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[CK_TILE] Add Various Fusion Functions to RMSNorm (#1802)
* Add shortcut to RMSNorm
* Modify test for adding shortcut for RMSNorm
* Add fused parameter into tests
* 1. Add YDataType. 2. rmsnorm2d_fwd_traits_ from rmsnorm2d_fwd.hpp to rmsnorm2d_fwd_api.cpp and rmsnorm2d_fwd_instance_common.hpp
* 1. Supports various stride and percisions.
* Add support of Epilogue
* Add fuse and epilogue support to rmsnorm ref
* Modify rmsnorm example
* Refactor tests/examples
* Bug fix for newly added tests/examples
* Bug fix for new tests 2
* Modify smoke test scripts
remove dbg code
* Supports non-smooth dyanmic quant
* Update Rmsnorm2dFwd::GetName()
* rename xscale and prec_sx to smoothscale and prec_sm
Bug fix after rename
Remove files
* change example_rmsnorm2d_fwd.cpp
* update performance calculator
* Fix issue in two-pass when fuse add is enabled
* Remove comment of beta
---------
Co-authored-by: rocking <ChunYu.Lai@amd.com>
[ROCm/composable_kernel commit: 04dd314883]
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@@ -8,16 +8,40 @@
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namespace ck_tile {
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// Note: for simplicity, each functor only care about single M
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struct reference_rmsnorm2d_default_epilogue
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{
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template <typename OutDataType, typename AccDataType>
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void operator()(int m, HostTensor<OutDataType>& o, const HostTensor<AccDataType>& acc)
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{
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const int N = acc.mDesc.get_lengths()[1];
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for(int n = 0; n < N; ++n)
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{
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o(m, n) = ck_tile::type_convert<OutDataType>(acc(m, n));
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}
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}
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template <typename OutDataType, typename AccDataType>
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auto operator()(int m, const HostTensor<AccDataType>& acc)
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{
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HostTensor<OutDataType> o(acc.get_lengths(), acc.get_strides());
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operator()(m, o, acc);
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return o;
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}
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};
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template <typename XDataType,
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typename GammaDataType,
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typename ComputeDataType,
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typename YDataType,
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typename InvRmsDataType>
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typename InvRmsDataType,
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typename Epilogue = reference_rmsnorm2d_default_epilogue>
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void reference_rmsnorm2d_fwd(const HostTensor<XDataType>& x_m_n,
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const HostTensor<GammaDataType>& gamma_n,
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HostTensor<YDataType>& y_m_n,
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HostTensor<InvRmsDataType>& invRms_m,
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ComputeDataType epsilon)
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ComputeDataType epsilon,
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Epilogue epilogue_functor = {})
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{
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auto rmsnorm2d_fwd_func = [&](auto m) {
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const int N = x_m_n.mDesc.get_lengths()[1];
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@@ -37,13 +61,15 @@ void reference_rmsnorm2d_fwd(const HostTensor<XDataType>& x_m_n,
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if constexpr(!std::is_same_v<InvRmsDataType, ck_tile::null_type>)
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invRms_m(m) = ck_tile::type_convert<InvRmsDataType>(divisor);
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HostTensor<ComputeDataType> acc(x_m_n.get_lengths(), x_m_n.get_strides());
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for(int n = 0; n < N; ++n)
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{
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ComputeDataType x = ck_tile::type_convert<ComputeDataType>(x_m_n(m, n));
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ComputeDataType gamma = ck_tile::type_convert<ComputeDataType>(gamma_n(n));
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auto y = x * divisor * gamma;
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y_m_n(m, n) = ck_tile::type_convert<YDataType>(y);
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acc(m, n) = x * divisor * gamma;
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}
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epilogue_functor(m, y_m_n, acc);
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};
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make_ParallelTensorFunctor(rmsnorm2d_fwd_func, invRms_m.mDesc.get_lengths()[0])(
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