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https://gitlab.com/libeigen/eigen.git
synced 2025-08-10 10:49:04 +08:00
Fix a bunch of ODR violations.
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@ -7,8 +7,8 @@
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include <valarray>
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#include <vector>
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#include "main.h"
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using Eigen::placeholders::all;
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@ -17,11 +17,13 @@ using Eigen::placeholders::lastN;
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using Eigen::placeholders::lastp1;
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#include <array>
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namespace test {
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typedef std::pair<Index, Index> IndexPair;
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}
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int encode(Index i, Index j) { return int(i * 100 + j); }
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IndexPair decode(Index ij) { return IndexPair(ij / 100, ij % 100); }
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test::IndexPair decode(Index ij) { return test::IndexPair(ij / 100, ij % 100); }
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template <typename T>
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bool match(const T& xpr, std::string ref, std::string str_xpr = "") {
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@ -69,12 +71,10 @@ void check_indexed_view() {
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ArrayXXi A = ArrayXXi::NullaryExpr(n, n, std::ref(encode));
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for (Index i = 0; i < n; ++i)
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for (Index j = 0; j < n; ++j) VERIFY(decode(A(i, j)) == IndexPair(i, j));
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for (Index j = 0; j < n; ++j) VERIFY(decode(A(i, j)) == test::IndexPair(i, j));
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Array4i eii(4);
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eii << 3, 1, 6, 5;
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std::valarray<int> vali(4);
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Map<ArrayXi>(&vali[0], 4) = eii;
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std::vector<int> veci(4);
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Map<ArrayXi>(veci.data(), 4) = eii;
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@ -538,7 +538,7 @@ void packetmath() {
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CHECK_CWISE2_IF(PacketTraits::HasMul, REF_MUL, internal::pmul);
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CHECK_CWISE2_IF(PacketTraits::HasDiv, REF_DIV, internal::pdiv);
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CHECK_CWISE1_IF(PacketTraits::HasNegate, internal::negate, internal::pnegate);
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CHECK_CWISE1_IF(PacketTraits::HasNegate, test::negate, internal::pnegate);
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CHECK_CWISE1_IF(PacketTraits::HasReciprocal, REF_RECIPROCAL, internal::preciprocal);
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CHECK_CWISE1(numext::conj, internal::pconj);
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CHECK_CWISE1_IF(PacketTraits::HasSign, numext::sign, internal::psign);
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@ -1141,7 +1141,7 @@ void packetmath_real() {
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data1[0] = -Scalar(0.);
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h.store(data2, internal::psin(h.load(data1)));
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VERIFY(internal::biteq(data2[0], data1[0]));
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VERIFY(test::biteq(data2[0], data1[0]));
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h.store(data2, internal::pcos(h.load(data1)));
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VERIFY_IS_EQUAL(data2[0], Scalar(1));
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}
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@ -19,7 +19,8 @@
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bool g_first_pass = true;
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namespace Eigen {
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namespace internal {
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namespace test {
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template <typename T>
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T negate(const T& x) {
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@ -31,50 +32,11 @@ Map<const Array<unsigned char, sizeof(T), 1> > bits(const T& x) {
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return Map<const Array<unsigned char, sizeof(T), 1> >(reinterpret_cast<const unsigned char*>(&x));
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}
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// The following implement bitwise operations on floating point types
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template <typename T, typename Bits, typename Func>
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T apply_bit_op(Bits a, Bits b, Func f) {
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Array<unsigned char, sizeof(T), 1> data;
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T res;
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for (Index i = 0; i < data.size(); ++i) data[i] = f(a[i], b[i]);
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// Note: The reinterpret_cast works around GCC's class-memaccess warnings:
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std::memcpy(reinterpret_cast<unsigned char*>(&res), data.data(), sizeof(T));
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return res;
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}
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#define EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, T) \
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template <> \
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T EIGEN_CAT(p, OP)(const T& a, const T& b) { \
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return apply_bit_op<T>(bits(a), bits(b), FUNC); \
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}
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#define EIGEN_TEST_MAKE_BITWISE(OP, FUNC) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, float) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, double) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, half) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, bfloat16) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, std::complex<float>) \
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EIGEN_TEST_MAKE_BITWISE2(OP, FUNC, std::complex<double>)
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EIGEN_TEST_MAKE_BITWISE(xor, std::bit_xor<unsigned char>())
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EIGEN_TEST_MAKE_BITWISE(and, std::bit_and<unsigned char>())
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EIGEN_TEST_MAKE_BITWISE(or, std::bit_or<unsigned char>())
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struct bit_andnot {
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template <typename T>
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T operator()(T a, T b) const {
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return a & (~b);
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}
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};
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EIGEN_TEST_MAKE_BITWISE(andnot, bit_andnot())
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template <typename T>
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bool biteq(T a, T b) {
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return (bits(a) == bits(b)).all();
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}
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} // namespace internal
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namespace test {
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// NOTE: we disable inlining for this function to workaround a GCC issue when using -O3 and the i387 FPU.
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template <typename Scalar>
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EIGEN_DONT_INLINE bool isApproxAbs(const Scalar& a, const Scalar& b, const typename NumTraits<Scalar>::Real& refvalue) {
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@ -1007,13 +1007,14 @@ class TensorBase<Derived, ReadOnlyAccessors>
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#include EIGEN_READONLY_TENSORBASE_PLUGIN
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#endif
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
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protected:
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template <typename Scalar, int NumIndices, int Options, typename IndexType> friend class Tensor;
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template <typename Scalar, typename Dimensions, int Option, typename IndexTypes> friend class TensorFixedSize;
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// the Eigen:: prefix is required to workaround a compilation issue with nvcc 9.0
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template <typename OtherDerived, int AccessLevel> friend class Eigen::TensorBase;
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
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};
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template<typename Derived, int AccessLevel = internal::accessors_level<Derived>::value>
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@ -1199,6 +1200,11 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
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return TensorAsyncDevice<Derived, DeviceType, DoneCallback>(dev, derived(), std::move(done));
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Derived& derived() { return *static_cast<Derived*>(this); }
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
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#ifdef EIGEN_TENSORBASE_PLUGIN
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#include EIGEN_TENSORBASE_PLUGIN
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#endif
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@ -1215,10 +1221,6 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
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internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
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return derived();
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}
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE Derived& derived() { return *static_cast<Derived*>(this); }
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE const Derived& derived() const { return *static_cast<const Derived*>(this); }
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};
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#endif // EIGEN_PARSED_BY_DOXYGEN
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} // end namespace Eigen
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@ -23,9 +23,12 @@ namespace Eigen {
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template <typename ADerived, typename BDerived, typename XDerived>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorCwiseTernaryOp<internal::scalar_betainc_op<typename XDerived::Scalar>,
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const ADerived, const BDerived, const XDerived>
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betainc(const ADerived& a, const BDerived& b, const XDerived& x) {
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betainc(const Eigen::TensorBase<ADerived, ReadOnlyAccessors>& a,
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const Eigen::TensorBase<BDerived, ReadOnlyAccessors>& b,
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const Eigen::TensorBase<XDerived, ReadOnlyAccessors>& x) {
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return TensorCwiseTernaryOp<internal::scalar_betainc_op<typename XDerived::Scalar>, const ADerived, const BDerived,
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const XDerived>(a, b, x, internal::scalar_betainc_op<typename XDerived::Scalar>());
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const XDerived>(a.derived(), b.derived(), x.derived(),
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internal::scalar_betainc_op<typename XDerived::Scalar>());
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}
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} // end namespace Eigen
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