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https://github.com/saymrwulf/onnxruntime.git
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c9240f4e93
* Implement Nuphar execution provider Nuphar execution provider is a TVM-based compilation provider. It has shown great speedups for RNN models using Scan. This PR is mainly for a preview of the shared codegen library for other TVM-based providers. * Fix submodules * Fix TVM submodule * Update Nuphar to latest and resolve confliction * Remove stale files caused by merge -X theirs * Revert heap buffer change to not introduce onnxruntime_framework into onnxruntime_perf_test * Fix bad merge * Merge from Nuphar * Fix warning treated as error, revert some unnecessary changes * Revert some more test changes * Some more test revert or comments to make review easier New tests could be added later * One more revert of unnecessary changes * More change revert. Test could be added back later.
30 lines
966 B
C++
30 lines
966 B
C++
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#include "core/codegen/mti/math/gemm.h"
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#include "core/codegen/mti/math/matmul_ops.h"
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#include "core/codegen/mti/mti_tvm_utils.h"
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#include <topi/broadcast.h>
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// Using namespace topi for override operator +-*/
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using namespace topi;
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namespace onnxruntime {
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namespace tvm_codegen {
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tvm::Tensor Gemm(const tvm::Tensor& A, const tvm::Tensor& B, const tvm::Tensor& C,
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bool trans_A, bool trans_B, float alpha, float beta,
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const std::string& name) {
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auto A_dot_B = MatMul2D(A, B, trans_A, trans_B, name + "_matmul2d");
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tvm::Expr alphaExpr = tvm::make_const(A->dtype, alpha);
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if (beta != 0) {
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tvm::Expr betaExpr = tvm::make_const(A->dtype, beta);
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return Rename(alphaExpr * A_dot_B + (betaExpr * C), name);
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} else {
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return Rename(alphaExpr * A_dot_B, name);
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}
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}
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} // namespace tvm_codegen
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} // namespace onnxruntime
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