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* fix boost download url (#7843) * Topo sort the model before saving (#7913) * checkin toposort * review comments * revert and add TODO * Add shape inference to custom symbolic functions (#7937) **Description**: As title. **Motivation and Context** - PyTorch ONNX exporter heavily depends on ONNX shape inference to export accurate and efficient model. Custom symbolic function exports the op as contrib ops, thus exporter is unable to perform standard onnx shape inference. Models with dynamic shape inputs are affected. * Fix missing files on linux (#8066) * [Mobile package] Update required operator config with additional ops for wav2vec2. (#8079) Add some additional ops to the mobile package that are needed for the wav2vec2 model. * Add module attribute to ORTModule to support HuggingFace Trainer save_model (#8088) * Fix input schema extrator for ORTModule (#8098) * Fix 32bit Android java API crash (#8122) * Fix 32bit Android java API crash * fix code formating * [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. * Add int64 as a required type to ConstantOfShape as it's used by the pytorch converter for Pad. (#8128) It's also used pointlessly for torch.tensor.repeat (although that usage should always be able to be constant folded). * Update logic in props.xml to account for shared provider library changes (#8138) * Ortmodule override torch.manual_seed() (#8131) * Ortmodule override torch.manual_seed() * Fix Python Cuda loading issues (#7939) * Fix mac shared_provider warning (#8153) Co-authored-by: Guoyu Wang <62914304+gwang-msft@users.noreply.github.com> Co-authored-by: Ye Wang <52801275+wangyems@users.noreply.github.com> Co-authored-by: Bowen Bao <bowbao@microsoft.com> Co-authored-by: Ryan Hill <38674843+RyanUnderhill@users.noreply.github.com> Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> Co-authored-by: baijumeswani <bmeswani@microsoft.com> Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com> Co-authored-by: Scott McKay <skottmckay@gmail.com> Co-authored-by: Hariharan Seshadri <shariharan91@gmail.com> Co-authored-by: Sherlock <baihan.huang@gmail.com>
34 lines
3 KiB
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34 lines
3 KiB
Text
# Android package for ORT Mobile operator and type reduction configuration
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#
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# The list of operators was generated from:
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# - the ONNX operators use by the tf2onnx tflite converter
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# - the operators used in a set of tflite models from tfhub, the tflite examples, and the mlperf mobile models
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# - models were optimized with optimizations set to 'basic', 'extended' and 'all'
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# - see the readme file for full details
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# allow float, int8, uint8. operators that manipulate shapes or indices have int32 and int64 enabled internally.
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!globally_allowed_types;float,int8_t,uint8_t
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# ops used by the tf2onnx tflite converter. same list for opsets 12 and 13.
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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
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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
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# other ops found in test models
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ai.onnx;12;Erf,GlobalAveragePool,InstanceNormalization,MatMulInteger,QLinearConv,QLinearMatMul
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ai.onnx;13;Erf,GlobalAveragePool,InstanceNormalization,MatMulInteger,QLinearConv,QLinearMatMul
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# Control flow ops
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# - If and Loop are covered by the tflite converter list
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# - Scan tends to be used in speech models (it's more efficient than Loop) so include it for support of those
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ai.onnx;12;Scan
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ai.onnx;13;Scan
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# internal ops added by optimizers
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# Note: LayerNormalization is an internal op even though it is (incorrectly) registered in the ONNX domain.
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ai.onnx;1;LayerNormalization
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com.microsoft;1;DynamicQuantizeMatMul,FusedConv,FusedGemm,FusedMatMul,Gelu,MatMulIntegerToFloat,NhwcMaxPool,QLinearAdd,QLinearAveragePool,QLinearConv,QLinearGlobalAveragePool,QLinearMul,QLinearSigmoid
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# NHWC transformer also uses this, so assuming it's valuable enough to include
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com.microsoft;1;QLinearLeakyRelu
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# Quantized contrib ops that are registered but no usage was found. Excluding for now.
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# com.microsoft;1;DynamicQuantizeLSTM,QAttention
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