From acc1b8b5ea249f000b461443578e4ead93e67e64 Mon Sep 17 00:00:00 2001 From: Scott McKay Date: Tue, 26 Sep 2023 07:57:39 +1000 Subject: [PATCH] Update some op docs for release (#17626) ### Description Update some ops docs for 1.16 release ### Motivation and Context --- docs/reference/operators/MobileOps.md | 2 + docs/reference/operators/OperatorKernels.md | 3 +- .../mobile_package_op_type_support_1.15.md | 139 ++++++++++++++++++ .../mobile_package_op_type_support_1.16.md | 139 ++++++++++++++++++ 4 files changed, 282 insertions(+), 1 deletion(-) create mode 100644 docs/reference/operators/mobile_package_op_type_support_1.15.md create mode 100644 docs/reference/operators/mobile_package_op_type_support_1.16.md diff --git a/docs/reference/operators/MobileOps.md b/docs/reference/operators/MobileOps.md index 697ea59280fd5..8e258290b2bfe 100644 --- a/docs/reference/operators/MobileOps.md +++ b/docs/reference/operators/MobileOps.md @@ -10,6 +10,8 @@ These are the operators and types included in the ORT Mobile pre-built packages | Release | Documentation | |---------|---------------| +| 1.16 | [Pre-Built Package Support](./mobile_package_op_type_support_1.16.md)| +| 1.15 | [Pre-Built Package Support](./mobile_package_op_type_support_1.15.md)| | 1.14 | [Pre-Built Package Support](./mobile_package_op_type_support_1.14.md)| | 1.13 | [Pre-Built Package Support](./mobile_package_op_type_support_1.13.md)| | 1.12 | [Pre-Built Package Support](./mobile_package_op_type_support_1.12.md)| diff --git a/docs/reference/operators/OperatorKernels.md b/docs/reference/operators/OperatorKernels.md index fe448e397944f..caa7df1143abd 100644 --- a/docs/reference/operators/OperatorKernels.md +++ b/docs/reference/operators/OperatorKernels.md @@ -5,11 +5,12 @@ grand_parent: Reference nav_order: 1 --- -The operator kernels supported by the CPU Execution Provider and CUDA Execution Provider are documented in the ONNX Runtime repository. +The operator kernels supported by the CPU Execution Provider, CUDA Execution Provider and DML Execution Provider are documented in the ONNX Runtime repository. | Release | Documentation | |---------|---------------| | Current main | [https://github.com/microsoft/onnxruntime/blob/main/docs/OperatorKernels.md](https://github.com/microsoft/onnxruntime/blob/main/docs/OperatorKernels.md) | +| 1.16 | [https://github.com/microsoft/onnxruntime/blob/rel-1.16.0/docs/OperatorKernels.md](https://github.com/microsoft/onnxruntime/blob/rel-1.16.0/docs/OperatorKernels.md)| | 1.15 | [https://github.com/microsoft/onnxruntime/blob/rel-1.15.0/docs/OperatorKernels.md](https://github.com/microsoft/onnxruntime/blob/rel-1.15.0/docs/OperatorKernels.md)| | 1.14 | [https://github.com/microsoft/onnxruntime/blob/rel-1.14.0/docs/OperatorKernels.md](https://github.com/microsoft/onnxruntime/blob/rel-1.14.0/docs/OperatorKernels.md)| | 1.13 | [https://github.com/microsoft/onnxruntime/blob/rel-1.13.1/docs/OperatorKernels.md](https://github.com/microsoft/onnxruntime/blob/rel-1.13.1/docs/OperatorKernels.md)| diff --git a/docs/reference/operators/mobile_package_op_type_support_1.15.md b/docs/reference/operators/mobile_package_op_type_support_1.15.md new file mode 100644 index 0000000000000..31ad456421413 --- /dev/null +++ b/docs/reference/operators/mobile_package_op_type_support_1.15.md @@ -0,0 +1,139 @@ +--- +title: ORT 1.15 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| +||| diff --git a/docs/reference/operators/mobile_package_op_type_support_1.16.md b/docs/reference/operators/mobile_package_op_type_support_1.16.md new file mode 100644 index 0000000000000..ebb00dc18662c --- /dev/null +++ b/docs/reference/operators/mobile_package_op_type_support_1.16.md @@ -0,0 +1,139 @@ +--- +title: ORT 1.16 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| +|||