From e88f9d58f0f49222ae0db43c524937cd810c2b59 Mon Sep 17 00:00:00 2001 From: Scott McKay Date: Thu, 1 Feb 2024 09:12:09 +1000 Subject: [PATCH] Add 1.17 mobile package info. Same as 1.16 (#19339) ### Description Add list of operators/types for 1.17 mobile package. Unchanged from 1.16. ### Motivation and Context --- .../mobile_package_op_type_support_1.17.md | 139 ++++++++++++++++++ 1 file changed, 139 insertions(+) create mode 100644 docs/reference/operators/mobile_package_op_type_support_1.17.md diff --git a/docs/reference/operators/mobile_package_op_type_support_1.17.md b/docs/reference/operators/mobile_package_op_type_support_1.17.md new file mode 100644 index 0000000000..9e0573d492 --- /dev/null +++ b/docs/reference/operators/mobile_package_op_type_support_1.17.md @@ -0,0 +1,139 @@ +--- +title: ORT 1.17 Mobile Package Operators +parent: Operators +grand_parent: Reference +nav_exclude: true +--- + +# ONNX Runtime Mobile Pre-Built Package Operator and Type Support + +## Supported operators and types + +The supported operators and types are based on what is required to support float32 and quantized versions of popular models. The full list of input models used to determine this list is available [here](https://github.com/microsoft/onnxruntime/blob/main/tools/ci_build/github/android/mobile_package.required_operators.readme.txt) + +## Supported data input types + + - float + - int8_t + - uint8_t + +NOTE: Operators used to manipulate dimensions and indices will support int32 and int64. + +## Supported Operators + +|Operator|Opsets| +|--------|------| +|**ai.onnx**|| +|ai.onnx:Abs|12, 13, 14, 15| +|ai.onnx:Add|12, 13, 14, 15| +|ai.onnx:And|12, 13, 14, 15| +|ai.onnx:ArgMax|12, 13, 14, 15| +|ai.onnx:ArgMin|12, 13, 14, 15| +|ai.onnx:AveragePool|12, 13, 14, 15| +|ai.onnx:Cast|12, 13, 14, 15| +|ai.onnx:Ceil|12, 13, 14, 15| +|ai.onnx:Clip|12, 13, 14, 15| +|ai.onnx:Concat|12, 13, 14, 15| +|ai.onnx:ConstantOfShape|12, 13, 14, 15| +|ai.onnx:Conv|12, 13, 14, 15| +|ai.onnx:ConvTranspose|12, 13, 14, 15| +|ai.onnx:Cos|12, 13, 14, 15| +|ai.onnx:CumSum|12, 13, 14, 15| +|ai.onnx:DepthToSpace|12, 13, 14, 15| +|ai.onnx:DequantizeLinear|12, 13, 14, 15| +|ai.onnx:Div|12, 13, 14, 15| +|ai.onnx:DynamicQuantizeLinear|12, 13, 14, 15| +|ai.onnx:Elu|12, 13, 14, 15| +|ai.onnx:Equal|12, 13, 14, 15| +|ai.onnx:Erf|12, 13, 14, 15| +|ai.onnx:Exp|12, 13, 14, 15| +|ai.onnx:Expand|12, 13, 14, 15| +|ai.onnx:Flatten|12, 13, 14, 15| +|ai.onnx:Floor|12, 13, 14, 15| +|ai.onnx:Gather|12, 13, 14, 15| +|ai.onnx:GatherND|12, 13, 14, 15| +|ai.onnx:Gemm|12, 13, 14, 15| +|ai.onnx:GlobalAveragePool|12, 13, 14, 15| +|ai.onnx:Greater|12, 13, 14, 15| +|ai.onnx:GreaterOrEqual|12, 13, 14, 15| +|ai.onnx:HardSigmoid|12, 13, 14, 15| +|ai.onnx:Identity|12, 13, 14, 15| +|ai.onnx:If|12, 13, 14, 15| +|ai.onnx:InstanceNormalization|12, 13, 14, 15| +|ai.onnx:LRN|12, 13, 14, 15| +|ai.onnx:LayerNormalization|1| +|ai.onnx:LeakyRelu|12, 13, 14, 15| +|ai.onnx:Less|12, 13, 14, 15| +|ai.onnx:LessOrEqual|12, 13, 14, 15| +|ai.onnx:Log|12, 13, 14, 15| +|ai.onnx:LogSoftmax|12, 13, 14, 15| +|ai.onnx:Loop|12, 13, 14, 15| +|ai.onnx:MatMul|12, 13, 14, 15| +|ai.onnx:MatMulInteger|12, 13, 14, 15| +|ai.onnx:Max|12, 13, 14, 15| +|ai.onnx:MaxPool|12, 13, 14, 15| +|ai.onnx:Mean|12, 13, 14, 15| +|ai.onnx:Min|12, 13, 14, 15| +|ai.onnx:Mul|12, 13, 14, 15| +|ai.onnx:Neg|12, 13, 14, 15| +|ai.onnx:NonMaxSuppression|12, 13, 14, 15| +|ai.onnx:NonZero|12, 13, 14, 15| +|ai.onnx:Not|12, 13, 14, 15| +|ai.onnx:Or|12, 13, 14, 15| +|ai.onnx:PRelu|12, 13, 14, 15| +|ai.onnx:Pad|12, 13, 14, 15| +|ai.onnx:Pow|12, 13, 14, 15| +|ai.onnx:QLinearConv|12, 13, 14, 15| +|ai.onnx:QLinearMatMul|12, 13, 14, 15| +|ai.onnx:QuantizeLinear|12, 13, 14, 15| +|ai.onnx:Range|12, 13, 14, 15| +|ai.onnx:Reciprocal|12, 13, 14, 15| +|ai.onnx:ReduceMax|12, 13, 14, 15| +|ai.onnx:ReduceMean|12, 13, 14, 15| +|ai.onnx:ReduceMin|12, 13, 14, 15| +|ai.onnx:ReduceProd|12, 13, 14, 15| +|ai.onnx:ReduceSum|12, 13, 14, 15| +|ai.onnx:Relu|12, 13, 14, 15| +|ai.onnx:Reshape|12, 13, 14, 15| +|ai.onnx:Resize|12, 13, 14, 15| +|ai.onnx:ReverseSequence|12, 13, 14, 15| +|ai.onnx:Round|12, 13, 14, 15| +|ai.onnx:Scan|12, 13, 14, 15| +|ai.onnx:ScatterND|12, 13, 14, 15| +|ai.onnx:Shape|12, 13, 14, 15| +|ai.onnx:Sigmoid|12, 13, 14, 15| +|ai.onnx:Sin|12, 13, 14, 15| +|ai.onnx:Size|12, 13, 14, 15| +|ai.onnx:Slice|12, 13, 14, 15| +|ai.onnx:Softmax|12, 13, 14, 15| +|ai.onnx:SpaceToDepth|12, 13, 14, 15| +|ai.onnx:Split|12, 13, 14, 15| +|ai.onnx:Sqrt|12, 13, 14, 15| +|ai.onnx:Squeeze|12, 13, 14, 15| +|ai.onnx:Sub|12, 13, 14, 15| +|ai.onnx:Sum|12, 13, 14, 15| +|ai.onnx:Tanh|12, 13, 14, 15| +|ai.onnx:ThresholdedRelu|12, 13, 14, 15| +|ai.onnx:Tile|12, 13, 14, 15| +|ai.onnx:TopK|12, 13, 14, 15| +|ai.onnx:Transpose|12, 13, 14, 15| +|ai.onnx:Unique|12, 13, 14, 15| +|ai.onnx:Unsqueeze|12, 13, 14, 15| +|ai.onnx:Where|12, 13, 14, 15| +||| +|**com.microsoft**|| +|com.microsoft:DynamicQuantizeMatMul|1| +|com.microsoft:FusedConv|1| +|com.microsoft:FusedGemm|1| +|com.microsoft:FusedMatMul|1| +|com.microsoft:Gelu|1| +|com.microsoft:MatMulIntegerToFloat|1| +|com.microsoft:NhwcMaxPool|1| +|com.microsoft:QLinearAdd|1| +|com.microsoft:QLinearAveragePool|1| +|com.microsoft:QLinearConv|1| +|com.microsoft:QLinearGlobalAveragePool|1| +|com.microsoft:QLinearLeakyRelu|1| +|com.microsoft:QLinearMul|1| +|com.microsoft:QLinearSigmoid|1| +|||