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<!-- Thanks for contributing a merge request! We recommend that first-time contributors read our [contribution guidelines](https://eigen.tuxfamily.org/index.php?title=Contributing_to_Eigen). Before submitting the MR, please complete the following checks: - Create one PR per feature or bugfix, - Run the test suite to verify your changes. See our [test guidelines](https://eigen.tuxfamily.org/index.php?title=Tests). - Add tests to cover the bug addressed or any new feature. - Document new features. If it is a substantial change, add it to the [Changelog](https://gitlab.com/libeigen/eigen/-/blob/master/CHANGELOG.md). - Leave the following box checked when submitting: `Allow commits from members who can merge to the target branch`. This allows us to rebase and merge your change. Note that we are a team of volunteers; we appreciate your patience during the review process. --> ### Description <!--Please explain your changes.--> Fix MKL enum conversion warning. ### Reference issue <!-- You can link to a specific issue using the gitlab syntax #<issue number>. If the MR fixes an issue, write "Fixes #<issue number>" to have the issue automatically closed on merge. --> Fixes #2999. Closes #2999 See merge request libeigen/eigen!2061
184 lines
12 KiB
C++
184 lines
12 KiB
C++
/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to Intel(R) MKL
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* MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
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********************************************************************************
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*/
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#ifndef EIGEN_ASSIGN_VML_H
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#define EIGEN_ASSIGN_VML_H
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// IWYU pragma: private
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#include "./InternalHeaderCheck.h"
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namespace Eigen {
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namespace internal {
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template <typename Dst, typename Src>
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class vml_assign_traits {
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private:
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enum {
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DstHasDirectAccess = Dst::Flags & DirectAccessBit,
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SrcHasDirectAccess = Src::Flags & DirectAccessBit,
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StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
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InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
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: int(Dst::Flags) & RowMajorBit ? int(Dst::ColsAtCompileTime)
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: int(Dst::RowsAtCompileTime),
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InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
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: int(Dst::Flags) & RowMajorBit ? int(Dst::MaxColsAtCompileTime)
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: int(Dst::MaxRowsAtCompileTime),
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MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
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MightEnableVml = bool(StorageOrdersAgree) && bool(DstHasDirectAccess) && bool(SrcHasDirectAccess) &&
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Src::InnerStrideAtCompileTime == 1 && Dst::InnerStrideAtCompileTime == 1,
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MightLinearize = bool(MightEnableVml) && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
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VmlSize = bool(MightLinearize) ? MaxSizeAtCompileTime : InnerMaxSize,
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LargeEnough = (VmlSize == Dynamic) || VmlSize >= EIGEN_MKL_VML_THRESHOLD
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};
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public:
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enum { EnableVml = MightEnableVml && LargeEnough, Traversal = MightLinearize ? LinearTraversal : DefaultTraversal };
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};
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#define EIGEN_PP_EXPAND(ARG) ARG
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#if !defined(EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
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#define EIGEN_VMLMODE_EXPAND_xLA , VML_HA
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#else
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#define EIGEN_VMLMODE_EXPAND_xLA , VML_LA
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#endif
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#define EIGEN_VMLMODE_EXPAND_x_
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#define EIGEN_VMLMODE_PREFIX_xLA vm
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#define EIGEN_VMLMODE_PREFIX_x_ v
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#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x, VMLMODE)
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#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
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template <typename DstXprType, typename SrcXprNested> \
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struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, \
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assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense, \
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std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> { \
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typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
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static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
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resize_if_allowed(dst, src, func); \
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eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
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if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == (int)LinearTraversal) { \
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VMLOP(dst.size(), (const VMLTYPE *)src.nestedExpression().data(), \
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(VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
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} else { \
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const Index outerSize = dst.outerSize(); \
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for (Index outer = 0; outer < outerSize; ++outer) { \
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const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer, 0)) \
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: &(src.nestedExpression().coeffRef(0, outer)); \
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EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \
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VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, \
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(VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
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} \
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} \
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} \
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};
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#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), s##VMLOP), float, float, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), d##VMLOP), double, double, VMLMODE)
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#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), c##VMLOP), scomplex, \
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MKL_Complex8, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), z##VMLOP), dcomplex, \
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MKL_Complex16, VMLMODE)
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#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
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// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
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EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(cbrt, Cbrt, _)
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#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
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template <typename DstXprType, typename SrcXprNested, typename Plain> \
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struct Assignment<DstXprType, \
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CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested, \
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const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>, \
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assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense, \
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std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> { \
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typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested, \
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const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>> \
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SrcXprType; \
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static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
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resize_if_allowed(dst, src, func); \
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eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
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VMLTYPE exponent = reinterpret_cast<const VMLTYPE &>(src.rhs().functor().m_other); \
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if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == LinearTraversal) { \
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VMLOP(dst.size(), (const VMLTYPE *)src.lhs().data(), exponent, \
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(VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
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} else { \
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const Index outerSize = dst.outerSize(); \
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for (Index outer = 0; outer < outerSize; ++outer) { \
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const EIGENTYPE *src_ptr = \
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src.IsRowMajor ? &(src.lhs().coeffRef(outer, 0)) : &(src.lhs().coeffRef(0, outer)); \
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EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \
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VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, exponent, \
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(VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
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} \
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} \
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} \
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};
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EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
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EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
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EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
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EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
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} // end namespace internal
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} // end namespace Eigen
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#endif // EIGEN_ASSIGN_VML_H
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