onnxruntime/tools/ci_build/github/android/mobile_package.required_operators.config
Edward Chen b1e21312b5
[Mobile package] Update required operator config with additional ops for newer version of Wav2Vec 2. (#8123)
This is an update to https://github.com/microsoft/onnxruntime/pull/8079
The sample application motivating the original update changed to use an updated version of the model. Now, fewer ops are required. This change removes the previously added ops which are no longer needed.
2021-06-22 19:19:46 -07:00

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# Android package for ORT Mobile operator and type reduction configuration
#
# The list of operators was generated from:
# - the ONNX operators use by the tf2onnx tflite converter
# - the operators used in a set of tflite models from tfhub, the tflite examples, and the mlperf mobile models
# - models were optimized with optimizations set to 'basic', 'extended' and 'all'
# - see the readme file for full details
# allow float, int8, uint8. operators that manipulate shapes or indices have int32 and int64 enabled internally.
!globally_allowed_types;float,int8_t,uint8_t
# ops used by the tf2onnx tflite converter. same list for opsets 12 and 13.
ai.onnx;12;Abs,Add,And,ArgMax,ArgMin,AveragePool,Cast,Ceil,Clip,Concat,ConstantOfShape,Conv,ConvTranspose,Cos,CumSum,DepthToSpace,DequantizeLinear,Div,DynamicQuantizeLinear,Elu,Equal,Exp,Expand,Flatten,Floor,Gather,GatherND,Gemm,Greater,GreaterOrEqual,Identity,If,LRN,LeakyRelu,Less,LessOrEqual,Log,LogSoftmax,Loop,MatMul,Max,MaxPool,Mean,Min,Mul,Neg,NonMaxSuppression,NonZero,Not,Or,PRelu,Pad,Pow,QuantizeLinear,Range,Reciprocal,ReduceMax,ReduceMean,ReduceMin,ReduceProd,ReduceSum,Relu,Reshape,Resize,ReverseSequence,Round,ScatterND,Shape,Sigmoid,Sin,Size,Slice,Softmax,SpaceToDepth,Split,Sqrt,Squeeze,Sub,Sum,Tanh,ThresholdedRelu,Tile,TopK,Transpose,Unique,Unsqueeze,Where
ai.onnx;13;Abs,Add,And,ArgMax,ArgMin,AveragePool,Cast,Ceil,Clip,Concat,ConstantOfShape,Conv,ConvTranspose,Cos,CumSum,DepthToSpace,DequantizeLinear,Div,DynamicQuantizeLinear,Elu,Equal,Exp,Expand,Flatten,Floor,Gather,GatherND,Gemm,Greater,GreaterOrEqual,Identity,If,LRN,LeakyRelu,Less,LessOrEqual,Log,LogSoftmax,Loop,MatMul,Max,MaxPool,Mean,Min,Mul,Neg,NonMaxSuppression,NonZero,Not,Or,PRelu,Pad,Pow,QuantizeLinear,Range,Reciprocal,ReduceMax,ReduceMean,ReduceMin,ReduceProd,ReduceSum,Relu,Reshape,Resize,ReverseSequence,Round,ScatterND,Shape,Sigmoid,Sin,Size,Slice,Softmax,SpaceToDepth,Split,Sqrt,Squeeze,Sub,Sum,Tanh,ThresholdedRelu,Tile,TopK,Transpose,Unique,Unsqueeze,Where
# other ops found in test models
ai.onnx;12;Erf,GlobalAveragePool,InstanceNormalization,MatMulInteger,QLinearConv,QLinearMatMul
ai.onnx;13;Erf,GlobalAveragePool,InstanceNormalization,MatMulInteger,QLinearConv,QLinearMatMul
# Control flow ops
# - If and Loop are covered by the tflite converter list
# - Scan tends to be used in speech models (it's more efficient than Loop) so include it for support of those
ai.onnx;12;Scan
ai.onnx;13;Scan
# internal ops added by optimizers
# Note: LayerNormalization is an internal op even though it is (incorrectly) registered in the ONNX domain.
ai.onnx;1;LayerNormalization
com.microsoft;1;DynamicQuantizeMatMul,FusedConv,FusedGemm,FusedMatMul,Gelu,MatMulIntegerToFloat,NhwcMaxPool,QLinearAdd,QLinearAveragePool,QLinearConv,QLinearGlobalAveragePool,QLinearMul,QLinearSigmoid
# NHWC transformer also uses this, so assuming it's valuable enough to include
com.microsoft;1;QLinearLeakyRelu
# Quantized contrib ops that are registered but no usage was found. Excluding for now.
# com.microsoft;1;DynamicQuantizeLSTM,QAttention