greater|Yes||💚OK| |
| |HardSigmoid|Yes||💔No op| |
| |Hardmax|Yes||💔No op| |
| |InstanceNormalization|||💚OK| |
| |LRN||OK|💚OK| |
| |LSTM|||💚OK| |
| |LeakyRelu|Yes|OK|💚OK| |
| |Less|Yes||💚OK| |
| |Log|Yes|OK|💚OK| |
| |LogSoftmax||OK|💚No op, translated in onnx-caffe2| |
| |LpNormalization|||💔ONNX and C2 have different definition| |
| |LpPool|||💚Should be LpPool, no tests| |
| |MatMul|Yes|OK|💚OK| |
| |Max|Yes|OK|💚OK| |
| |MaxPool||OK|💚OK| |
| |MaxRoiPool|||💔No mapping yet| |
| |Mean|||💚OK, need broadcasting support| |
| |Min|Yes|OK|💚OK, need broadcasting support| |
| |Mul|Yes|OK|💚OK, need broadcasting support| |
| |Multinomial|Yes|OK|💔no op| |
| |Neg|Yes|OK|💚OK| |
| |Not|Yes||💚OK| |
| |Or|Yes||💚OK| |
| |PRelu|Yes|OK|💛Need to enhance C2 implementation| |
| |Pad|Yes|OK|💚OK| |
| |Pow|Yes|OK|💚OK| |
| |RNN|||💚OK| |
| |RandomNormal|||💔No op| |
| |RandomNormalLike|||💔No op| |
| |RandomUniform|||💔No op| |
| |RandomUniformLike|||💔No op| |
| |Reciprocal|Yes||💚Use Pow to implement| |
| |ReduceL1|||💔No op| |
| |ReduceL2|||💔No op| |
| |ReduceLogSum|||💔No op| |
| |ReduceLogSumExp|||💔No op| |
| |ReduceMax|||💚OK| |
| |ReduceMean|||💚OK| |
| |ReduceMin|||💚OK| |
| |ReduceProd|||💚OK| |
| |ReduceSum|||💚OK| |
| |ReduceSumSquare|||💔No op| |
| |Relu|Yes|OK|💚OK| |
| |Reshape|Yes|OK|💚OK| |
| |Selu|Yes|OK|💚OK| |
| |Sigmoid|Yes|OK|💚OK| |
| |Sin|Yes|OK|💚OK| |
| |Size|Yes|OK|💚OK| |
| |Slice|Yes|OK|💔ScatterAssign + Cast, very hacky implementation, Slice in C2 only supports one dimension| |
| |Softmax|Yes|OK|💔Axis and dim has different semantics| |
| |Softplus|Yes|OK|💚OK| |
| |Softsign|Yes||💚OK| |
| |SpaceToDepth|||💔No op| |
| |Split|Yes|OK|💚OK| |
| |Sqrt|Yes||💚OK| |
| |Squeeze|Yes||💚OK| |
| |Sub|Yes|OK|💚OK| |
| |Sum|Yes|OK|💚OK, need broadcasting support| |
| |Tanh|Yes|OK|💚OK| |
| |Tile||OK|💛OK, need some enhance| |
| |TopK||OK|💚OK| |
| |Transpose|Yes|OK|💚OK| |
| |Upsample|||💛No bilinear| |
| |Xor|Yes||💚OK| |
| |experimental ATen|||💚OK| |
| |experimental Affine|||💔No op| |
| |experimental ConstantFill|||💚OK| |
| |experimental Crop|||💔No op| |
| |experimental FC|||💚OK| |
| |experimental GRUUnit|||💚OK, no tests| |
| |experimental GivenTensorFill|||💚OK| |
| |experimental Identity|||💚OK| |
| |experimental ImageScaler|||💔No op| |
| |experimental MeanVarianceNormalization|||💔No op| |
| |experimental ParametricSoftplus|||💔No op| |
| |experimental Scale|||💚OK| |
| |experimental ScaledTanh|||💔No op| |
| |experimental ThresholdedRelu|Yes||💚OK| |
