mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-31 23:27:43 +00:00
Bumped up to op_ver 11 for a bunch of Nuphar Ops (#2025)
This change enabled op_ver 11 for a dozen of Nuphar Ops
This commit is contained in:
Yang Chen
KeDengMS
parent
3c26ae5b6d
commit
7d2f0c79bd
4 changed files with 93 additions and 26 deletions
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@ -28,6 +28,7 @@ tvm::Tensor Gather(const tvm::Tensor& t,
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for (size_t i = axis_t + 1; i < t->shape.size(); ++i)
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output_shape.push_back(t->shape[i]);
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tvm::Expr idx_upper_bound = t->shape[axis_t];
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auto l = [&](const tvm::Array<tvm::Var>& ovars) {
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tvm::Array<tvm::Expr> ivars;
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for (size_t i = 0; i < t->shape.size(); ++i) {
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@ -37,7 +38,9 @@ tvm::Tensor Gather(const tvm::Tensor& t,
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tvm::Array<tvm::Expr> idx_vars;
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for (size_t d = 0; d < indices->shape.size(); ++d)
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idx_vars.push_back(ovars[axis_t + d]);
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ivars.push_back(tvm::cast(tvm::Int(32), indices(idx_vars))); // tvm indices must be Int32
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// make sure idx is clamped in the range of [-idx_upper_bound, idx_upper_bound - 1]
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tvm::Expr real_idx = tvm_codegen::ClampIndex(indices(idx_vars), idx_upper_bound);
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ivars.push_back(tvm::cast(tvm::Int(32), real_idx)); // tvm indices must be Int32
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} else {
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ivars.push_back(ovars[i - 1 + indices->shape.size()]);
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}
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@ -182,10 +182,22 @@ ONNX_OPERATOR_KERNEL_EX(
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.TypeConstraint("T2", DataTypeImpl::AllFixedSizeTensorExceptHalfTypes()),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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ONNX_OPERATOR_VERSIONED_KERNEL_EX(
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Gather,
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kOnnxDomain,
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1,
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10,
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kNupharExecutionProvider,
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KernelDefBuilder()
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.TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes())
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.TypeConstraint("Tind", std::vector<MLDataType>{DataTypeImpl::GetTensorType<int32_t>(),
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DataTypeImpl::GetTensorType<int64_t>()}),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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Gather,
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kOnnxDomain,
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11,
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kNupharExecutionProvider,
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KernelDefBuilder()
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.TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes())
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@ -228,10 +240,21 @@ ONNX_OPERATOR_KERNEL_EX(
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.TypeConstraint("T3", DataTypeImpl::GetTensorType<int32_t>()),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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ONNX_OPERATOR_VERSIONED_KERNEL_EX(
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Scan,
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kOnnxDomain,
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9,
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10,
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kNupharExecutionProvider,
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KernelDefBuilder()
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.TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
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.TypeConstraint("V", DataTypeImpl::AllTensorTypes()),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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Scan,
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kOnnxDomain,
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11,
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kNupharExecutionProvider,
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KernelDefBuilder()
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.TypeConstraint("I", DataTypeImpl::GetTensorType<int64_t>())
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@ -250,6 +273,17 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
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DataTypeImpl::GetTensorType<int64_t>()}),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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Scatter,
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kOnnxDomain,
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11,
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kNupharExecutionProvider,
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KernelDefBuilder()
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.TypeConstraint("T", DataTypeImpl::AllFixedSizeTensorTypes())
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.TypeConstraint("Tind", std::vector<MLDataType>{DataTypeImpl::GetTensorType<int32_t>(),
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DataTypeImpl::GetTensorType<int64_t>()}),
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nuphar::NupharKernel);
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ONNX_OPERATOR_KERNEL_EX(
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ScatterElements,
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kOnnxDomain,
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@ -75,23 +75,30 @@ class NupharKernelState {
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#define LIST_NUPHAR_OPS() \
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NUPHAR_OP(Abs, 6, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Add, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ArgMax, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ArgMax, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ArgMax, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ArgMin, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ArgMin, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ArgMin, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(AveragePool, 7, 9, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(AveragePool, 10, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(AveragePool, 11, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(Ceil, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Clip, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Concat, 4, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(Concat, 4, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Concat, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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DISABLE_MACRO(NUPHAR_OP(Conv, 1, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes())) \
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NUPHAR_OP(Crop, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Div, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Dropout, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Elu, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Equal, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(Equal, 7, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Equal, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Erf, 9, DataTypeImpl::GetTensorType<float>()) \
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NUPHAR_OP(Exp, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(Flatten, 1, 8, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Flatten, 9, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(Flatten, 9, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Flatten, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Floor, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(Gemm, 7, 8, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(Gemm, 9, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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@ -103,7 +110,8 @@ class NupharKernelState {
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NUPHAR_OP(LeakyRelu, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Less, 9, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Log, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(LogSoftmax, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(LogSoftmax, 1, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(LogSoftmax, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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DISABLE_MACRO(NUPHAR_OP(LSTM, 7, DataTypeImpl::AllIEEEFloatTensorTypes())) \
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NUPHAR_VERSIONED_OP(MatMul, 1, 8, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(MatMul, 9, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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@ -111,6 +119,7 @@ class NupharKernelState {
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NUPHAR_VERSIONED_OP(MaxPool, 1, 7, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_VERSIONED_OP(MaxPool, 8, 9, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(MaxPool, 10, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(MaxPool, 11, DataTypeImpl::AllIEEEFloatTensorExceptHalfTypes()) \
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NUPHAR_OP(Min, 8, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Mul, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Neg, 6, DataTypeImpl::AllFixedSizeTensorTypes()) \
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@ -119,27 +128,41 @@ class NupharKernelState {
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NUPHAR_OP(PRelu, 7, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Relu, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Reciprocal, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceL1, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceL2, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceLogSum, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceLogSumExp, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceMax, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceMean, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceMin, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceProd, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceSum, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceSumSquare, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceL1, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceL1, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceL2, 1, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceL2, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceLogSum, 1, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceLogSum, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceLogSumExp, 1, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(ReduceLogSumExp, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceMax, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceMax, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceMean, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceMean, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceMin, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceMin, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceProd, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceProd, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceSum, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceSum, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(ReduceSumSquare, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ReduceSumSquare, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Reshape, 5, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(ScaledTanh, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Selu, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Sigmoid, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(Slice, 1, 9, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Slice, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Softmax, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Slice, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(Softmax, 1, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Softmax, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Softplus, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Softsign, 1, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Split, 2, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Squeeze, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(Split, 2, 10, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Split, 11, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_VERSIONED_OP(Squeeze, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Squeeze, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Sqrt, 6, DataTypeImpl::AllIEEEFloatTensorTypes()) \
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NUPHAR_OP(Sub, 7, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Sum, 8, DataTypeImpl::AllFixedSizeTensorTypes()) \
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@ -147,7 +170,8 @@ class NupharKernelState {
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NUPHAR_OP(ThresholdedRelu, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Tile, 6, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Transpose, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Unsqueeze, 1, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_VERSIONED_OP(Unsqueeze, 1, 10, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Unsqueeze, 11, DataTypeImpl::AllFixedSizeTensorTypes()) \
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NUPHAR_OP(Where, 9, DataTypeImpl::AllFixedSizeTensorTypes())
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} // namespace nuphar
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@ -396,12 +396,15 @@ LIST_NUPHAR_OPS()
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 6, 8, Cast);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, Cast);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 1, Gather);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 1, 10, Gather);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Gather);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, GatherElements);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 10, MatMulInteger);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kMSDomain, 1, MatMulInteger16);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, Scan);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, 10, Scan);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Scan);
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class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, 10, Scatter);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Scatter);
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class ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, ScatterElements);
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static void RegisterStandaloneNupharKernels(KernelRegistry& kernel_registry) {
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@ -419,12 +422,15 @@ static void RegisterStandaloneNupharKernels(KernelRegistry& kernel_registry) {
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// ops that have multiple type constraints
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 6, 8, Cast)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, Cast)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 1, Gather)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 1, 10, Gather)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Gather)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, GatherElements)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 10, MatMulInteger)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kMSDomain, 1, MatMulInteger16)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, Scan)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, 10, Scan)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Scan)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 9, 10, Scatter)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, Scatter)>());
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kernel_registry.Register(BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kNupharExecutionProvider, kOnnxDomain, 11, ScatterElements)>());
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}
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